Review ArticleFilters in 2D and 3D Cardiac SPECT Image Processing
Maria Lyra1 Agapi Ploussi2 Maritina Rouchota1 and Stella Synefia1
1 1st Department of Radiology Faculty of Medicine Aretaieion Hospital University of Athens 11528 Athens Greece2 2nd Department of Radiology Faculty of Medicine Aretaieion Hospital University of Athens 11528 Athens Greece
Correspondence should be addressed to Maria Lyra mlyrameduoagr
Received 23 October 2013 Accepted 20 January 2014 Published 1 April 2014
Academic Editor Gavin W Lambert
Copyright copy 2014 Maria Lyra et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited
Nuclear cardiac imaging is a noninvasive sensitive method providing information on cardiac structure and physiology Singlephoton emission tomography (SPECT) evaluatesmyocardial perfusion viability and function and is widely used in clinical routineThe quality of the tomographic image is a key for accurate diagnosis Image filtering a mathematical processing compensates forloss of detail in an image while reducing image noise and it can improve the image resolution and limit the degradation of theimage SPECT images are then reconstructed either by filter back projection (FBP) analytical technique or iteratively by algebraicmethods The aim of this study is to review filters in cardiac 2D 3D and 4D SPECT applications and how these affect the imagequality mirroring the diagnostic accuracy of SPECT images Several filters including the Hanning Butterworth and Parzen filterswere evaluated in combination with the two reconstruction methods as well as with a specified MatLab program Results showedthat for both 3D and 4D cardiac SPECT the Butterworth filter for different critical frequencies and orders produced the best resultsBetween the two reconstruction methods the iterative one might be more appropriate for cardiac SPECT since it improves lesiondetectability due to the significant improvement of image contrast
1 Introduction
Cardiovascular disease (CVD) is a general term used toencompass various types of heart disease including coronaryheart disease (ischemic heart disease) pulmonary heartdisease stroke (cerebrovascular disease) diseases of arteriesand other diseases of veins heart failure and rheumatic heartdisease CVD is the leading cause of death in the developedworld accounting for approximately 17 million deaths peryear It is estimated that CVD is responsible for around 1 inevery 3 deaths in men and 1 in every 5 deaths in womenCVD affects infant children and adults both genders andall ethnicities [1]
It has been observed that in many cases CVD events areconnected to diseases such as chronic kidney disease (CKD)andmetabolic syndrome (MetS) [2] Such diseases may act asstrong predictors of CVD allowing an earlier diagnosis
Nuclear imaging plays an important role and is con-sidered a current standard in the diagnosis of CVD Single
photon emission tomography (SPECT) and positron emis-sion tomography (PET) techniques evaluating myocardialperfusion viability and function are widely used in clinicalroutine [3]
The quality of the tomographic image is a key for theaccurate diagnosis Image filtering can greatly improve theimage quality and yield information that otherwise couldhave been missed There are several types of filters used inmedical imaging and the choice of the appropriate filter inclinical practice is not an easy work [4]
Through cardiac SPECT myocardial perfusion defectsas well as the overall coronary artery disease (CAD) canbe detected 3D surface images of the myocardium providea relationship between the location and the degree of thestenosis in coronary arteries and the observed perfusion onthe myocardial scintigraphy The impact evolution of thesestenoses can then be predicted and coronarography can bejustified or avoided
Hindawi Publishing CorporationCardiology Research and PracticeVolume 2014 Article ID 963264 11 pageshttpdxdoiorg1011552014963264
2 Cardiology Research and Practice
2 Basic Principles of Cardiac SPECT Imaging
21 Myocardium Data Acquisition SPECT provides three-dimensional images that facilitate both a visual and a quan-titative evaluation of the cardiac radionuclide distributionand of the surrounding tissues by removing superimposedactivity from surrounding tissues [5]
The administrated radioisotope in the patientrsquos bodyemits single gamma ray photons that are recorded througha gamma camera mounted on a gantry in numerous projec-tions around the patient Both contour and elliptical orbitscan be used The projection acquisition may be performedin three different ways step-and-shoot continuous andcontinuous step-and-shoot The method mostly used is thestep-and-shoot method For a given orbit the camera stopsat predefined angular positions and acquires a projection forpredefined time durations An arc of 180 degrees is usuallycovered that is 45 degrees right anterior oblique to leftposterior oblique (RAO-LPO) [5] Equal times are used toachieve the same count statistics
Another parameter that greatly affects the image quality(sensitivity and resolution) is the choice of the collimatorThis is determined mainly by the tracer activity When 201Tlis being used a low-energy general purpose collimator istraditionally chosen For 99Tc-labeled agents high resolutioncollimators are recommended whereas for 111In and 123ImdashMIBG (metaiodobenzylguanidine) medium energy collima-tors are usually used [5]
Other important parameters that are to be taken intoaccount during acquisition are the projection matrix size thenumber of angles and the time per view For the projectionmatrix a common rule of thumb is that at least three pixelsshould be used to image a structure for each full width athalf maximum (FWHM) of the response profile For thenumber of angles the time per view determines the statisticalcontent of the projected imageThe interrelationship of theseparameters is quite complicated
In most cardiac SPECT protocols a 180∘ camera rotationwith 64 times 64 matrix size is recommended [6] The 2Dprojection-images are first corrected for nonuniformities andthen mathematical algorithms are used to reconstruct 3Dmatrices of selected planes from the 2D projection data
22 Myocardium Image Reconstruction Techniques The pur-pose of reconstruction algorithms is to calculate an accurate3D radioactivity distribution from the acquired projectionsThere are two methods to reconstruct SPECT images eitherby filter back projection (FBP) analytical technique or itera-tively by algebraic methods
221 Filtered Back Projection Method (FBP) Filtered backprojection is an analytical method that is still the most widelyused in clinical SPECT because of its simplicity speed andcomputational efficiency FBP consists of two steps filteringof data and back projection of the filtered data [7]
In 2D acquisition each row of projections represents thesum of all counts along a straight line through the depth
of the object being imaged Back projection technique redis-tributes the number of counts at each particular point backalong a line from which they were originally detected Thisprocess is repeated for all pixels and all angles A limitednumber of projection sets can result in the formation ofthe star artifact and in blurring of the image To eliminatethis problem the projections are filtered before being backprojected onto the image matrix It has to be noticed thatthe back projection process has taken place in spatial domainwhile data filtration is done in the frequency domain Whilethe analytic approaches typically result in fast reconstruc-tion algorithms accuracy of the reconstructed images islimited by the approximations in the line-integral model onwhich the reconstruction formulae are based [8] CardiacSPECT reconstruction process may obtain attenuation cor-rections approximately using a postprocessing step [9] Somereconstruction algorithms apply approximation formulas tothe projection data for attenuation correction Lee-Tzuu[9] applied a simple effective two-step procedure to theuncorrected image For two-dimensional (2D) SPECT withparallel or fan beam collimators 2D filtered back projection(FBP) algorithms are routinely used for myocardium SPECTreconstruction
222 Iterative Reconstruction Method Iterative reconstruc-tion starts with an initial estimate of the image [7] Most ofthe times the initial estimate is very simple for example auniform activity distribution Then a set of projection data isestimated from the initial estimate using a mathematical pro-cess called forward projection The resulting projections arecompared with the recorded projections and the differencesbetween the two are used to update the estimated image Theiterative process is repeated until the differences between thecalculated and measured data are smaller than a specifiedpreselected value
Data from SPECT systems using parallel fan beam andcone beam collimators can be modelled as sets of line inte-grals of the tracer density along the collimation directionsConsequently SPECT images can be reconstructed usinganalytic inversion methods that are based on the relationshipbetween a function and its line integrals
For 3D SPECT the iterative reconstruction methodsinclude algebraic methods like the algebraic reconstructiontechnique (ART) and statistical algorithms like maximumlikelihood expectation maximization (ML-EM) or orderedsubsets expectation maximization (OS-EM) [10] The ML-EM algorithm is a general approach to solving maximumlikelihood problems through the introduction of a set of datawhich if observed would make the ML problem readilysolvable The algorithm then iterates between computing themean of the complete data given the observed data and thecurrent estimate of the image andmaximizing the probabilityof the complete data over the image space In the orderedsubsets EM (OS-EM) method the full set of views is dividedinto subsets and the EM algorithm applied sequentially toeach of these data sets in turn This produces remarkableimprovements in the initial convergence rate compared toML-EM [8]
Cardiology Research and Practice 3
23 Image Processing in 3D and 4D Cardiac SPECT Afterthe planar images have been obtained for several projectionangles a 3D reconstruction can be performed using differentmethods and the appropriate filters The first method is byusing a type of commercially available software for SPECTimaging Such software with different filters is discussed inSection 51 Another method is by using a specified program-ming code Such a MatLab code is tested in Section 52again for multiple filters When a spatiotemporal approachis of need electrocardiogram- (ECG-) gated SPECT can beperformed In ECG-gated SPECT data from specific partsof the cardiac cycle can be isolated This method is furtherexplained in Section 6
24 Image Filtering in Cardiac SPECT Different filter typesin SPECT imaging can produce different optimal resultsin processed images such as star artifact reduction noisesuppression or signal enhancement and restoration [4] Thechoice of filter for a given image processing task is generally acompromise between the extent of noise reduction fine detailsuppression and contrast enhancement as well as the spatialfrequency pattern of the image data of interest
Filters that are commonly used on SPECT imaging arethe Ramp filter a high pass filter eliminating the star artifactand blurring the Hanning filter a low pass smoothing filterthe Hamming filter also a low pass smoothing filter having adifferent amplitude at the cutoff frequency the Butterworthfilter which both smoothers noise and preserves the imageresolution the Parzen filter the most smoothing low passfilter and the Shepp-Logan filter which is the least smoothingbut has the highest resolution [4] Two enhancement filtersalso used in cardiac SPECT are the Metz filter a function ofmodulation transfer function and the Wiener filter which isbased on the signal-to-noise ratio of the specific image
The filters mostly used in cardiac SPECT imaging arepresented with a greater detail in the next paragraphs Amore extensive presentation of all the mentioned filters canbe found in ldquoFiltering in SPECT Image Reconstructionrdquo [11]
241 Ramp Filter The Ramp filter is the most widely usedhigh pass filter as it does not permit low frequencies thatcause blurring to appear in the image In frequency domainits mathematical function is given by
where 119896119909 119896119910are the spatial frequencies
The Ramp is a compensatory filter as it eliminates the starartifact resulting from simple back projection Because theblurring only appears in the transaxial plane the filter is onlyapplied in that plane [12] The filter is linearly proportionalto the spatial frequency As a high pass filter the Rampfilter has the severe disadvantage of amplifying the statisticalnoise present in the measured counts In order to reduce theamplification of high frequencies the Ramp filter is alwayscombined with a low pass filter
242 Butterworth Filter Butterworth filter is the filtermostlyused in nuclear medicineThe Butterworth filter is a low pass
Figure 1 The effect of varying cutoff frequencies of Butterworthfilter of order 5 (power factor = 10 for all critical frequencies)with FBP First column shows myocardial slices and second columnshows Butterworth equation curves for various cutoff frequencies(02 03 05 and 08) in cyclescm (minimum value 00 andmaximum value 20)
filter It is characterized by two parameters the critical fre-quency which is the point at which the filter starts its roll-off to zero and the order or power [13] As it is mentionedearlier the order changes the slope of the filter Because ofthis ability to change not only the critical frequency butalso the steepness of the roll-off the Butterworth filter canboth smoothen noise and preserve the image resolutionA Butterworth filter in spatial domain is described by thefollowing equation
119861 (119891) =1
1 + (119891119891119888)2119899 (2)
where 119891 is the spatial frequency domain 119891119888is the critical
frequency and 119899 is the order of the filterFiltration is usually applied to projection images before
reconstruction but effect of filtration is shown on recon-structed transaxial images [6] Because Butterworth filters arelow pass filters their application results in smoother imagesthan with no filtering application
Lower critical frequencies correspond to increasedsmoothing with optimal value depending on specific radi-oisotope and protocol used Power factor of a filter equals (bydefinition) twice its order and all frequencies are expressedin cycles per centimeter rather than cycles per pixel
The selection of the cutoff frequency is important toreduce noise and preserve the image details The effect ofButterworth filter of various cutoff frequencies with order119899 = 5 (power 10) in a myocardial SPECT study reconstructedby filtered back projection (FBP) is shown in Figure 1
243 Hanning Filter The Hanning (or Hann) filter is a rela-tively simple low pass filter which is described by one
4 Cardiology Research and Practice
Figure 2 The effect of varying cutoff frequencies of Hanning filterwith FBP First column shows myocardial slices and second columnshows Hanning equation curves for various cutoff frequencies (0509 12 and 16) in cyclescm (minimum value 00 and maximumvalue 20)
parameter the cutoff frequency [14] The Hanning filter isdefined in the frequency domain as follows
119867(119891) =
05 + 05 cos(120587119891
119891119898
) 0 le10038161003816100381610038161198911003816100381610038161003816 le 119891119898
0 otherwise(3)
where 119891 are the spatial frequencies of the image and 119891119898is
the cutoff frequency The Hanning filter is very effective inreducing image noise because it reaches zero very quicklyHowever it does not preserve edgesThe effect of varying cut-off frequencies for the Hanning filter for FBP reconstructionis shown in Figure 2
244 Parzen Filter The Parzen filter is another example ofa low pass filter and is defined in the frequency domain asfollows [14]
10038161003816100381610038161198911003816100381610038161003816 minus 6
0 (10038161003816100381610038161198911003816100381610038161003816 ge 119891119898)
(4)
where119891 are the spatial frequencies of the image and 119891119898is the
cutoff frequencyThe Parzen filter is the most smoothing filter it not only
eliminates high frequency noise but it also degrades the imageresolution [4]
245 Metz Filter TheMetz filter is a function of modulationtransfer function (MTF) and it is based on the measured
MTF of the gamma camera system The MTF describes howthe system handles or degrades the frequencies The Metzrestoration filter is defined in the frequency domain as follows[19]
119872(119891) = MTF(119891)minus1 [1 minus (1 minusMTF(119891)2)119909
] (5)
where 119891 is the spatial domain and 119909 is a parameter thatcontrols the extent to which the inverse filter is followedbefore the low pass filter rolls off to zero
Equation (5) is the product of the inverse filter (first term)and a low pass filter (second term)
The Metz filter is count-dependent
246 Wiener Filter TheWiener filter is based on the signal-to-noise ratio (SNR) of a specific imageThe one-dimensionalfrequency domain form of the Wiener filter is defined asfollows [20]
119882(119891) = MTFminus1 times MTF2
(MTF2 + 119873119874) (6)
where MTF is the modulation transfer function of theimaging system119873 is the noise power spectrum and119874 is theobject power spectrum As with the Metz filter the Wiener isthe product of the inverse filter (which shows the resolutionrecovery) and the low pass filter (which shows the noisesuppression) In order to apply theWiener filter it is necessaryto know a priori the MTF the power spectrum of the objectand the power spectrum of the noise It has to be noticed thatis impossible to know exactly the MTF or the SNR in anyimage As a result the mathematical models used to optimizeboth Metz and Wiener filters are uncertain [4]
247 Cardiac SPECT Filter Dependence Gamma camerasystems offer a wide choice of filters in cardiac SPECT as wellas in many types of examinations The filter choice dependson several parameters [4 21]
(i) the energy of the isotope the number of counts andthe activity administration
(ii) the statistical noise and the background noise level(iii) the type of the organ being imaged(iv) the kind of information we want to obtain from the
images(v) the collimator that is used
The choice of the filter must ensure the best compromise be-tween the noise reduction and the resolution in the image
3 A Comparison of Various Filters in CardiacSPECT Studies on Phantoms
Myocardial SPECT is a well-established noninvasive tech-nique to detect flow-limiting coronary artery disease dur-ing stress and rest conditions Comparison of the myocar-dial distribution of radiopharmaceutical after stress and at
Cardiology Research and Practice 5
A
B
CD
(a) (b) (c) (d)
Figure 3 (a)TheCarlson phantom showing the individual inserts for resolution and contrast evaluation (b) the phantomassembled showingall inserts including hot and cold regions (c) schematic diagrams of the pairs holes as hot regions and drawn line profiles for evaluation ofhot regions (a)ndash(c) obtained from citation [15] (d) Cardiac insert with solidfillable defect set (Model ECTCARI)
rest provides information on myocardial viability inducibleperfusion abnormalities regional myocardial motion andthickening In cardiac SPECT the most commonly usedradiotracers are thallium-201 (201Tl) and technetium-99m( 99mTc) labeled agents such as sestamibi and tetrafosminAccording to the literature the sensitivity specificity andaccuracy of cardiac SPECT varies from 71 to 98 33 to89 and 72 to 95 respectively [22 23]
The quality of the myocardium SPECT images is degrad-ed by several factors The most important factors affect-ing image quality of myocardial perfusion SPECT are thestatistical fluctuation in photon detection the attenuationof photons through the tissues and the scatter radiation[24] Especially nuclear cardiology images because of theirrelatively low counts statistics (breast attenuation obesitypatients) tend to have greater amount of image noise [25]Image filtering is necessary to compensate these effects andtherefore to improve image quality
In order to test and improve the image quality in SPECTspecially constructed phantoms are used for measurementsAn example of such a phantom is the PETSPECT perfor-mance phantom designed and developed by Carlson andColvin [26] Fluke Biomedical Nuclear Associates (Figure 3)The effect of implementing different filters on the hot regionof Carlson phantom SPECT image was tested in order toevaluate the perceived image quality of the hot region and alsoits detectability as far as filters are concerned The findingsshowed that the more accurate locations of radionuclidedistribution were produced when using the Ram-Lak andShepp-Logan filters with cutoff frequency of 04 [15]
A cardiac insert (Figure 3(d)) may be used with theCarlson phantom to mimic the human heart for myocardialperfusion study The ldquoheartrdquo is approximately 8 cm in diame-ter and has a 15 cm thick hollow ldquowallrdquo which may be filledwith a solution containing 201Tl or 99mTcThe insert is placedwithin the source tank which could be filled with radioactivebackground solution [26] Evaluation of cardiac ECT dataacquisition and reconstruction methods can be performed aswell as a quantitative evaluation of nonuniform attenuationand scatter compensation methods Reconstruction of heartinsert images helps in standardization
Figure 4 The SNMMI 2012 Cardiac SPECT phantom simulatorshowing the myocardium insert manufacturedby Medical DesignsInc (MDI) Figure is obtained from citation [16]
Another three-dimensional simulator was created tomeet the imaging needs of general and cardiac nuclearimaging departments by Medical Designs Inc (MDI) TheSNMMI 2012 cardiac SPECT phantom simulator makespossible for myocardial perfusion studies to be performedand for areas of perfusion abnormality to be quantifiedFindings can then be evaluated as far as their diagnosticand prognostic significance is concerned [16] One can useit to perform both visual and semiquantitative evaluation ofthe images A picture of SNMMI cardiac phantom is shownbelow (Figure 4)
The standardization of image processing confines thefilter types for myocardium SPECT imaging to certain filtersMoreover only specific values of cutoff frequency and orderor power are selected to optimize image processing time andclinical results
Takavar et al [27] studied the determination of theoptimum filter in 99mTc myocardial SPECT using a phantomthat simulates the heart left ventricle Filters such as ParzenHanning Hamming and Butterworth and a combination oftheir characteristic parameters were applied on the phantom
6 Cardiology Research and Practice
images To choose the optimumfilter for quantitative analysiscontrast signal-to-noise ratio (SNR) and defect size criteriawere analyzed In each of these criteria were given a numberfrom 1 to 20 1 for the worst and 20 for the best contrastand SNR while 1 for the largest defect size and 20 for thesmallest For every filter the final criterion resulted from thetotal sum of the marks of the previous parameters The studyshowed that Parzen filter is inappropriate for heart studyThecutoff frequency of 0325Nq and 05Nq gave the best overallresult for Hanning and Hamming filters respectively ForButterworth filter order 11 and cutoff 045Nq gave the bestimage quality and size accuracy
A determination of the appropriate filter for myocardialSPECT was conducted by Salihin and Zakaria [14] Inthis study a cardiac phantom was filled with 40 120583CimL(0148MBqmL) 99mTc solution The filters functions evalu-ated in this study included Butterworth HammingHanningand Parzen filters From these filters 272 combinations offilter parameters were selected and applied to the projectiondata For the determination of the best filter Tanavar etal [27] method was applied [20] The study suggested thatButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter produced thebest accurate size
The same group [28] has investigated the relationshipbetween the optimum cutoff frequency for Butterworth filterand lung-heart ratio in 99mTc myocardial SPECT For thestudy a cardiac phantom was used and the optimum cutofffrequency and order of Butterworth filter were determinedusing Takavar et al method [27] A linear relationshipbetween cutoff frequency and lung-heart ratio had beenfound which shows that the lung-heart ratio of each patientmust be taken into account in order to choose the optimumcutoff frequency for Butterworth filter
Links et al [20] examined the effect of Wiener filterin myocardial perfusion with 201Tl SPECT The study wasdone in 19 dogs and showed that Wiener filter improves thequantization of regional myocardial perfusion defects
In amyocardial perfusion studywith 99mTc sestamibi theinvestigators explore the effect of different filters on the con-trast of the defected location Calculations showed that max-imum contrast between normal and defected myocardiumcould be obtained using the Metz (FWHM 35ndash45 pixelorders of 8ndash95) Wiener (FWHMs 35ndash4) Butterworth (cut-offs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) [29]
4 IR versus FBP in Cardiac SPECT
Iterative reconstruction (IR) algorithms allow accurate mod-elling of statistical fluctuation (noise) produce accurateimages without streak artifacts as FBP and promise noisesuppression and improved resolution [30]
Themost commonly used IRmethod in SPECT studies isordered-subset expectation maximization (OSEM) Myocar-dial perfusion SPECT images reconstructed with OSEMIR algorithm have a superior quality than those processedwith FBP Perfusion defects anatomic variants and the right
(a) (b)
Figure 5 Comparison of vertical horizontal and short axis slicesof a stress perfusion imaging study reconstructed by FBP (a) and byOSEM (b) algorithm using the Butterworth filter (cutoff frequency03 cmminus1 and power 10) as a processing filter Data acquired byGE Starcam 4000 and reconstructed in Radiation Physics UnitUniversity Aretaieion Hospital Athens Greece 2013
ventricular myocardium are better visualized with OSEMLikewise image contrast is improved thereby better definingthe left ventricular endocardial borders The effect of OSEMon image quality improvement is more intense in lower countdensity studies [31]
Hatton et al [32] in myocardial perfusion SPECT studyshow that OSEM technique demonstrates fewer artifacts andimproves tolerance when projections are missing HoweverOSEM seems to be less tolerant in motion artifacts thanFBP [33] Won et al [34] in 2008 studied the impact of IRon myocardial perfusion imaging in 6 patients The resultsdemonstrate that there was no statistically significant differ-ence in the accuracy of myocardial perfusion interpretationbetween FBP and IR but there were statistically significantdifferences in functional results
A stress perfusion imaging study reconstructed bothby FBP and by OSEM algorithm using the Butterworthfilter is shown in Figure 5 It is believed that in such a casediagnostic information might be easier to obtain throughthe OSEM algorithm This is because corrections for imagedegrading effects such as attenuation scatter and resolutiondegradation as well as corrections for partial volume effectsand missing data are quite straightforward to be included inthe resulting image through iterative techniques [35]
5 Reconstruction and Processing of3D Cardiac SPECT Images
The 3-dimensional (3D) description of an organ and theinformation of an organrsquos surface can be obtained from asequence of 2D slices reconstructed from projections to forma volume image Volume visualization obtains volumetricsigns useful in diagnosis in a more familiar and realistic way
Cardiology Research and Practice 7
Filtering thresholding and gradient are necessary tools inthe production of diagnostic 3D images [36]
Cardiac SPECT provides information with respect to thedetection of myocardial perfusion defects the assessment ofthe pattern of defect reversibility and the overall detectionof coronary artery disease (CAD) There is a relationshipbetween the location and the degree of the stenosis in coro-nary arteries and the observed perfusion on the myocardialscintigraphy using data of 3D surface images ofmyocardiumThis allows us to predict the impact of evolution of thesestenoses to justify a coronarography or to avoid it
51 3-Dimensional Software Filter Application Seret andForthomme [37] have studied types of commercial softwarefor SPECT image processing It was also observed that therewere 2 definitions of the Butterworth filter For a fixed orderand a fixed cutoff frequency one definition led to a lesssmoothing filter which resulted in higher noise levels andsmaller FWHMs However differences in the FWHM weretranslated to differences in contrast only when they exceeded05 mm for the hot rods and 1 mm for the cold rods ofthe used phantom When considering the FWHM and noiselevel more noticeable differences between the workstationswere observed for OSEM reconstruction
All of the software types used in the study [37] behaved asexpected lowering the filter cutoff frequency in FBP resultedin larger FWHMs and in lower noise levels and reducedcontrast increasing the product number of subsets times thenumber of iterations in OSEM resulted in improved contrastand higher noise levels
Nowadays in many cases myocardium diagnosis is reliedon 3D surface shaded images 3D data obtained at stress andat rest of the LV myocardium respectively are analysed andthe deformation of both images is evaluated qualitatively andquantitatively
3D data reconstructed by IR were obtained by the GEVolumetrix software in the GE Xeleris processing systemat stress and rest MPI studies (Figure 6) Butterworth Filter(cutoff frequency 04 cmminus1 power 10) was used in bothreconstructions Chang attenuation correction was applied(coefficient = 01) These data were then used to evaluate theleft ventricle deformation in both stress and rest 3D surfaceimage series If a significant difference is obtained in rest andstress 3D data perfusion the location and the impact of thepathology of left ventricle myocardium are recognized
3D shaded surface display of a patient stress and rest per-fusion angular images (Figure 7) can be reconstructed by FBPor OSEM algorithm and improved usually by Butterworthor Hanning filter 3D reconstruction in studies by Tc99mtetrofosmin may show normal (or abnormal) myocardiumperfusion in apex base andwalls ofmyocardium Transaxialslices are used to be reconstructed and the created 3D volumeimages are displayedThrough base we recognize the cavity ofLV
52 3-Dimensional Reconstruction byMatLab Filters Applica-tion 3D reconstruction was also performed using a specified
(a)
(b)
Figure 6 3D reconstruction at stress (a) and rest (b) by OSEMiterative reconstruction (10 subsets) Butterworth filter (cutoff04Hz power 10 Chang AC coefficient 01) obtained by the GEVolumetrix software (GE Xeleris-2 processing system) The colourscale indicates a high perfusion in white and red regions and a lowerperfusion in the other regions Defected areas are seen on the aboveimage with a darker colour A perfusion recovery of the defects onthe rest images is observed Data acquired by GE Starcam 4000and reconstructed in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
(a)
(b)
Figure 7 Stress (a) and at rest (b) 3D surface angular images offemale myocardium Small defect at posterior-basal wall at stress isimproved almost completely at rest (2 rest defect) threshold value50 of maximum OSEM iterative reconstruction Defect lesionunder stress is recovered in rest condition (seen on the first structurein both above and below image)
MatLab code in order to evaluate the different filters used(Figure 10) and also to compare myocardium volume at restand at stress (Figure 11) In MatLab volume visualizationcan be achieved by constructing a 3D surface plot whichuses the pixel identities for (119909 119910) axes and the pixel valueis transformed into surface plot height and consequentlycolour Apart from that 3D voxel images can be constructedSPECT projections are acquired isocontours are depicted onthem including a number of voxels and finally all of them canbe added in order to create the desirable volume image [17]
8 Cardiology Research and Practice
40
35
30
25
20
15
25 30 35 40 45 50
(a)
34
32
30
28
26
24
22
20
36 38 40 42 44 46 48 50
(b)
Figure 8 Isocontour surfaces for threshold value determination in rest [17] Images obtained in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
40
35
30
25
20
15
30 35 40 45 50 55
(a)
34
32
30
28
26
24
22
20
34 36 38 40 42 44 46 48
(b)
Figure 9 Isocontour surfaces for threshold value determination in stress [17] Images obtained in Radiation Physics Unit UniversityAretaieio hospital Athens Greece 2013
Themethod is illustrated in Figures 8 and 9 for rest and stressconditions respectively
The volume rendered by MatLab is slow enough but sim-ilar to other codesrsquo volume renderings
The volume rendering used in 3D myocardium usedzoom angles of 56 degrees and a focal length in pixels de-pending on the organsrsquo sizeThe size of the reprojection is thesame as the main size of input image
6 4D Gated SPECT Imaging
In some cases SPECT imaging can be gated to the cardiacelectrocardiogram signal allowing data from specific parts ofthe cardiac cycle to be isolated and providing a spatiotem-poral approach (4D) It also allows a combined evaluation ofboth myocardial perfusion and left ventricular (LV) functionin one study which can provide additional information thatperfusion imaging cannot provide alone An example of sucha case are patients suffering from a 3-vessel coronary diseasewhere gated SPECThas been noted to yield significantlymoreabnormal segments than perfusion does alone [38]
As in a regular SPECT acquisition a 120574-camera registersphotons emitted from the object atmultiple projection anglesalong an arc of usually 180 degrees At each projection insteadof one static image several dynamic images are acquired
spanning the length of the cardiac cycle at equal intervalsThe cardiac cycle is marked within the R-R interval whichcorresponds to the end-diastole and is divided in 8-16 equalframes For each frame image data are acquired overmultiplecardiac cycles and stored All data for a specific frame are thenadded together to form an image representing a specific phaseof the cardiac cycle If temporal frames are added togetherthe resulting set of images is equivalent to a standard set ofungated perfusion images
During reconstruction in gated SPECT a significant levelof smoothing is required in comparison to ungated orsummedprojection data because of the relatively poor counts[39] This is done by using appropriate filters Several studieshave been made to establish the most appropriate filters forthis purpose
In a 201Tl gated SPECT study concerning patients withmajor myocardial infarction [40] a Butterworth filter oforder 5 with six cutoff frequencies (013 015 020 025030 and 035 cyclepixel) was successively testedThe reportshowed that filtering affects end diastolic volume (EDV) endsystolic volume (ESV) and left ventricular ejection fraction(LVEF) Marie et al [41] suggested that the best results forcardiac gated SPECT image reconstruction with 201Tl wereachieved using a Butterworth filter with an order of 5 andcutoff frequency 030 cyclespixel
Cardiology Research and Practice 9
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(a)
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(b)
Figure 10 3D volume of a normal myocardium reconstruction is obtained through a specifiedMatLab code in order to compare the differentfilters used Butterworth (a) and Hann (b) filetrs are used Insignificant voxel differences are observed Data acquired at Medical ImagingNuclear Medicine and MatLab algorithm in Radiation Physics Unit Aretaieion Hospital Athens
16
14
12
10
8
6
48
46
44
42
40
38
28 26 24 22 20 18 16
(a)
48
46
44
42
40
38
12
10
8
6
4
25
20
15
(b)
Figure 11 3Dmyocardium processed by aMatLab code in order to compare myocardium volume at rest (left) and at stress (right) (Lyra et al2010) The image does not depict the real volume but the voxelized one (the functional myocardium) Figure is obtained from citation [18]
In 2005 [42] the differences produced by change ofreconstruction filter in calculations of left-ventricular enddiastolic volume (EDV) end systolic volume (ESV) strokevolume (SV) and ejection fraction (LVEF) from 99mTc-sestamibi myocardial gated SPECT studies have been inves-tigated Butterworth order 4 cutoff frequency 025 cyclespixel and Metz order 8 full-width half maximum 40mmwere applied and compared With the Metz filter ratherthan the Butterworth filter left-ventricular EDV and ESVwere significantly larger and the LVEF and SV were notsignificantly changedThe results were consistent to previoussimilar studies [40 43]
7 Discussion
The SPECT filters can greatly affect the quality of clinicalimages Proper filter selection and adequate smoothing helpsthe physician in resultsrsquo interpretation and accurate diagnosis
Several studies on phantoms with respect to the mostappropriate filter for cardiac SPECT have been consideredThe studies showed that for the 3D SPECT reconstructionButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter producesthe best accurate size [20] Maximum contrast betweennormal and defected myocardium could be obtained using
10 Cardiology Research and Practice
the Metz (FWHM 35ndash45 pixel orders of 8ndash95) Wiener(FWHMs 35ndash4) Butterworth (cutoffs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) filters [29] The cutofffrequency of 0325 of Nq gave the best overall result for theHanning filter whereas for the Butterworth filter order 11and cut off of 045Nq gave the best image quality and sizeaccuracy [27]
For the 4DECG-gated SPECT reconstruction best resultswere obtained using a Butterworth filter with an order of 5and cutoff frequency of 030 cyclespixel [41]
As far as the reconstruction technique is concerned using3D OSEM with suitable AC may improve lesion detectabilitydue to the significant improvement of image contrast [35] 3Diterative reconstruction algorithms are likely to replace theFBP technique for many SPECT clinical applications
When a specified 3D reconstruction MatLab code wasused to compare both two chosen filters (Butterworth andHann) andmyocardium volume at rest and at stress accuratediagnostic images were produced
It is expected that further significant improvement inimage quality will be attained which in turn will increasethe confidence of image interpretation The development ofalgorithms for analysis of myocardial 3D images may allowbetter evaluation of small and nontransmural myocardialdefects For the diagnosis and treatment of heart diseasesthe accurate visualisation of the spatial heart shape 3Dvolume of the LV and the heart wall perfusion plays a crucialrole Surface shading is a valuable tool for determining thepresence extent and location of CAD
Further developments in cardiac diagnosis include anew promising tool computational cardiologyThe functionsof the diseased heart and the probable new techniques indiagnosis and treatment can be studied using state-of-the-art whole-heart models of electrophysiology and electrome-chanics A characteristic example of implementing such amodel is ventricular modelling where important aspects ofarrhythmias including dynamic characteristics of ventricu-lar fibrillation can be revealed Performing patient-specificcomputer simulations of the function of the diseased heart foreither diagnostic or treatment purposes could be an excitingnew implementation of computational cardiology [44]
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
References
[1] WHO Global Atlas on Cardiovascular Disease Prevention andControl WHO World Heart Federation World Stroke Organi-zation 2011 httpwwwwhointcardiovascular diseasesen
[2] S Agarwal M G Shlipak H Kramer A Jain and D MHerrington ldquoThe association of chronic kidney disease andmetabolic syndrome with incident cardiovascular events mul-tiethnic study of atherosclerosisrdquo Cardiology Research andPractice vol 2012 Article ID 806102 8 pages 2012
[3] H Jadvar H W Strauss and G M Segall ldquoSPECT and PET inthe evaluation of coronary artery diseaserdquo Radiographics vol19 no 4 pp 915ndash926 1999
[4] K van Laere M Koole I Lemahieu and R Dierckx ldquoImagefiltering in single-photon emission computed tomography Pri-nciples and applicationsrdquo Computerized Medical Imaging andGraphics vol 25 no 2 pp 127ndash133 2001
[5] E G DePuey D S Berman and E V Garcia Cardiac SPECTImaging Raven Press New York NY USA 1995
[6] G Germano ldquoTechnical aspects of myocardial SPECT imag-ingrdquo Journal of Nuclear Medicine vol 42 no 10 pp 1499ndash15072001
[7] S R Cherry J A Sorenson andM E Phelps Physics in NuclearMedicine Saunders Philadelphia Pa USA 2003
[8] J Qi and R M Leahy ldquoIterative reconstruction techniques inemission computed tomographyrdquo Physics in Medicine and Bi-ology vol 51 pp R541ndashR578 2006
[9] C Lee-Tzuu ldquoA method for attenuation correction in radionu-clide computed tomographyrdquo IEEE Transactions on NuclearScience vol 25 no 1 pp 638ndash643 1978
[10] P P Bruyant ldquoAnalytic and iterative reconstruction algorithmsin SPECTrdquo Journal of NuclearMedicine vol 43 no 10 pp 1343ndash1358 2002
[11] M Lyra and A Ploussi ldquoFiltering in SPECT image reconstruc-tionrdquo International Journal of Biomedical Imaging vol 2011Article ID 693795 14 pages 2011
[12] M W Groch and W D Erwin ldquoSPECT in the year 2000 basicprinciplesrdquo Journal of Nuclear Medicine Technology vol 28 no4 pp 233ndash244 2000
[13] M M Khalil Basic Sciences of Nuclear Medicine Springer Be-rlin Germany 2010
[14] M N Salihin and A Zakaria ldquoDetermination of the optimumfilter for qualitative and quantitative 99mTc myocardial SPECTimagingrdquo Iranian Journal of Radiation Research vol 6 no 4 pp173ndash182 2009
[15] A Sadremomtaz and P Taherparvar ldquoThe influence of filters onthe SPECT image of Carlson phantomrdquo Journal of BiomedicalScience and Engineering vol 6 pp 291ndash297 2013
[16] Society of Nuclear Medicine and Molecular Imaging (2012)Phantoms Cardiac SPECT simulator 2012 httpinteractivesnmorgindexcfmPageID=11666
[17] S SynefiaM SotiropoulosM Argyrou et al ldquo3D SPECTmyo-cardial volume estimation increases the reliability of perfusiondiagnosisrdquo e-Journal of Science and Technology In press
[18] M Lyra M Sotiropoulos N Lagopati and M GavrillelildquoQuantification of myocardial perfusion in 3D SPECT images-stressrest volume differences 3D myocardium images quan-tificationrdquo in Proceedings of the IEEE International Conferenceon Imaging Systems and Techniques (IST rsquo10) pp 31ndash35 Thessa-loniki Greece July 2010
[19] M A King S J Glick B C Penney R B Schwinger and PW Doherty ldquoInteractive visual optimization of SPECT prerec-onstruction filteringrdquo Journal of Nuclear Medicine vol 28 no 7pp 1192ndash1198 1987
[20] J M Links R W Jeremy S M Dyer T L Frank and L CBecker ldquoWiener filtering improves quantification of regionalmyocardial perfusion with thallium-201 SPECTrdquo Journal ofNuclear Medicine vol 31 no 7 pp 1230ndash1236 1990
[21] G V Heller A Mann and R C Hendel Nuclear CardiologyTechnical Applications McGraw-Hill New York NY USA2009
Cardiology Research and Practice 11
[22] B Tasdemir T Balci B Demirel I Karaca A Aydin and ZKoc ldquoComparison of myocardial perfusion scintigraphy andcomputed tomography (CT) angiography based on conven-tional coronary angiographyrdquo Natural Science vol 4 pp 976ndash982 2012
[23] S R Underwood C Anagnostopoulos M Cerqueira et alldquoMyocardial perfusion scintigraphy the evidencerdquo EuropeanJournal of Nuclear Medicine and Molecular Imaging vol 31 no2 pp 261ndash291 2004
[24] Y H Lue and F J Wackers Cardiovascular Imaging MansonPublishing 2010
[25] E G DePuey Imaging Guidelines for Nuclear Cardiology Proce-dures The American Society of Nuclear Cardiology 2006
[26] R A Carlson and J T Colvin ldquoFluke Biomedical Nuclear Asso-ciates 76ndash823 76ndash824 amp 76ndash825 PETSPECT Phantom SourceTank Phantom Inserts and Cardiac Insertrdquo 2006 httpwwwflukebiomedicalcomBiomedicalusenNuclear-MedicineQual-ity-Control-Phantoms76-825htmPID=55292
[27] A Takavar G Shamsipour M Sohrabi and M Eftekhari ldquoDe-termination of optimumfilter inmyocardial SPECT a phantomstudyrdquo Iranian Journal of Radiation Research vol 4 no 1 pp205ndash210 2004
[28] M N Salihin and A Zakaria ldquoRelationship between the opti-mum cut off frequency for Butterworth filter and lung-heartratio in 99mTcmyocardial SPECTrdquo Iranian Journal of RadiationResearch vol 8 no 1 pp 17ndash24 2010
[29] H Rajabi A Rajabi N Yaghoobi H Firouzabady and F Rust-gou ldquoDetermination of the optimum filter function for Tc99m-sestamibi myocardial perfusion SPECT imagingrdquo Indian Jour-nal of Nuclear Medicine vol 20 no 3 pp 77ndash82 2005
[30] S Vandenberghe Y DrsquoAsseler R van de Walle et al ldquoIterativereconstruction algorithms in nuclear medicinerdquo ComputerizedMedical Imaging and Graphics vol 25 no 2 pp 105ndash111 2001
[31] E G DePuey ldquoAdvances in SPECT camera software and hard-ware currently available and new on the horizonrdquo Journal ofNuclear Cardiology vol 19 no 3 pp 551ndash581 2012
[32] R L Hatton B F Hutton S Angelides K K L Choong andG Larcos ldquoImproved tolerance to missing data in myocardialperfusion SPET usingOSEM reconstructionrdquo European Journalof Nuclear Medicine and Molecular Imaging vol 31 no 6 pp857ndash861 2004
[33] S R Zakavi A Zonoozi V D Kakhki M Hajizadeh MMom-ennezhad and K Ariana ldquoImage reconstruction using filteredbackprojection and iterative method effect on motion artifactsin myocardial perfusion SPECTrdquo Journal of Nuclear MedicineTechnology vol 34 no 4 pp 220ndash223 2006
[34] KWon E KimMMar et al ldquoIs iterative reconstruction an im-provement over filtered back projection in processing gatedmyocardial perfusion SPECTrdquo The Open Medical ImagingJournal vol 2 pp 17ndash23 2008
[35] A Otte K Audenaert K Peremans K Heeringen and R Dier-ckx Nuclear Medicine in Psychiatry Springer Berlin Germany2004
[36] M Lyra ldquoSingle photon emission tomography (SPECT) and 3Dimages evaluation in nuclear medicinerdquo in Image ProcessingY S Chen Ed InTech 2009 httpwwwintechopencombooksimage-processingsingle-photon-emission-tomography-spect-and-3d-images-evaluation-in-nuclear-medicine
[37] A Seret and J Forthomme ldquoComparison of different types ofcommercial filtered backprojection and ordered-subset expec-tation maximization SPECT reconstruction softwarerdquo Journalof Nuclear Medicine Technology vol 37 no 3 pp 179ndash187 2009
[38] R S Lima D DWatson A R Goode et al ldquoIncremental valueof combined perfusion and function over perfusion alone bygated SPECT myocardial perfusion imaging for detection ofsevere three-vessel coronary artery diseaserdquo Journal of theAmerican College of Cardiology vol 42 no 1 pp 64ndash70 2003
[39] A K Paul andH A Nabi ldquoGatedmyocardial perfusion SPECTbasic principles technical aspects and clinical applicationsrdquoJournal of Nuclear Medicine Technology vol 32 no 4 pp 179ndash187 2004
[40] P Vera A Manrique V Pontvianne A Hitzel R Koningand A Cribier ldquoThallium-gated SPECT in patients with majormyocardial infarction effect of filtering and zooming in com-parison with equilibrium radionuclide imaging and left ven-triculographyrdquo Journal of Nuclear Medicine vol 40 no 4 pp513ndash521 1999
[41] P Y Marie W Djaballah P R Franken et al ldquoOSEM recon-struction associated with temporal Fourier and depth-dependant resolution recovery filtering enhances results fromsestamibi and 201T1 16-Interval Gated SPECTrdquo Journal ofNuclear Medicine vol 46 no 11 pp 1789ndash1795 2005
[42] T Vakhtangandze D O Hall F V Zananiri and M R ReesldquoThe effect of Butterworth and Metz reconstruction filters onvolume and ejection fraction calculations with 99Tcm gatedmyocardial SPECTrdquoBritish Journal of Radiology vol 78 no 932pp 733ndash736 2005
[43] G A Wright M McDade W Martin and I Hutton ldquoQuan-titative gated SPECT the effect of reconstruction filter oncalculated left ventricular ejection fractions and volumesrdquoPhysics in Medicine and Biology vol 47 no 8 pp 99ndash105 2002
[44] N Trayanova ldquoComputational cardiology the heart of thematterrdquo ISRN Cardiology vol 2012 Article ID 269680 15 pages2012
21 Myocardium Data Acquisition SPECT provides three-dimensional images that facilitate both a visual and a quan-titative evaluation of the cardiac radionuclide distributionand of the surrounding tissues by removing superimposedactivity from surrounding tissues [5]
The administrated radioisotope in the patientrsquos bodyemits single gamma ray photons that are recorded througha gamma camera mounted on a gantry in numerous projec-tions around the patient Both contour and elliptical orbitscan be used The projection acquisition may be performedin three different ways step-and-shoot continuous andcontinuous step-and-shoot The method mostly used is thestep-and-shoot method For a given orbit the camera stopsat predefined angular positions and acquires a projection forpredefined time durations An arc of 180 degrees is usuallycovered that is 45 degrees right anterior oblique to leftposterior oblique (RAO-LPO) [5] Equal times are used toachieve the same count statistics
Another parameter that greatly affects the image quality(sensitivity and resolution) is the choice of the collimatorThis is determined mainly by the tracer activity When 201Tlis being used a low-energy general purpose collimator istraditionally chosen For 99Tc-labeled agents high resolutioncollimators are recommended whereas for 111In and 123ImdashMIBG (metaiodobenzylguanidine) medium energy collima-tors are usually used [5]
Other important parameters that are to be taken intoaccount during acquisition are the projection matrix size thenumber of angles and the time per view For the projectionmatrix a common rule of thumb is that at least three pixelsshould be used to image a structure for each full width athalf maximum (FWHM) of the response profile For thenumber of angles the time per view determines the statisticalcontent of the projected imageThe interrelationship of theseparameters is quite complicated
In most cardiac SPECT protocols a 180∘ camera rotationwith 64 times 64 matrix size is recommended [6] The 2Dprojection-images are first corrected for nonuniformities andthen mathematical algorithms are used to reconstruct 3Dmatrices of selected planes from the 2D projection data
22 Myocardium Image Reconstruction Techniques The pur-pose of reconstruction algorithms is to calculate an accurate3D radioactivity distribution from the acquired projectionsThere are two methods to reconstruct SPECT images eitherby filter back projection (FBP) analytical technique or itera-tively by algebraic methods
221 Filtered Back Projection Method (FBP) Filtered backprojection is an analytical method that is still the most widelyused in clinical SPECT because of its simplicity speed andcomputational efficiency FBP consists of two steps filteringof data and back projection of the filtered data [7]
In 2D acquisition each row of projections represents thesum of all counts along a straight line through the depth
of the object being imaged Back projection technique redis-tributes the number of counts at each particular point backalong a line from which they were originally detected Thisprocess is repeated for all pixels and all angles A limitednumber of projection sets can result in the formation ofthe star artifact and in blurring of the image To eliminatethis problem the projections are filtered before being backprojected onto the image matrix It has to be noticed thatthe back projection process has taken place in spatial domainwhile data filtration is done in the frequency domain Whilethe analytic approaches typically result in fast reconstruc-tion algorithms accuracy of the reconstructed images islimited by the approximations in the line-integral model onwhich the reconstruction formulae are based [8] CardiacSPECT reconstruction process may obtain attenuation cor-rections approximately using a postprocessing step [9] Somereconstruction algorithms apply approximation formulas tothe projection data for attenuation correction Lee-Tzuu[9] applied a simple effective two-step procedure to theuncorrected image For two-dimensional (2D) SPECT withparallel or fan beam collimators 2D filtered back projection(FBP) algorithms are routinely used for myocardium SPECTreconstruction
222 Iterative Reconstruction Method Iterative reconstruc-tion starts with an initial estimate of the image [7] Most ofthe times the initial estimate is very simple for example auniform activity distribution Then a set of projection data isestimated from the initial estimate using a mathematical pro-cess called forward projection The resulting projections arecompared with the recorded projections and the differencesbetween the two are used to update the estimated image Theiterative process is repeated until the differences between thecalculated and measured data are smaller than a specifiedpreselected value
Data from SPECT systems using parallel fan beam andcone beam collimators can be modelled as sets of line inte-grals of the tracer density along the collimation directionsConsequently SPECT images can be reconstructed usinganalytic inversion methods that are based on the relationshipbetween a function and its line integrals
For 3D SPECT the iterative reconstruction methodsinclude algebraic methods like the algebraic reconstructiontechnique (ART) and statistical algorithms like maximumlikelihood expectation maximization (ML-EM) or orderedsubsets expectation maximization (OS-EM) [10] The ML-EM algorithm is a general approach to solving maximumlikelihood problems through the introduction of a set of datawhich if observed would make the ML problem readilysolvable The algorithm then iterates between computing themean of the complete data given the observed data and thecurrent estimate of the image andmaximizing the probabilityof the complete data over the image space In the orderedsubsets EM (OS-EM) method the full set of views is dividedinto subsets and the EM algorithm applied sequentially toeach of these data sets in turn This produces remarkableimprovements in the initial convergence rate compared toML-EM [8]
Cardiology Research and Practice 3
23 Image Processing in 3D and 4D Cardiac SPECT Afterthe planar images have been obtained for several projectionangles a 3D reconstruction can be performed using differentmethods and the appropriate filters The first method is byusing a type of commercially available software for SPECTimaging Such software with different filters is discussed inSection 51 Another method is by using a specified program-ming code Such a MatLab code is tested in Section 52again for multiple filters When a spatiotemporal approachis of need electrocardiogram- (ECG-) gated SPECT can beperformed In ECG-gated SPECT data from specific partsof the cardiac cycle can be isolated This method is furtherexplained in Section 6
24 Image Filtering in Cardiac SPECT Different filter typesin SPECT imaging can produce different optimal resultsin processed images such as star artifact reduction noisesuppression or signal enhancement and restoration [4] Thechoice of filter for a given image processing task is generally acompromise between the extent of noise reduction fine detailsuppression and contrast enhancement as well as the spatialfrequency pattern of the image data of interest
Filters that are commonly used on SPECT imaging arethe Ramp filter a high pass filter eliminating the star artifactand blurring the Hanning filter a low pass smoothing filterthe Hamming filter also a low pass smoothing filter having adifferent amplitude at the cutoff frequency the Butterworthfilter which both smoothers noise and preserves the imageresolution the Parzen filter the most smoothing low passfilter and the Shepp-Logan filter which is the least smoothingbut has the highest resolution [4] Two enhancement filtersalso used in cardiac SPECT are the Metz filter a function ofmodulation transfer function and the Wiener filter which isbased on the signal-to-noise ratio of the specific image
The filters mostly used in cardiac SPECT imaging arepresented with a greater detail in the next paragraphs Amore extensive presentation of all the mentioned filters canbe found in ldquoFiltering in SPECT Image Reconstructionrdquo [11]
241 Ramp Filter The Ramp filter is the most widely usedhigh pass filter as it does not permit low frequencies thatcause blurring to appear in the image In frequency domainits mathematical function is given by
where 119896119909 119896119910are the spatial frequencies
The Ramp is a compensatory filter as it eliminates the starartifact resulting from simple back projection Because theblurring only appears in the transaxial plane the filter is onlyapplied in that plane [12] The filter is linearly proportionalto the spatial frequency As a high pass filter the Rampfilter has the severe disadvantage of amplifying the statisticalnoise present in the measured counts In order to reduce theamplification of high frequencies the Ramp filter is alwayscombined with a low pass filter
242 Butterworth Filter Butterworth filter is the filtermostlyused in nuclear medicineThe Butterworth filter is a low pass
Figure 1 The effect of varying cutoff frequencies of Butterworthfilter of order 5 (power factor = 10 for all critical frequencies)with FBP First column shows myocardial slices and second columnshows Butterworth equation curves for various cutoff frequencies(02 03 05 and 08) in cyclescm (minimum value 00 andmaximum value 20)
filter It is characterized by two parameters the critical fre-quency which is the point at which the filter starts its roll-off to zero and the order or power [13] As it is mentionedearlier the order changes the slope of the filter Because ofthis ability to change not only the critical frequency butalso the steepness of the roll-off the Butterworth filter canboth smoothen noise and preserve the image resolutionA Butterworth filter in spatial domain is described by thefollowing equation
119861 (119891) =1
1 + (119891119891119888)2119899 (2)
where 119891 is the spatial frequency domain 119891119888is the critical
frequency and 119899 is the order of the filterFiltration is usually applied to projection images before
reconstruction but effect of filtration is shown on recon-structed transaxial images [6] Because Butterworth filters arelow pass filters their application results in smoother imagesthan with no filtering application
Lower critical frequencies correspond to increasedsmoothing with optimal value depending on specific radi-oisotope and protocol used Power factor of a filter equals (bydefinition) twice its order and all frequencies are expressedin cycles per centimeter rather than cycles per pixel
The selection of the cutoff frequency is important toreduce noise and preserve the image details The effect ofButterworth filter of various cutoff frequencies with order119899 = 5 (power 10) in a myocardial SPECT study reconstructedby filtered back projection (FBP) is shown in Figure 1
243 Hanning Filter The Hanning (or Hann) filter is a rela-tively simple low pass filter which is described by one
4 Cardiology Research and Practice
Figure 2 The effect of varying cutoff frequencies of Hanning filterwith FBP First column shows myocardial slices and second columnshows Hanning equation curves for various cutoff frequencies (0509 12 and 16) in cyclescm (minimum value 00 and maximumvalue 20)
parameter the cutoff frequency [14] The Hanning filter isdefined in the frequency domain as follows
119867(119891) =
05 + 05 cos(120587119891
119891119898
) 0 le10038161003816100381610038161198911003816100381610038161003816 le 119891119898
0 otherwise(3)
where 119891 are the spatial frequencies of the image and 119891119898is
the cutoff frequency The Hanning filter is very effective inreducing image noise because it reaches zero very quicklyHowever it does not preserve edgesThe effect of varying cut-off frequencies for the Hanning filter for FBP reconstructionis shown in Figure 2
244 Parzen Filter The Parzen filter is another example ofa low pass filter and is defined in the frequency domain asfollows [14]
10038161003816100381610038161198911003816100381610038161003816 minus 6
0 (10038161003816100381610038161198911003816100381610038161003816 ge 119891119898)
(4)
where119891 are the spatial frequencies of the image and 119891119898is the
cutoff frequencyThe Parzen filter is the most smoothing filter it not only
eliminates high frequency noise but it also degrades the imageresolution [4]
245 Metz Filter TheMetz filter is a function of modulationtransfer function (MTF) and it is based on the measured
MTF of the gamma camera system The MTF describes howthe system handles or degrades the frequencies The Metzrestoration filter is defined in the frequency domain as follows[19]
119872(119891) = MTF(119891)minus1 [1 minus (1 minusMTF(119891)2)119909
] (5)
where 119891 is the spatial domain and 119909 is a parameter thatcontrols the extent to which the inverse filter is followedbefore the low pass filter rolls off to zero
Equation (5) is the product of the inverse filter (first term)and a low pass filter (second term)
The Metz filter is count-dependent
246 Wiener Filter TheWiener filter is based on the signal-to-noise ratio (SNR) of a specific imageThe one-dimensionalfrequency domain form of the Wiener filter is defined asfollows [20]
119882(119891) = MTFminus1 times MTF2
(MTF2 + 119873119874) (6)
where MTF is the modulation transfer function of theimaging system119873 is the noise power spectrum and119874 is theobject power spectrum As with the Metz filter the Wiener isthe product of the inverse filter (which shows the resolutionrecovery) and the low pass filter (which shows the noisesuppression) In order to apply theWiener filter it is necessaryto know a priori the MTF the power spectrum of the objectand the power spectrum of the noise It has to be noticed thatis impossible to know exactly the MTF or the SNR in anyimage As a result the mathematical models used to optimizeboth Metz and Wiener filters are uncertain [4]
247 Cardiac SPECT Filter Dependence Gamma camerasystems offer a wide choice of filters in cardiac SPECT as wellas in many types of examinations The filter choice dependson several parameters [4 21]
(i) the energy of the isotope the number of counts andthe activity administration
(ii) the statistical noise and the background noise level(iii) the type of the organ being imaged(iv) the kind of information we want to obtain from the
images(v) the collimator that is used
The choice of the filter must ensure the best compromise be-tween the noise reduction and the resolution in the image
3 A Comparison of Various Filters in CardiacSPECT Studies on Phantoms
Myocardial SPECT is a well-established noninvasive tech-nique to detect flow-limiting coronary artery disease dur-ing stress and rest conditions Comparison of the myocar-dial distribution of radiopharmaceutical after stress and at
Cardiology Research and Practice 5
A
B
CD
(a) (b) (c) (d)
Figure 3 (a)TheCarlson phantom showing the individual inserts for resolution and contrast evaluation (b) the phantomassembled showingall inserts including hot and cold regions (c) schematic diagrams of the pairs holes as hot regions and drawn line profiles for evaluation ofhot regions (a)ndash(c) obtained from citation [15] (d) Cardiac insert with solidfillable defect set (Model ECTCARI)
rest provides information on myocardial viability inducibleperfusion abnormalities regional myocardial motion andthickening In cardiac SPECT the most commonly usedradiotracers are thallium-201 (201Tl) and technetium-99m( 99mTc) labeled agents such as sestamibi and tetrafosminAccording to the literature the sensitivity specificity andaccuracy of cardiac SPECT varies from 71 to 98 33 to89 and 72 to 95 respectively [22 23]
The quality of the myocardium SPECT images is degrad-ed by several factors The most important factors affect-ing image quality of myocardial perfusion SPECT are thestatistical fluctuation in photon detection the attenuationof photons through the tissues and the scatter radiation[24] Especially nuclear cardiology images because of theirrelatively low counts statistics (breast attenuation obesitypatients) tend to have greater amount of image noise [25]Image filtering is necessary to compensate these effects andtherefore to improve image quality
In order to test and improve the image quality in SPECTspecially constructed phantoms are used for measurementsAn example of such a phantom is the PETSPECT perfor-mance phantom designed and developed by Carlson andColvin [26] Fluke Biomedical Nuclear Associates (Figure 3)The effect of implementing different filters on the hot regionof Carlson phantom SPECT image was tested in order toevaluate the perceived image quality of the hot region and alsoits detectability as far as filters are concerned The findingsshowed that the more accurate locations of radionuclidedistribution were produced when using the Ram-Lak andShepp-Logan filters with cutoff frequency of 04 [15]
A cardiac insert (Figure 3(d)) may be used with theCarlson phantom to mimic the human heart for myocardialperfusion study The ldquoheartrdquo is approximately 8 cm in diame-ter and has a 15 cm thick hollow ldquowallrdquo which may be filledwith a solution containing 201Tl or 99mTcThe insert is placedwithin the source tank which could be filled with radioactivebackground solution [26] Evaluation of cardiac ECT dataacquisition and reconstruction methods can be performed aswell as a quantitative evaluation of nonuniform attenuationand scatter compensation methods Reconstruction of heartinsert images helps in standardization
Figure 4 The SNMMI 2012 Cardiac SPECT phantom simulatorshowing the myocardium insert manufacturedby Medical DesignsInc (MDI) Figure is obtained from citation [16]
Another three-dimensional simulator was created tomeet the imaging needs of general and cardiac nuclearimaging departments by Medical Designs Inc (MDI) TheSNMMI 2012 cardiac SPECT phantom simulator makespossible for myocardial perfusion studies to be performedand for areas of perfusion abnormality to be quantifiedFindings can then be evaluated as far as their diagnosticand prognostic significance is concerned [16] One can useit to perform both visual and semiquantitative evaluation ofthe images A picture of SNMMI cardiac phantom is shownbelow (Figure 4)
The standardization of image processing confines thefilter types for myocardium SPECT imaging to certain filtersMoreover only specific values of cutoff frequency and orderor power are selected to optimize image processing time andclinical results
Takavar et al [27] studied the determination of theoptimum filter in 99mTc myocardial SPECT using a phantomthat simulates the heart left ventricle Filters such as ParzenHanning Hamming and Butterworth and a combination oftheir characteristic parameters were applied on the phantom
6 Cardiology Research and Practice
images To choose the optimumfilter for quantitative analysiscontrast signal-to-noise ratio (SNR) and defect size criteriawere analyzed In each of these criteria were given a numberfrom 1 to 20 1 for the worst and 20 for the best contrastand SNR while 1 for the largest defect size and 20 for thesmallest For every filter the final criterion resulted from thetotal sum of the marks of the previous parameters The studyshowed that Parzen filter is inappropriate for heart studyThecutoff frequency of 0325Nq and 05Nq gave the best overallresult for Hanning and Hamming filters respectively ForButterworth filter order 11 and cutoff 045Nq gave the bestimage quality and size accuracy
A determination of the appropriate filter for myocardialSPECT was conducted by Salihin and Zakaria [14] Inthis study a cardiac phantom was filled with 40 120583CimL(0148MBqmL) 99mTc solution The filters functions evalu-ated in this study included Butterworth HammingHanningand Parzen filters From these filters 272 combinations offilter parameters were selected and applied to the projectiondata For the determination of the best filter Tanavar etal [27] method was applied [20] The study suggested thatButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter produced thebest accurate size
The same group [28] has investigated the relationshipbetween the optimum cutoff frequency for Butterworth filterand lung-heart ratio in 99mTc myocardial SPECT For thestudy a cardiac phantom was used and the optimum cutofffrequency and order of Butterworth filter were determinedusing Takavar et al method [27] A linear relationshipbetween cutoff frequency and lung-heart ratio had beenfound which shows that the lung-heart ratio of each patientmust be taken into account in order to choose the optimumcutoff frequency for Butterworth filter
Links et al [20] examined the effect of Wiener filterin myocardial perfusion with 201Tl SPECT The study wasdone in 19 dogs and showed that Wiener filter improves thequantization of regional myocardial perfusion defects
In amyocardial perfusion studywith 99mTc sestamibi theinvestigators explore the effect of different filters on the con-trast of the defected location Calculations showed that max-imum contrast between normal and defected myocardiumcould be obtained using the Metz (FWHM 35ndash45 pixelorders of 8ndash95) Wiener (FWHMs 35ndash4) Butterworth (cut-offs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) [29]
4 IR versus FBP in Cardiac SPECT
Iterative reconstruction (IR) algorithms allow accurate mod-elling of statistical fluctuation (noise) produce accurateimages without streak artifacts as FBP and promise noisesuppression and improved resolution [30]
Themost commonly used IRmethod in SPECT studies isordered-subset expectation maximization (OSEM) Myocar-dial perfusion SPECT images reconstructed with OSEMIR algorithm have a superior quality than those processedwith FBP Perfusion defects anatomic variants and the right
(a) (b)
Figure 5 Comparison of vertical horizontal and short axis slicesof a stress perfusion imaging study reconstructed by FBP (a) and byOSEM (b) algorithm using the Butterworth filter (cutoff frequency03 cmminus1 and power 10) as a processing filter Data acquired byGE Starcam 4000 and reconstructed in Radiation Physics UnitUniversity Aretaieion Hospital Athens Greece 2013
ventricular myocardium are better visualized with OSEMLikewise image contrast is improved thereby better definingthe left ventricular endocardial borders The effect of OSEMon image quality improvement is more intense in lower countdensity studies [31]
Hatton et al [32] in myocardial perfusion SPECT studyshow that OSEM technique demonstrates fewer artifacts andimproves tolerance when projections are missing HoweverOSEM seems to be less tolerant in motion artifacts thanFBP [33] Won et al [34] in 2008 studied the impact of IRon myocardial perfusion imaging in 6 patients The resultsdemonstrate that there was no statistically significant differ-ence in the accuracy of myocardial perfusion interpretationbetween FBP and IR but there were statistically significantdifferences in functional results
A stress perfusion imaging study reconstructed bothby FBP and by OSEM algorithm using the Butterworthfilter is shown in Figure 5 It is believed that in such a casediagnostic information might be easier to obtain throughthe OSEM algorithm This is because corrections for imagedegrading effects such as attenuation scatter and resolutiondegradation as well as corrections for partial volume effectsand missing data are quite straightforward to be included inthe resulting image through iterative techniques [35]
5 Reconstruction and Processing of3D Cardiac SPECT Images
The 3-dimensional (3D) description of an organ and theinformation of an organrsquos surface can be obtained from asequence of 2D slices reconstructed from projections to forma volume image Volume visualization obtains volumetricsigns useful in diagnosis in a more familiar and realistic way
Cardiology Research and Practice 7
Filtering thresholding and gradient are necessary tools inthe production of diagnostic 3D images [36]
Cardiac SPECT provides information with respect to thedetection of myocardial perfusion defects the assessment ofthe pattern of defect reversibility and the overall detectionof coronary artery disease (CAD) There is a relationshipbetween the location and the degree of the stenosis in coro-nary arteries and the observed perfusion on the myocardialscintigraphy using data of 3D surface images ofmyocardiumThis allows us to predict the impact of evolution of thesestenoses to justify a coronarography or to avoid it
51 3-Dimensional Software Filter Application Seret andForthomme [37] have studied types of commercial softwarefor SPECT image processing It was also observed that therewere 2 definitions of the Butterworth filter For a fixed orderand a fixed cutoff frequency one definition led to a lesssmoothing filter which resulted in higher noise levels andsmaller FWHMs However differences in the FWHM weretranslated to differences in contrast only when they exceeded05 mm for the hot rods and 1 mm for the cold rods ofthe used phantom When considering the FWHM and noiselevel more noticeable differences between the workstationswere observed for OSEM reconstruction
All of the software types used in the study [37] behaved asexpected lowering the filter cutoff frequency in FBP resultedin larger FWHMs and in lower noise levels and reducedcontrast increasing the product number of subsets times thenumber of iterations in OSEM resulted in improved contrastand higher noise levels
Nowadays in many cases myocardium diagnosis is reliedon 3D surface shaded images 3D data obtained at stress andat rest of the LV myocardium respectively are analysed andthe deformation of both images is evaluated qualitatively andquantitatively
3D data reconstructed by IR were obtained by the GEVolumetrix software in the GE Xeleris processing systemat stress and rest MPI studies (Figure 6) Butterworth Filter(cutoff frequency 04 cmminus1 power 10) was used in bothreconstructions Chang attenuation correction was applied(coefficient = 01) These data were then used to evaluate theleft ventricle deformation in both stress and rest 3D surfaceimage series If a significant difference is obtained in rest andstress 3D data perfusion the location and the impact of thepathology of left ventricle myocardium are recognized
3D shaded surface display of a patient stress and rest per-fusion angular images (Figure 7) can be reconstructed by FBPor OSEM algorithm and improved usually by Butterworthor Hanning filter 3D reconstruction in studies by Tc99mtetrofosmin may show normal (or abnormal) myocardiumperfusion in apex base andwalls ofmyocardium Transaxialslices are used to be reconstructed and the created 3D volumeimages are displayedThrough base we recognize the cavity ofLV
52 3-Dimensional Reconstruction byMatLab Filters Applica-tion 3D reconstruction was also performed using a specified
(a)
(b)
Figure 6 3D reconstruction at stress (a) and rest (b) by OSEMiterative reconstruction (10 subsets) Butterworth filter (cutoff04Hz power 10 Chang AC coefficient 01) obtained by the GEVolumetrix software (GE Xeleris-2 processing system) The colourscale indicates a high perfusion in white and red regions and a lowerperfusion in the other regions Defected areas are seen on the aboveimage with a darker colour A perfusion recovery of the defects onthe rest images is observed Data acquired by GE Starcam 4000and reconstructed in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
(a)
(b)
Figure 7 Stress (a) and at rest (b) 3D surface angular images offemale myocardium Small defect at posterior-basal wall at stress isimproved almost completely at rest (2 rest defect) threshold value50 of maximum OSEM iterative reconstruction Defect lesionunder stress is recovered in rest condition (seen on the first structurein both above and below image)
MatLab code in order to evaluate the different filters used(Figure 10) and also to compare myocardium volume at restand at stress (Figure 11) In MatLab volume visualizationcan be achieved by constructing a 3D surface plot whichuses the pixel identities for (119909 119910) axes and the pixel valueis transformed into surface plot height and consequentlycolour Apart from that 3D voxel images can be constructedSPECT projections are acquired isocontours are depicted onthem including a number of voxels and finally all of them canbe added in order to create the desirable volume image [17]
8 Cardiology Research and Practice
40
35
30
25
20
15
25 30 35 40 45 50
(a)
34
32
30
28
26
24
22
20
36 38 40 42 44 46 48 50
(b)
Figure 8 Isocontour surfaces for threshold value determination in rest [17] Images obtained in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
40
35
30
25
20
15
30 35 40 45 50 55
(a)
34
32
30
28
26
24
22
20
34 36 38 40 42 44 46 48
(b)
Figure 9 Isocontour surfaces for threshold value determination in stress [17] Images obtained in Radiation Physics Unit UniversityAretaieio hospital Athens Greece 2013
Themethod is illustrated in Figures 8 and 9 for rest and stressconditions respectively
The volume rendered by MatLab is slow enough but sim-ilar to other codesrsquo volume renderings
The volume rendering used in 3D myocardium usedzoom angles of 56 degrees and a focal length in pixels de-pending on the organsrsquo sizeThe size of the reprojection is thesame as the main size of input image
6 4D Gated SPECT Imaging
In some cases SPECT imaging can be gated to the cardiacelectrocardiogram signal allowing data from specific parts ofthe cardiac cycle to be isolated and providing a spatiotem-poral approach (4D) It also allows a combined evaluation ofboth myocardial perfusion and left ventricular (LV) functionin one study which can provide additional information thatperfusion imaging cannot provide alone An example of sucha case are patients suffering from a 3-vessel coronary diseasewhere gated SPECThas been noted to yield significantlymoreabnormal segments than perfusion does alone [38]
As in a regular SPECT acquisition a 120574-camera registersphotons emitted from the object atmultiple projection anglesalong an arc of usually 180 degrees At each projection insteadof one static image several dynamic images are acquired
spanning the length of the cardiac cycle at equal intervalsThe cardiac cycle is marked within the R-R interval whichcorresponds to the end-diastole and is divided in 8-16 equalframes For each frame image data are acquired overmultiplecardiac cycles and stored All data for a specific frame are thenadded together to form an image representing a specific phaseof the cardiac cycle If temporal frames are added togetherthe resulting set of images is equivalent to a standard set ofungated perfusion images
During reconstruction in gated SPECT a significant levelof smoothing is required in comparison to ungated orsummedprojection data because of the relatively poor counts[39] This is done by using appropriate filters Several studieshave been made to establish the most appropriate filters forthis purpose
In a 201Tl gated SPECT study concerning patients withmajor myocardial infarction [40] a Butterworth filter oforder 5 with six cutoff frequencies (013 015 020 025030 and 035 cyclepixel) was successively testedThe reportshowed that filtering affects end diastolic volume (EDV) endsystolic volume (ESV) and left ventricular ejection fraction(LVEF) Marie et al [41] suggested that the best results forcardiac gated SPECT image reconstruction with 201Tl wereachieved using a Butterworth filter with an order of 5 andcutoff frequency 030 cyclespixel
Cardiology Research and Practice 9
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(a)
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(b)
Figure 10 3D volume of a normal myocardium reconstruction is obtained through a specifiedMatLab code in order to compare the differentfilters used Butterworth (a) and Hann (b) filetrs are used Insignificant voxel differences are observed Data acquired at Medical ImagingNuclear Medicine and MatLab algorithm in Radiation Physics Unit Aretaieion Hospital Athens
16
14
12
10
8
6
48
46
44
42
40
38
28 26 24 22 20 18 16
(a)
48
46
44
42
40
38
12
10
8
6
4
25
20
15
(b)
Figure 11 3Dmyocardium processed by aMatLab code in order to compare myocardium volume at rest (left) and at stress (right) (Lyra et al2010) The image does not depict the real volume but the voxelized one (the functional myocardium) Figure is obtained from citation [18]
In 2005 [42] the differences produced by change ofreconstruction filter in calculations of left-ventricular enddiastolic volume (EDV) end systolic volume (ESV) strokevolume (SV) and ejection fraction (LVEF) from 99mTc-sestamibi myocardial gated SPECT studies have been inves-tigated Butterworth order 4 cutoff frequency 025 cyclespixel and Metz order 8 full-width half maximum 40mmwere applied and compared With the Metz filter ratherthan the Butterworth filter left-ventricular EDV and ESVwere significantly larger and the LVEF and SV were notsignificantly changedThe results were consistent to previoussimilar studies [40 43]
7 Discussion
The SPECT filters can greatly affect the quality of clinicalimages Proper filter selection and adequate smoothing helpsthe physician in resultsrsquo interpretation and accurate diagnosis
Several studies on phantoms with respect to the mostappropriate filter for cardiac SPECT have been consideredThe studies showed that for the 3D SPECT reconstructionButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter producesthe best accurate size [20] Maximum contrast betweennormal and defected myocardium could be obtained using
10 Cardiology Research and Practice
the Metz (FWHM 35ndash45 pixel orders of 8ndash95) Wiener(FWHMs 35ndash4) Butterworth (cutoffs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) filters [29] The cutofffrequency of 0325 of Nq gave the best overall result for theHanning filter whereas for the Butterworth filter order 11and cut off of 045Nq gave the best image quality and sizeaccuracy [27]
For the 4DECG-gated SPECT reconstruction best resultswere obtained using a Butterworth filter with an order of 5and cutoff frequency of 030 cyclespixel [41]
As far as the reconstruction technique is concerned using3D OSEM with suitable AC may improve lesion detectabilitydue to the significant improvement of image contrast [35] 3Diterative reconstruction algorithms are likely to replace theFBP technique for many SPECT clinical applications
When a specified 3D reconstruction MatLab code wasused to compare both two chosen filters (Butterworth andHann) andmyocardium volume at rest and at stress accuratediagnostic images were produced
It is expected that further significant improvement inimage quality will be attained which in turn will increasethe confidence of image interpretation The development ofalgorithms for analysis of myocardial 3D images may allowbetter evaluation of small and nontransmural myocardialdefects For the diagnosis and treatment of heart diseasesthe accurate visualisation of the spatial heart shape 3Dvolume of the LV and the heart wall perfusion plays a crucialrole Surface shading is a valuable tool for determining thepresence extent and location of CAD
Further developments in cardiac diagnosis include anew promising tool computational cardiologyThe functionsof the diseased heart and the probable new techniques indiagnosis and treatment can be studied using state-of-the-art whole-heart models of electrophysiology and electrome-chanics A characteristic example of implementing such amodel is ventricular modelling where important aspects ofarrhythmias including dynamic characteristics of ventricu-lar fibrillation can be revealed Performing patient-specificcomputer simulations of the function of the diseased heart foreither diagnostic or treatment purposes could be an excitingnew implementation of computational cardiology [44]
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
References
[1] WHO Global Atlas on Cardiovascular Disease Prevention andControl WHO World Heart Federation World Stroke Organi-zation 2011 httpwwwwhointcardiovascular diseasesen
[2] S Agarwal M G Shlipak H Kramer A Jain and D MHerrington ldquoThe association of chronic kidney disease andmetabolic syndrome with incident cardiovascular events mul-tiethnic study of atherosclerosisrdquo Cardiology Research andPractice vol 2012 Article ID 806102 8 pages 2012
[3] H Jadvar H W Strauss and G M Segall ldquoSPECT and PET inthe evaluation of coronary artery diseaserdquo Radiographics vol19 no 4 pp 915ndash926 1999
[4] K van Laere M Koole I Lemahieu and R Dierckx ldquoImagefiltering in single-photon emission computed tomography Pri-nciples and applicationsrdquo Computerized Medical Imaging andGraphics vol 25 no 2 pp 127ndash133 2001
[5] E G DePuey D S Berman and E V Garcia Cardiac SPECTImaging Raven Press New York NY USA 1995
[6] G Germano ldquoTechnical aspects of myocardial SPECT imag-ingrdquo Journal of Nuclear Medicine vol 42 no 10 pp 1499ndash15072001
[7] S R Cherry J A Sorenson andM E Phelps Physics in NuclearMedicine Saunders Philadelphia Pa USA 2003
[8] J Qi and R M Leahy ldquoIterative reconstruction techniques inemission computed tomographyrdquo Physics in Medicine and Bi-ology vol 51 pp R541ndashR578 2006
[9] C Lee-Tzuu ldquoA method for attenuation correction in radionu-clide computed tomographyrdquo IEEE Transactions on NuclearScience vol 25 no 1 pp 638ndash643 1978
[10] P P Bruyant ldquoAnalytic and iterative reconstruction algorithmsin SPECTrdquo Journal of NuclearMedicine vol 43 no 10 pp 1343ndash1358 2002
[11] M Lyra and A Ploussi ldquoFiltering in SPECT image reconstruc-tionrdquo International Journal of Biomedical Imaging vol 2011Article ID 693795 14 pages 2011
[12] M W Groch and W D Erwin ldquoSPECT in the year 2000 basicprinciplesrdquo Journal of Nuclear Medicine Technology vol 28 no4 pp 233ndash244 2000
[13] M M Khalil Basic Sciences of Nuclear Medicine Springer Be-rlin Germany 2010
[14] M N Salihin and A Zakaria ldquoDetermination of the optimumfilter for qualitative and quantitative 99mTc myocardial SPECTimagingrdquo Iranian Journal of Radiation Research vol 6 no 4 pp173ndash182 2009
[15] A Sadremomtaz and P Taherparvar ldquoThe influence of filters onthe SPECT image of Carlson phantomrdquo Journal of BiomedicalScience and Engineering vol 6 pp 291ndash297 2013
[16] Society of Nuclear Medicine and Molecular Imaging (2012)Phantoms Cardiac SPECT simulator 2012 httpinteractivesnmorgindexcfmPageID=11666
[17] S SynefiaM SotiropoulosM Argyrou et al ldquo3D SPECTmyo-cardial volume estimation increases the reliability of perfusiondiagnosisrdquo e-Journal of Science and Technology In press
[18] M Lyra M Sotiropoulos N Lagopati and M GavrillelildquoQuantification of myocardial perfusion in 3D SPECT images-stressrest volume differences 3D myocardium images quan-tificationrdquo in Proceedings of the IEEE International Conferenceon Imaging Systems and Techniques (IST rsquo10) pp 31ndash35 Thessa-loniki Greece July 2010
[19] M A King S J Glick B C Penney R B Schwinger and PW Doherty ldquoInteractive visual optimization of SPECT prerec-onstruction filteringrdquo Journal of Nuclear Medicine vol 28 no 7pp 1192ndash1198 1987
[20] J M Links R W Jeremy S M Dyer T L Frank and L CBecker ldquoWiener filtering improves quantification of regionalmyocardial perfusion with thallium-201 SPECTrdquo Journal ofNuclear Medicine vol 31 no 7 pp 1230ndash1236 1990
[21] G V Heller A Mann and R C Hendel Nuclear CardiologyTechnical Applications McGraw-Hill New York NY USA2009
Cardiology Research and Practice 11
[22] B Tasdemir T Balci B Demirel I Karaca A Aydin and ZKoc ldquoComparison of myocardial perfusion scintigraphy andcomputed tomography (CT) angiography based on conven-tional coronary angiographyrdquo Natural Science vol 4 pp 976ndash982 2012
[23] S R Underwood C Anagnostopoulos M Cerqueira et alldquoMyocardial perfusion scintigraphy the evidencerdquo EuropeanJournal of Nuclear Medicine and Molecular Imaging vol 31 no2 pp 261ndash291 2004
[24] Y H Lue and F J Wackers Cardiovascular Imaging MansonPublishing 2010
[25] E G DePuey Imaging Guidelines for Nuclear Cardiology Proce-dures The American Society of Nuclear Cardiology 2006
[26] R A Carlson and J T Colvin ldquoFluke Biomedical Nuclear Asso-ciates 76ndash823 76ndash824 amp 76ndash825 PETSPECT Phantom SourceTank Phantom Inserts and Cardiac Insertrdquo 2006 httpwwwflukebiomedicalcomBiomedicalusenNuclear-MedicineQual-ity-Control-Phantoms76-825htmPID=55292
[27] A Takavar G Shamsipour M Sohrabi and M Eftekhari ldquoDe-termination of optimumfilter inmyocardial SPECT a phantomstudyrdquo Iranian Journal of Radiation Research vol 4 no 1 pp205ndash210 2004
[28] M N Salihin and A Zakaria ldquoRelationship between the opti-mum cut off frequency for Butterworth filter and lung-heartratio in 99mTcmyocardial SPECTrdquo Iranian Journal of RadiationResearch vol 8 no 1 pp 17ndash24 2010
[29] H Rajabi A Rajabi N Yaghoobi H Firouzabady and F Rust-gou ldquoDetermination of the optimum filter function for Tc99m-sestamibi myocardial perfusion SPECT imagingrdquo Indian Jour-nal of Nuclear Medicine vol 20 no 3 pp 77ndash82 2005
[30] S Vandenberghe Y DrsquoAsseler R van de Walle et al ldquoIterativereconstruction algorithms in nuclear medicinerdquo ComputerizedMedical Imaging and Graphics vol 25 no 2 pp 105ndash111 2001
[31] E G DePuey ldquoAdvances in SPECT camera software and hard-ware currently available and new on the horizonrdquo Journal ofNuclear Cardiology vol 19 no 3 pp 551ndash581 2012
[32] R L Hatton B F Hutton S Angelides K K L Choong andG Larcos ldquoImproved tolerance to missing data in myocardialperfusion SPET usingOSEM reconstructionrdquo European Journalof Nuclear Medicine and Molecular Imaging vol 31 no 6 pp857ndash861 2004
[33] S R Zakavi A Zonoozi V D Kakhki M Hajizadeh MMom-ennezhad and K Ariana ldquoImage reconstruction using filteredbackprojection and iterative method effect on motion artifactsin myocardial perfusion SPECTrdquo Journal of Nuclear MedicineTechnology vol 34 no 4 pp 220ndash223 2006
[34] KWon E KimMMar et al ldquoIs iterative reconstruction an im-provement over filtered back projection in processing gatedmyocardial perfusion SPECTrdquo The Open Medical ImagingJournal vol 2 pp 17ndash23 2008
[35] A Otte K Audenaert K Peremans K Heeringen and R Dier-ckx Nuclear Medicine in Psychiatry Springer Berlin Germany2004
[36] M Lyra ldquoSingle photon emission tomography (SPECT) and 3Dimages evaluation in nuclear medicinerdquo in Image ProcessingY S Chen Ed InTech 2009 httpwwwintechopencombooksimage-processingsingle-photon-emission-tomography-spect-and-3d-images-evaluation-in-nuclear-medicine
[37] A Seret and J Forthomme ldquoComparison of different types ofcommercial filtered backprojection and ordered-subset expec-tation maximization SPECT reconstruction softwarerdquo Journalof Nuclear Medicine Technology vol 37 no 3 pp 179ndash187 2009
[38] R S Lima D DWatson A R Goode et al ldquoIncremental valueof combined perfusion and function over perfusion alone bygated SPECT myocardial perfusion imaging for detection ofsevere three-vessel coronary artery diseaserdquo Journal of theAmerican College of Cardiology vol 42 no 1 pp 64ndash70 2003
[39] A K Paul andH A Nabi ldquoGatedmyocardial perfusion SPECTbasic principles technical aspects and clinical applicationsrdquoJournal of Nuclear Medicine Technology vol 32 no 4 pp 179ndash187 2004
[40] P Vera A Manrique V Pontvianne A Hitzel R Koningand A Cribier ldquoThallium-gated SPECT in patients with majormyocardial infarction effect of filtering and zooming in com-parison with equilibrium radionuclide imaging and left ven-triculographyrdquo Journal of Nuclear Medicine vol 40 no 4 pp513ndash521 1999
[41] P Y Marie W Djaballah P R Franken et al ldquoOSEM recon-struction associated with temporal Fourier and depth-dependant resolution recovery filtering enhances results fromsestamibi and 201T1 16-Interval Gated SPECTrdquo Journal ofNuclear Medicine vol 46 no 11 pp 1789ndash1795 2005
[42] T Vakhtangandze D O Hall F V Zananiri and M R ReesldquoThe effect of Butterworth and Metz reconstruction filters onvolume and ejection fraction calculations with 99Tcm gatedmyocardial SPECTrdquoBritish Journal of Radiology vol 78 no 932pp 733ndash736 2005
[43] G A Wright M McDade W Martin and I Hutton ldquoQuan-titative gated SPECT the effect of reconstruction filter oncalculated left ventricular ejection fractions and volumesrdquoPhysics in Medicine and Biology vol 47 no 8 pp 99ndash105 2002
[44] N Trayanova ldquoComputational cardiology the heart of thematterrdquo ISRN Cardiology vol 2012 Article ID 269680 15 pages2012
23 Image Processing in 3D and 4D Cardiac SPECT Afterthe planar images have been obtained for several projectionangles a 3D reconstruction can be performed using differentmethods and the appropriate filters The first method is byusing a type of commercially available software for SPECTimaging Such software with different filters is discussed inSection 51 Another method is by using a specified program-ming code Such a MatLab code is tested in Section 52again for multiple filters When a spatiotemporal approachis of need electrocardiogram- (ECG-) gated SPECT can beperformed In ECG-gated SPECT data from specific partsof the cardiac cycle can be isolated This method is furtherexplained in Section 6
24 Image Filtering in Cardiac SPECT Different filter typesin SPECT imaging can produce different optimal resultsin processed images such as star artifact reduction noisesuppression or signal enhancement and restoration [4] Thechoice of filter for a given image processing task is generally acompromise between the extent of noise reduction fine detailsuppression and contrast enhancement as well as the spatialfrequency pattern of the image data of interest
Filters that are commonly used on SPECT imaging arethe Ramp filter a high pass filter eliminating the star artifactand blurring the Hanning filter a low pass smoothing filterthe Hamming filter also a low pass smoothing filter having adifferent amplitude at the cutoff frequency the Butterworthfilter which both smoothers noise and preserves the imageresolution the Parzen filter the most smoothing low passfilter and the Shepp-Logan filter which is the least smoothingbut has the highest resolution [4] Two enhancement filtersalso used in cardiac SPECT are the Metz filter a function ofmodulation transfer function and the Wiener filter which isbased on the signal-to-noise ratio of the specific image
The filters mostly used in cardiac SPECT imaging arepresented with a greater detail in the next paragraphs Amore extensive presentation of all the mentioned filters canbe found in ldquoFiltering in SPECT Image Reconstructionrdquo [11]
241 Ramp Filter The Ramp filter is the most widely usedhigh pass filter as it does not permit low frequencies thatcause blurring to appear in the image In frequency domainits mathematical function is given by
where 119896119909 119896119910are the spatial frequencies
The Ramp is a compensatory filter as it eliminates the starartifact resulting from simple back projection Because theblurring only appears in the transaxial plane the filter is onlyapplied in that plane [12] The filter is linearly proportionalto the spatial frequency As a high pass filter the Rampfilter has the severe disadvantage of amplifying the statisticalnoise present in the measured counts In order to reduce theamplification of high frequencies the Ramp filter is alwayscombined with a low pass filter
242 Butterworth Filter Butterworth filter is the filtermostlyused in nuclear medicineThe Butterworth filter is a low pass
Figure 1 The effect of varying cutoff frequencies of Butterworthfilter of order 5 (power factor = 10 for all critical frequencies)with FBP First column shows myocardial slices and second columnshows Butterworth equation curves for various cutoff frequencies(02 03 05 and 08) in cyclescm (minimum value 00 andmaximum value 20)
filter It is characterized by two parameters the critical fre-quency which is the point at which the filter starts its roll-off to zero and the order or power [13] As it is mentionedearlier the order changes the slope of the filter Because ofthis ability to change not only the critical frequency butalso the steepness of the roll-off the Butterworth filter canboth smoothen noise and preserve the image resolutionA Butterworth filter in spatial domain is described by thefollowing equation
119861 (119891) =1
1 + (119891119891119888)2119899 (2)
where 119891 is the spatial frequency domain 119891119888is the critical
frequency and 119899 is the order of the filterFiltration is usually applied to projection images before
reconstruction but effect of filtration is shown on recon-structed transaxial images [6] Because Butterworth filters arelow pass filters their application results in smoother imagesthan with no filtering application
Lower critical frequencies correspond to increasedsmoothing with optimal value depending on specific radi-oisotope and protocol used Power factor of a filter equals (bydefinition) twice its order and all frequencies are expressedin cycles per centimeter rather than cycles per pixel
The selection of the cutoff frequency is important toreduce noise and preserve the image details The effect ofButterworth filter of various cutoff frequencies with order119899 = 5 (power 10) in a myocardial SPECT study reconstructedby filtered back projection (FBP) is shown in Figure 1
243 Hanning Filter The Hanning (or Hann) filter is a rela-tively simple low pass filter which is described by one
4 Cardiology Research and Practice
Figure 2 The effect of varying cutoff frequencies of Hanning filterwith FBP First column shows myocardial slices and second columnshows Hanning equation curves for various cutoff frequencies (0509 12 and 16) in cyclescm (minimum value 00 and maximumvalue 20)
parameter the cutoff frequency [14] The Hanning filter isdefined in the frequency domain as follows
119867(119891) =
05 + 05 cos(120587119891
119891119898
) 0 le10038161003816100381610038161198911003816100381610038161003816 le 119891119898
0 otherwise(3)
where 119891 are the spatial frequencies of the image and 119891119898is
the cutoff frequency The Hanning filter is very effective inreducing image noise because it reaches zero very quicklyHowever it does not preserve edgesThe effect of varying cut-off frequencies for the Hanning filter for FBP reconstructionis shown in Figure 2
244 Parzen Filter The Parzen filter is another example ofa low pass filter and is defined in the frequency domain asfollows [14]
10038161003816100381610038161198911003816100381610038161003816 minus 6
0 (10038161003816100381610038161198911003816100381610038161003816 ge 119891119898)
(4)
where119891 are the spatial frequencies of the image and 119891119898is the
cutoff frequencyThe Parzen filter is the most smoothing filter it not only
eliminates high frequency noise but it also degrades the imageresolution [4]
245 Metz Filter TheMetz filter is a function of modulationtransfer function (MTF) and it is based on the measured
MTF of the gamma camera system The MTF describes howthe system handles or degrades the frequencies The Metzrestoration filter is defined in the frequency domain as follows[19]
119872(119891) = MTF(119891)minus1 [1 minus (1 minusMTF(119891)2)119909
] (5)
where 119891 is the spatial domain and 119909 is a parameter thatcontrols the extent to which the inverse filter is followedbefore the low pass filter rolls off to zero
Equation (5) is the product of the inverse filter (first term)and a low pass filter (second term)
The Metz filter is count-dependent
246 Wiener Filter TheWiener filter is based on the signal-to-noise ratio (SNR) of a specific imageThe one-dimensionalfrequency domain form of the Wiener filter is defined asfollows [20]
119882(119891) = MTFminus1 times MTF2
(MTF2 + 119873119874) (6)
where MTF is the modulation transfer function of theimaging system119873 is the noise power spectrum and119874 is theobject power spectrum As with the Metz filter the Wiener isthe product of the inverse filter (which shows the resolutionrecovery) and the low pass filter (which shows the noisesuppression) In order to apply theWiener filter it is necessaryto know a priori the MTF the power spectrum of the objectand the power spectrum of the noise It has to be noticed thatis impossible to know exactly the MTF or the SNR in anyimage As a result the mathematical models used to optimizeboth Metz and Wiener filters are uncertain [4]
247 Cardiac SPECT Filter Dependence Gamma camerasystems offer a wide choice of filters in cardiac SPECT as wellas in many types of examinations The filter choice dependson several parameters [4 21]
(i) the energy of the isotope the number of counts andthe activity administration
(ii) the statistical noise and the background noise level(iii) the type of the organ being imaged(iv) the kind of information we want to obtain from the
images(v) the collimator that is used
The choice of the filter must ensure the best compromise be-tween the noise reduction and the resolution in the image
3 A Comparison of Various Filters in CardiacSPECT Studies on Phantoms
Myocardial SPECT is a well-established noninvasive tech-nique to detect flow-limiting coronary artery disease dur-ing stress and rest conditions Comparison of the myocar-dial distribution of radiopharmaceutical after stress and at
Cardiology Research and Practice 5
A
B
CD
(a) (b) (c) (d)
Figure 3 (a)TheCarlson phantom showing the individual inserts for resolution and contrast evaluation (b) the phantomassembled showingall inserts including hot and cold regions (c) schematic diagrams of the pairs holes as hot regions and drawn line profiles for evaluation ofhot regions (a)ndash(c) obtained from citation [15] (d) Cardiac insert with solidfillable defect set (Model ECTCARI)
rest provides information on myocardial viability inducibleperfusion abnormalities regional myocardial motion andthickening In cardiac SPECT the most commonly usedradiotracers are thallium-201 (201Tl) and technetium-99m( 99mTc) labeled agents such as sestamibi and tetrafosminAccording to the literature the sensitivity specificity andaccuracy of cardiac SPECT varies from 71 to 98 33 to89 and 72 to 95 respectively [22 23]
The quality of the myocardium SPECT images is degrad-ed by several factors The most important factors affect-ing image quality of myocardial perfusion SPECT are thestatistical fluctuation in photon detection the attenuationof photons through the tissues and the scatter radiation[24] Especially nuclear cardiology images because of theirrelatively low counts statistics (breast attenuation obesitypatients) tend to have greater amount of image noise [25]Image filtering is necessary to compensate these effects andtherefore to improve image quality
In order to test and improve the image quality in SPECTspecially constructed phantoms are used for measurementsAn example of such a phantom is the PETSPECT perfor-mance phantom designed and developed by Carlson andColvin [26] Fluke Biomedical Nuclear Associates (Figure 3)The effect of implementing different filters on the hot regionof Carlson phantom SPECT image was tested in order toevaluate the perceived image quality of the hot region and alsoits detectability as far as filters are concerned The findingsshowed that the more accurate locations of radionuclidedistribution were produced when using the Ram-Lak andShepp-Logan filters with cutoff frequency of 04 [15]
A cardiac insert (Figure 3(d)) may be used with theCarlson phantom to mimic the human heart for myocardialperfusion study The ldquoheartrdquo is approximately 8 cm in diame-ter and has a 15 cm thick hollow ldquowallrdquo which may be filledwith a solution containing 201Tl or 99mTcThe insert is placedwithin the source tank which could be filled with radioactivebackground solution [26] Evaluation of cardiac ECT dataacquisition and reconstruction methods can be performed aswell as a quantitative evaluation of nonuniform attenuationand scatter compensation methods Reconstruction of heartinsert images helps in standardization
Figure 4 The SNMMI 2012 Cardiac SPECT phantom simulatorshowing the myocardium insert manufacturedby Medical DesignsInc (MDI) Figure is obtained from citation [16]
Another three-dimensional simulator was created tomeet the imaging needs of general and cardiac nuclearimaging departments by Medical Designs Inc (MDI) TheSNMMI 2012 cardiac SPECT phantom simulator makespossible for myocardial perfusion studies to be performedand for areas of perfusion abnormality to be quantifiedFindings can then be evaluated as far as their diagnosticand prognostic significance is concerned [16] One can useit to perform both visual and semiquantitative evaluation ofthe images A picture of SNMMI cardiac phantom is shownbelow (Figure 4)
The standardization of image processing confines thefilter types for myocardium SPECT imaging to certain filtersMoreover only specific values of cutoff frequency and orderor power are selected to optimize image processing time andclinical results
Takavar et al [27] studied the determination of theoptimum filter in 99mTc myocardial SPECT using a phantomthat simulates the heart left ventricle Filters such as ParzenHanning Hamming and Butterworth and a combination oftheir characteristic parameters were applied on the phantom
6 Cardiology Research and Practice
images To choose the optimumfilter for quantitative analysiscontrast signal-to-noise ratio (SNR) and defect size criteriawere analyzed In each of these criteria were given a numberfrom 1 to 20 1 for the worst and 20 for the best contrastand SNR while 1 for the largest defect size and 20 for thesmallest For every filter the final criterion resulted from thetotal sum of the marks of the previous parameters The studyshowed that Parzen filter is inappropriate for heart studyThecutoff frequency of 0325Nq and 05Nq gave the best overallresult for Hanning and Hamming filters respectively ForButterworth filter order 11 and cutoff 045Nq gave the bestimage quality and size accuracy
A determination of the appropriate filter for myocardialSPECT was conducted by Salihin and Zakaria [14] Inthis study a cardiac phantom was filled with 40 120583CimL(0148MBqmL) 99mTc solution The filters functions evalu-ated in this study included Butterworth HammingHanningand Parzen filters From these filters 272 combinations offilter parameters were selected and applied to the projectiondata For the determination of the best filter Tanavar etal [27] method was applied [20] The study suggested thatButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter produced thebest accurate size
The same group [28] has investigated the relationshipbetween the optimum cutoff frequency for Butterworth filterand lung-heart ratio in 99mTc myocardial SPECT For thestudy a cardiac phantom was used and the optimum cutofffrequency and order of Butterworth filter were determinedusing Takavar et al method [27] A linear relationshipbetween cutoff frequency and lung-heart ratio had beenfound which shows that the lung-heart ratio of each patientmust be taken into account in order to choose the optimumcutoff frequency for Butterworth filter
Links et al [20] examined the effect of Wiener filterin myocardial perfusion with 201Tl SPECT The study wasdone in 19 dogs and showed that Wiener filter improves thequantization of regional myocardial perfusion defects
In amyocardial perfusion studywith 99mTc sestamibi theinvestigators explore the effect of different filters on the con-trast of the defected location Calculations showed that max-imum contrast between normal and defected myocardiumcould be obtained using the Metz (FWHM 35ndash45 pixelorders of 8ndash95) Wiener (FWHMs 35ndash4) Butterworth (cut-offs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) [29]
4 IR versus FBP in Cardiac SPECT
Iterative reconstruction (IR) algorithms allow accurate mod-elling of statistical fluctuation (noise) produce accurateimages without streak artifacts as FBP and promise noisesuppression and improved resolution [30]
Themost commonly used IRmethod in SPECT studies isordered-subset expectation maximization (OSEM) Myocar-dial perfusion SPECT images reconstructed with OSEMIR algorithm have a superior quality than those processedwith FBP Perfusion defects anatomic variants and the right
(a) (b)
Figure 5 Comparison of vertical horizontal and short axis slicesof a stress perfusion imaging study reconstructed by FBP (a) and byOSEM (b) algorithm using the Butterworth filter (cutoff frequency03 cmminus1 and power 10) as a processing filter Data acquired byGE Starcam 4000 and reconstructed in Radiation Physics UnitUniversity Aretaieion Hospital Athens Greece 2013
ventricular myocardium are better visualized with OSEMLikewise image contrast is improved thereby better definingthe left ventricular endocardial borders The effect of OSEMon image quality improvement is more intense in lower countdensity studies [31]
Hatton et al [32] in myocardial perfusion SPECT studyshow that OSEM technique demonstrates fewer artifacts andimproves tolerance when projections are missing HoweverOSEM seems to be less tolerant in motion artifacts thanFBP [33] Won et al [34] in 2008 studied the impact of IRon myocardial perfusion imaging in 6 patients The resultsdemonstrate that there was no statistically significant differ-ence in the accuracy of myocardial perfusion interpretationbetween FBP and IR but there were statistically significantdifferences in functional results
A stress perfusion imaging study reconstructed bothby FBP and by OSEM algorithm using the Butterworthfilter is shown in Figure 5 It is believed that in such a casediagnostic information might be easier to obtain throughthe OSEM algorithm This is because corrections for imagedegrading effects such as attenuation scatter and resolutiondegradation as well as corrections for partial volume effectsand missing data are quite straightforward to be included inthe resulting image through iterative techniques [35]
5 Reconstruction and Processing of3D Cardiac SPECT Images
The 3-dimensional (3D) description of an organ and theinformation of an organrsquos surface can be obtained from asequence of 2D slices reconstructed from projections to forma volume image Volume visualization obtains volumetricsigns useful in diagnosis in a more familiar and realistic way
Cardiology Research and Practice 7
Filtering thresholding and gradient are necessary tools inthe production of diagnostic 3D images [36]
Cardiac SPECT provides information with respect to thedetection of myocardial perfusion defects the assessment ofthe pattern of defect reversibility and the overall detectionof coronary artery disease (CAD) There is a relationshipbetween the location and the degree of the stenosis in coro-nary arteries and the observed perfusion on the myocardialscintigraphy using data of 3D surface images ofmyocardiumThis allows us to predict the impact of evolution of thesestenoses to justify a coronarography or to avoid it
51 3-Dimensional Software Filter Application Seret andForthomme [37] have studied types of commercial softwarefor SPECT image processing It was also observed that therewere 2 definitions of the Butterworth filter For a fixed orderand a fixed cutoff frequency one definition led to a lesssmoothing filter which resulted in higher noise levels andsmaller FWHMs However differences in the FWHM weretranslated to differences in contrast only when they exceeded05 mm for the hot rods and 1 mm for the cold rods ofthe used phantom When considering the FWHM and noiselevel more noticeable differences between the workstationswere observed for OSEM reconstruction
All of the software types used in the study [37] behaved asexpected lowering the filter cutoff frequency in FBP resultedin larger FWHMs and in lower noise levels and reducedcontrast increasing the product number of subsets times thenumber of iterations in OSEM resulted in improved contrastand higher noise levels
Nowadays in many cases myocardium diagnosis is reliedon 3D surface shaded images 3D data obtained at stress andat rest of the LV myocardium respectively are analysed andthe deformation of both images is evaluated qualitatively andquantitatively
3D data reconstructed by IR were obtained by the GEVolumetrix software in the GE Xeleris processing systemat stress and rest MPI studies (Figure 6) Butterworth Filter(cutoff frequency 04 cmminus1 power 10) was used in bothreconstructions Chang attenuation correction was applied(coefficient = 01) These data were then used to evaluate theleft ventricle deformation in both stress and rest 3D surfaceimage series If a significant difference is obtained in rest andstress 3D data perfusion the location and the impact of thepathology of left ventricle myocardium are recognized
3D shaded surface display of a patient stress and rest per-fusion angular images (Figure 7) can be reconstructed by FBPor OSEM algorithm and improved usually by Butterworthor Hanning filter 3D reconstruction in studies by Tc99mtetrofosmin may show normal (or abnormal) myocardiumperfusion in apex base andwalls ofmyocardium Transaxialslices are used to be reconstructed and the created 3D volumeimages are displayedThrough base we recognize the cavity ofLV
52 3-Dimensional Reconstruction byMatLab Filters Applica-tion 3D reconstruction was also performed using a specified
(a)
(b)
Figure 6 3D reconstruction at stress (a) and rest (b) by OSEMiterative reconstruction (10 subsets) Butterworth filter (cutoff04Hz power 10 Chang AC coefficient 01) obtained by the GEVolumetrix software (GE Xeleris-2 processing system) The colourscale indicates a high perfusion in white and red regions and a lowerperfusion in the other regions Defected areas are seen on the aboveimage with a darker colour A perfusion recovery of the defects onthe rest images is observed Data acquired by GE Starcam 4000and reconstructed in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
(a)
(b)
Figure 7 Stress (a) and at rest (b) 3D surface angular images offemale myocardium Small defect at posterior-basal wall at stress isimproved almost completely at rest (2 rest defect) threshold value50 of maximum OSEM iterative reconstruction Defect lesionunder stress is recovered in rest condition (seen on the first structurein both above and below image)
MatLab code in order to evaluate the different filters used(Figure 10) and also to compare myocardium volume at restand at stress (Figure 11) In MatLab volume visualizationcan be achieved by constructing a 3D surface plot whichuses the pixel identities for (119909 119910) axes and the pixel valueis transformed into surface plot height and consequentlycolour Apart from that 3D voxel images can be constructedSPECT projections are acquired isocontours are depicted onthem including a number of voxels and finally all of them canbe added in order to create the desirable volume image [17]
8 Cardiology Research and Practice
40
35
30
25
20
15
25 30 35 40 45 50
(a)
34
32
30
28
26
24
22
20
36 38 40 42 44 46 48 50
(b)
Figure 8 Isocontour surfaces for threshold value determination in rest [17] Images obtained in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
40
35
30
25
20
15
30 35 40 45 50 55
(a)
34
32
30
28
26
24
22
20
34 36 38 40 42 44 46 48
(b)
Figure 9 Isocontour surfaces for threshold value determination in stress [17] Images obtained in Radiation Physics Unit UniversityAretaieio hospital Athens Greece 2013
Themethod is illustrated in Figures 8 and 9 for rest and stressconditions respectively
The volume rendered by MatLab is slow enough but sim-ilar to other codesrsquo volume renderings
The volume rendering used in 3D myocardium usedzoom angles of 56 degrees and a focal length in pixels de-pending on the organsrsquo sizeThe size of the reprojection is thesame as the main size of input image
6 4D Gated SPECT Imaging
In some cases SPECT imaging can be gated to the cardiacelectrocardiogram signal allowing data from specific parts ofthe cardiac cycle to be isolated and providing a spatiotem-poral approach (4D) It also allows a combined evaluation ofboth myocardial perfusion and left ventricular (LV) functionin one study which can provide additional information thatperfusion imaging cannot provide alone An example of sucha case are patients suffering from a 3-vessel coronary diseasewhere gated SPECThas been noted to yield significantlymoreabnormal segments than perfusion does alone [38]
As in a regular SPECT acquisition a 120574-camera registersphotons emitted from the object atmultiple projection anglesalong an arc of usually 180 degrees At each projection insteadof one static image several dynamic images are acquired
spanning the length of the cardiac cycle at equal intervalsThe cardiac cycle is marked within the R-R interval whichcorresponds to the end-diastole and is divided in 8-16 equalframes For each frame image data are acquired overmultiplecardiac cycles and stored All data for a specific frame are thenadded together to form an image representing a specific phaseof the cardiac cycle If temporal frames are added togetherthe resulting set of images is equivalent to a standard set ofungated perfusion images
During reconstruction in gated SPECT a significant levelof smoothing is required in comparison to ungated orsummedprojection data because of the relatively poor counts[39] This is done by using appropriate filters Several studieshave been made to establish the most appropriate filters forthis purpose
In a 201Tl gated SPECT study concerning patients withmajor myocardial infarction [40] a Butterworth filter oforder 5 with six cutoff frequencies (013 015 020 025030 and 035 cyclepixel) was successively testedThe reportshowed that filtering affects end diastolic volume (EDV) endsystolic volume (ESV) and left ventricular ejection fraction(LVEF) Marie et al [41] suggested that the best results forcardiac gated SPECT image reconstruction with 201Tl wereachieved using a Butterworth filter with an order of 5 andcutoff frequency 030 cyclespixel
Cardiology Research and Practice 9
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(a)
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(b)
Figure 10 3D volume of a normal myocardium reconstruction is obtained through a specifiedMatLab code in order to compare the differentfilters used Butterworth (a) and Hann (b) filetrs are used Insignificant voxel differences are observed Data acquired at Medical ImagingNuclear Medicine and MatLab algorithm in Radiation Physics Unit Aretaieion Hospital Athens
16
14
12
10
8
6
48
46
44
42
40
38
28 26 24 22 20 18 16
(a)
48
46
44
42
40
38
12
10
8
6
4
25
20
15
(b)
Figure 11 3Dmyocardium processed by aMatLab code in order to compare myocardium volume at rest (left) and at stress (right) (Lyra et al2010) The image does not depict the real volume but the voxelized one (the functional myocardium) Figure is obtained from citation [18]
In 2005 [42] the differences produced by change ofreconstruction filter in calculations of left-ventricular enddiastolic volume (EDV) end systolic volume (ESV) strokevolume (SV) and ejection fraction (LVEF) from 99mTc-sestamibi myocardial gated SPECT studies have been inves-tigated Butterworth order 4 cutoff frequency 025 cyclespixel and Metz order 8 full-width half maximum 40mmwere applied and compared With the Metz filter ratherthan the Butterworth filter left-ventricular EDV and ESVwere significantly larger and the LVEF and SV were notsignificantly changedThe results were consistent to previoussimilar studies [40 43]
7 Discussion
The SPECT filters can greatly affect the quality of clinicalimages Proper filter selection and adequate smoothing helpsthe physician in resultsrsquo interpretation and accurate diagnosis
Several studies on phantoms with respect to the mostappropriate filter for cardiac SPECT have been consideredThe studies showed that for the 3D SPECT reconstructionButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter producesthe best accurate size [20] Maximum contrast betweennormal and defected myocardium could be obtained using
10 Cardiology Research and Practice
the Metz (FWHM 35ndash45 pixel orders of 8ndash95) Wiener(FWHMs 35ndash4) Butterworth (cutoffs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) filters [29] The cutofffrequency of 0325 of Nq gave the best overall result for theHanning filter whereas for the Butterworth filter order 11and cut off of 045Nq gave the best image quality and sizeaccuracy [27]
For the 4DECG-gated SPECT reconstruction best resultswere obtained using a Butterworth filter with an order of 5and cutoff frequency of 030 cyclespixel [41]
As far as the reconstruction technique is concerned using3D OSEM with suitable AC may improve lesion detectabilitydue to the significant improvement of image contrast [35] 3Diterative reconstruction algorithms are likely to replace theFBP technique for many SPECT clinical applications
When a specified 3D reconstruction MatLab code wasused to compare both two chosen filters (Butterworth andHann) andmyocardium volume at rest and at stress accuratediagnostic images were produced
It is expected that further significant improvement inimage quality will be attained which in turn will increasethe confidence of image interpretation The development ofalgorithms for analysis of myocardial 3D images may allowbetter evaluation of small and nontransmural myocardialdefects For the diagnosis and treatment of heart diseasesthe accurate visualisation of the spatial heart shape 3Dvolume of the LV and the heart wall perfusion plays a crucialrole Surface shading is a valuable tool for determining thepresence extent and location of CAD
Further developments in cardiac diagnosis include anew promising tool computational cardiologyThe functionsof the diseased heart and the probable new techniques indiagnosis and treatment can be studied using state-of-the-art whole-heart models of electrophysiology and electrome-chanics A characteristic example of implementing such amodel is ventricular modelling where important aspects ofarrhythmias including dynamic characteristics of ventricu-lar fibrillation can be revealed Performing patient-specificcomputer simulations of the function of the diseased heart foreither diagnostic or treatment purposes could be an excitingnew implementation of computational cardiology [44]
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
References
[1] WHO Global Atlas on Cardiovascular Disease Prevention andControl WHO World Heart Federation World Stroke Organi-zation 2011 httpwwwwhointcardiovascular diseasesen
[2] S Agarwal M G Shlipak H Kramer A Jain and D MHerrington ldquoThe association of chronic kidney disease andmetabolic syndrome with incident cardiovascular events mul-tiethnic study of atherosclerosisrdquo Cardiology Research andPractice vol 2012 Article ID 806102 8 pages 2012
[3] H Jadvar H W Strauss and G M Segall ldquoSPECT and PET inthe evaluation of coronary artery diseaserdquo Radiographics vol19 no 4 pp 915ndash926 1999
[4] K van Laere M Koole I Lemahieu and R Dierckx ldquoImagefiltering in single-photon emission computed tomography Pri-nciples and applicationsrdquo Computerized Medical Imaging andGraphics vol 25 no 2 pp 127ndash133 2001
[5] E G DePuey D S Berman and E V Garcia Cardiac SPECTImaging Raven Press New York NY USA 1995
[6] G Germano ldquoTechnical aspects of myocardial SPECT imag-ingrdquo Journal of Nuclear Medicine vol 42 no 10 pp 1499ndash15072001
[7] S R Cherry J A Sorenson andM E Phelps Physics in NuclearMedicine Saunders Philadelphia Pa USA 2003
[8] J Qi and R M Leahy ldquoIterative reconstruction techniques inemission computed tomographyrdquo Physics in Medicine and Bi-ology vol 51 pp R541ndashR578 2006
[9] C Lee-Tzuu ldquoA method for attenuation correction in radionu-clide computed tomographyrdquo IEEE Transactions on NuclearScience vol 25 no 1 pp 638ndash643 1978
[10] P P Bruyant ldquoAnalytic and iterative reconstruction algorithmsin SPECTrdquo Journal of NuclearMedicine vol 43 no 10 pp 1343ndash1358 2002
[11] M Lyra and A Ploussi ldquoFiltering in SPECT image reconstruc-tionrdquo International Journal of Biomedical Imaging vol 2011Article ID 693795 14 pages 2011
[12] M W Groch and W D Erwin ldquoSPECT in the year 2000 basicprinciplesrdquo Journal of Nuclear Medicine Technology vol 28 no4 pp 233ndash244 2000
[13] M M Khalil Basic Sciences of Nuclear Medicine Springer Be-rlin Germany 2010
[14] M N Salihin and A Zakaria ldquoDetermination of the optimumfilter for qualitative and quantitative 99mTc myocardial SPECTimagingrdquo Iranian Journal of Radiation Research vol 6 no 4 pp173ndash182 2009
[15] A Sadremomtaz and P Taherparvar ldquoThe influence of filters onthe SPECT image of Carlson phantomrdquo Journal of BiomedicalScience and Engineering vol 6 pp 291ndash297 2013
[16] Society of Nuclear Medicine and Molecular Imaging (2012)Phantoms Cardiac SPECT simulator 2012 httpinteractivesnmorgindexcfmPageID=11666
[17] S SynefiaM SotiropoulosM Argyrou et al ldquo3D SPECTmyo-cardial volume estimation increases the reliability of perfusiondiagnosisrdquo e-Journal of Science and Technology In press
[18] M Lyra M Sotiropoulos N Lagopati and M GavrillelildquoQuantification of myocardial perfusion in 3D SPECT images-stressrest volume differences 3D myocardium images quan-tificationrdquo in Proceedings of the IEEE International Conferenceon Imaging Systems and Techniques (IST rsquo10) pp 31ndash35 Thessa-loniki Greece July 2010
[19] M A King S J Glick B C Penney R B Schwinger and PW Doherty ldquoInteractive visual optimization of SPECT prerec-onstruction filteringrdquo Journal of Nuclear Medicine vol 28 no 7pp 1192ndash1198 1987
[20] J M Links R W Jeremy S M Dyer T L Frank and L CBecker ldquoWiener filtering improves quantification of regionalmyocardial perfusion with thallium-201 SPECTrdquo Journal ofNuclear Medicine vol 31 no 7 pp 1230ndash1236 1990
[21] G V Heller A Mann and R C Hendel Nuclear CardiologyTechnical Applications McGraw-Hill New York NY USA2009
Cardiology Research and Practice 11
[22] B Tasdemir T Balci B Demirel I Karaca A Aydin and ZKoc ldquoComparison of myocardial perfusion scintigraphy andcomputed tomography (CT) angiography based on conven-tional coronary angiographyrdquo Natural Science vol 4 pp 976ndash982 2012
[23] S R Underwood C Anagnostopoulos M Cerqueira et alldquoMyocardial perfusion scintigraphy the evidencerdquo EuropeanJournal of Nuclear Medicine and Molecular Imaging vol 31 no2 pp 261ndash291 2004
[24] Y H Lue and F J Wackers Cardiovascular Imaging MansonPublishing 2010
[25] E G DePuey Imaging Guidelines for Nuclear Cardiology Proce-dures The American Society of Nuclear Cardiology 2006
[26] R A Carlson and J T Colvin ldquoFluke Biomedical Nuclear Asso-ciates 76ndash823 76ndash824 amp 76ndash825 PETSPECT Phantom SourceTank Phantom Inserts and Cardiac Insertrdquo 2006 httpwwwflukebiomedicalcomBiomedicalusenNuclear-MedicineQual-ity-Control-Phantoms76-825htmPID=55292
[27] A Takavar G Shamsipour M Sohrabi and M Eftekhari ldquoDe-termination of optimumfilter inmyocardial SPECT a phantomstudyrdquo Iranian Journal of Radiation Research vol 4 no 1 pp205ndash210 2004
[28] M N Salihin and A Zakaria ldquoRelationship between the opti-mum cut off frequency for Butterworth filter and lung-heartratio in 99mTcmyocardial SPECTrdquo Iranian Journal of RadiationResearch vol 8 no 1 pp 17ndash24 2010
[29] H Rajabi A Rajabi N Yaghoobi H Firouzabady and F Rust-gou ldquoDetermination of the optimum filter function for Tc99m-sestamibi myocardial perfusion SPECT imagingrdquo Indian Jour-nal of Nuclear Medicine vol 20 no 3 pp 77ndash82 2005
[30] S Vandenberghe Y DrsquoAsseler R van de Walle et al ldquoIterativereconstruction algorithms in nuclear medicinerdquo ComputerizedMedical Imaging and Graphics vol 25 no 2 pp 105ndash111 2001
[31] E G DePuey ldquoAdvances in SPECT camera software and hard-ware currently available and new on the horizonrdquo Journal ofNuclear Cardiology vol 19 no 3 pp 551ndash581 2012
[32] R L Hatton B F Hutton S Angelides K K L Choong andG Larcos ldquoImproved tolerance to missing data in myocardialperfusion SPET usingOSEM reconstructionrdquo European Journalof Nuclear Medicine and Molecular Imaging vol 31 no 6 pp857ndash861 2004
[33] S R Zakavi A Zonoozi V D Kakhki M Hajizadeh MMom-ennezhad and K Ariana ldquoImage reconstruction using filteredbackprojection and iterative method effect on motion artifactsin myocardial perfusion SPECTrdquo Journal of Nuclear MedicineTechnology vol 34 no 4 pp 220ndash223 2006
[34] KWon E KimMMar et al ldquoIs iterative reconstruction an im-provement over filtered back projection in processing gatedmyocardial perfusion SPECTrdquo The Open Medical ImagingJournal vol 2 pp 17ndash23 2008
[35] A Otte K Audenaert K Peremans K Heeringen and R Dier-ckx Nuclear Medicine in Psychiatry Springer Berlin Germany2004
[36] M Lyra ldquoSingle photon emission tomography (SPECT) and 3Dimages evaluation in nuclear medicinerdquo in Image ProcessingY S Chen Ed InTech 2009 httpwwwintechopencombooksimage-processingsingle-photon-emission-tomography-spect-and-3d-images-evaluation-in-nuclear-medicine
[37] A Seret and J Forthomme ldquoComparison of different types ofcommercial filtered backprojection and ordered-subset expec-tation maximization SPECT reconstruction softwarerdquo Journalof Nuclear Medicine Technology vol 37 no 3 pp 179ndash187 2009
[38] R S Lima D DWatson A R Goode et al ldquoIncremental valueof combined perfusion and function over perfusion alone bygated SPECT myocardial perfusion imaging for detection ofsevere three-vessel coronary artery diseaserdquo Journal of theAmerican College of Cardiology vol 42 no 1 pp 64ndash70 2003
[39] A K Paul andH A Nabi ldquoGatedmyocardial perfusion SPECTbasic principles technical aspects and clinical applicationsrdquoJournal of Nuclear Medicine Technology vol 32 no 4 pp 179ndash187 2004
[40] P Vera A Manrique V Pontvianne A Hitzel R Koningand A Cribier ldquoThallium-gated SPECT in patients with majormyocardial infarction effect of filtering and zooming in com-parison with equilibrium radionuclide imaging and left ven-triculographyrdquo Journal of Nuclear Medicine vol 40 no 4 pp513ndash521 1999
[41] P Y Marie W Djaballah P R Franken et al ldquoOSEM recon-struction associated with temporal Fourier and depth-dependant resolution recovery filtering enhances results fromsestamibi and 201T1 16-Interval Gated SPECTrdquo Journal ofNuclear Medicine vol 46 no 11 pp 1789ndash1795 2005
[42] T Vakhtangandze D O Hall F V Zananiri and M R ReesldquoThe effect of Butterworth and Metz reconstruction filters onvolume and ejection fraction calculations with 99Tcm gatedmyocardial SPECTrdquoBritish Journal of Radiology vol 78 no 932pp 733ndash736 2005
[43] G A Wright M McDade W Martin and I Hutton ldquoQuan-titative gated SPECT the effect of reconstruction filter oncalculated left ventricular ejection fractions and volumesrdquoPhysics in Medicine and Biology vol 47 no 8 pp 99ndash105 2002
[44] N Trayanova ldquoComputational cardiology the heart of thematterrdquo ISRN Cardiology vol 2012 Article ID 269680 15 pages2012
Figure 2 The effect of varying cutoff frequencies of Hanning filterwith FBP First column shows myocardial slices and second columnshows Hanning equation curves for various cutoff frequencies (0509 12 and 16) in cyclescm (minimum value 00 and maximumvalue 20)
parameter the cutoff frequency [14] The Hanning filter isdefined in the frequency domain as follows
119867(119891) =
05 + 05 cos(120587119891
119891119898
) 0 le10038161003816100381610038161198911003816100381610038161003816 le 119891119898
0 otherwise(3)
where 119891 are the spatial frequencies of the image and 119891119898is
the cutoff frequency The Hanning filter is very effective inreducing image noise because it reaches zero very quicklyHowever it does not preserve edgesThe effect of varying cut-off frequencies for the Hanning filter for FBP reconstructionis shown in Figure 2
244 Parzen Filter The Parzen filter is another example ofa low pass filter and is defined in the frequency domain asfollows [14]
10038161003816100381610038161198911003816100381610038161003816 minus 6
0 (10038161003816100381610038161198911003816100381610038161003816 ge 119891119898)
(4)
where119891 are the spatial frequencies of the image and 119891119898is the
cutoff frequencyThe Parzen filter is the most smoothing filter it not only
eliminates high frequency noise but it also degrades the imageresolution [4]
245 Metz Filter TheMetz filter is a function of modulationtransfer function (MTF) and it is based on the measured
MTF of the gamma camera system The MTF describes howthe system handles or degrades the frequencies The Metzrestoration filter is defined in the frequency domain as follows[19]
119872(119891) = MTF(119891)minus1 [1 minus (1 minusMTF(119891)2)119909
] (5)
where 119891 is the spatial domain and 119909 is a parameter thatcontrols the extent to which the inverse filter is followedbefore the low pass filter rolls off to zero
Equation (5) is the product of the inverse filter (first term)and a low pass filter (second term)
The Metz filter is count-dependent
246 Wiener Filter TheWiener filter is based on the signal-to-noise ratio (SNR) of a specific imageThe one-dimensionalfrequency domain form of the Wiener filter is defined asfollows [20]
119882(119891) = MTFminus1 times MTF2
(MTF2 + 119873119874) (6)
where MTF is the modulation transfer function of theimaging system119873 is the noise power spectrum and119874 is theobject power spectrum As with the Metz filter the Wiener isthe product of the inverse filter (which shows the resolutionrecovery) and the low pass filter (which shows the noisesuppression) In order to apply theWiener filter it is necessaryto know a priori the MTF the power spectrum of the objectand the power spectrum of the noise It has to be noticed thatis impossible to know exactly the MTF or the SNR in anyimage As a result the mathematical models used to optimizeboth Metz and Wiener filters are uncertain [4]
247 Cardiac SPECT Filter Dependence Gamma camerasystems offer a wide choice of filters in cardiac SPECT as wellas in many types of examinations The filter choice dependson several parameters [4 21]
(i) the energy of the isotope the number of counts andthe activity administration
(ii) the statistical noise and the background noise level(iii) the type of the organ being imaged(iv) the kind of information we want to obtain from the
images(v) the collimator that is used
The choice of the filter must ensure the best compromise be-tween the noise reduction and the resolution in the image
3 A Comparison of Various Filters in CardiacSPECT Studies on Phantoms
Myocardial SPECT is a well-established noninvasive tech-nique to detect flow-limiting coronary artery disease dur-ing stress and rest conditions Comparison of the myocar-dial distribution of radiopharmaceutical after stress and at
Cardiology Research and Practice 5
A
B
CD
(a) (b) (c) (d)
Figure 3 (a)TheCarlson phantom showing the individual inserts for resolution and contrast evaluation (b) the phantomassembled showingall inserts including hot and cold regions (c) schematic diagrams of the pairs holes as hot regions and drawn line profiles for evaluation ofhot regions (a)ndash(c) obtained from citation [15] (d) Cardiac insert with solidfillable defect set (Model ECTCARI)
rest provides information on myocardial viability inducibleperfusion abnormalities regional myocardial motion andthickening In cardiac SPECT the most commonly usedradiotracers are thallium-201 (201Tl) and technetium-99m( 99mTc) labeled agents such as sestamibi and tetrafosminAccording to the literature the sensitivity specificity andaccuracy of cardiac SPECT varies from 71 to 98 33 to89 and 72 to 95 respectively [22 23]
The quality of the myocardium SPECT images is degrad-ed by several factors The most important factors affect-ing image quality of myocardial perfusion SPECT are thestatistical fluctuation in photon detection the attenuationof photons through the tissues and the scatter radiation[24] Especially nuclear cardiology images because of theirrelatively low counts statistics (breast attenuation obesitypatients) tend to have greater amount of image noise [25]Image filtering is necessary to compensate these effects andtherefore to improve image quality
In order to test and improve the image quality in SPECTspecially constructed phantoms are used for measurementsAn example of such a phantom is the PETSPECT perfor-mance phantom designed and developed by Carlson andColvin [26] Fluke Biomedical Nuclear Associates (Figure 3)The effect of implementing different filters on the hot regionof Carlson phantom SPECT image was tested in order toevaluate the perceived image quality of the hot region and alsoits detectability as far as filters are concerned The findingsshowed that the more accurate locations of radionuclidedistribution were produced when using the Ram-Lak andShepp-Logan filters with cutoff frequency of 04 [15]
A cardiac insert (Figure 3(d)) may be used with theCarlson phantom to mimic the human heart for myocardialperfusion study The ldquoheartrdquo is approximately 8 cm in diame-ter and has a 15 cm thick hollow ldquowallrdquo which may be filledwith a solution containing 201Tl or 99mTcThe insert is placedwithin the source tank which could be filled with radioactivebackground solution [26] Evaluation of cardiac ECT dataacquisition and reconstruction methods can be performed aswell as a quantitative evaluation of nonuniform attenuationand scatter compensation methods Reconstruction of heartinsert images helps in standardization
Figure 4 The SNMMI 2012 Cardiac SPECT phantom simulatorshowing the myocardium insert manufacturedby Medical DesignsInc (MDI) Figure is obtained from citation [16]
Another three-dimensional simulator was created tomeet the imaging needs of general and cardiac nuclearimaging departments by Medical Designs Inc (MDI) TheSNMMI 2012 cardiac SPECT phantom simulator makespossible for myocardial perfusion studies to be performedand for areas of perfusion abnormality to be quantifiedFindings can then be evaluated as far as their diagnosticand prognostic significance is concerned [16] One can useit to perform both visual and semiquantitative evaluation ofthe images A picture of SNMMI cardiac phantom is shownbelow (Figure 4)
The standardization of image processing confines thefilter types for myocardium SPECT imaging to certain filtersMoreover only specific values of cutoff frequency and orderor power are selected to optimize image processing time andclinical results
Takavar et al [27] studied the determination of theoptimum filter in 99mTc myocardial SPECT using a phantomthat simulates the heart left ventricle Filters such as ParzenHanning Hamming and Butterworth and a combination oftheir characteristic parameters were applied on the phantom
6 Cardiology Research and Practice
images To choose the optimumfilter for quantitative analysiscontrast signal-to-noise ratio (SNR) and defect size criteriawere analyzed In each of these criteria were given a numberfrom 1 to 20 1 for the worst and 20 for the best contrastand SNR while 1 for the largest defect size and 20 for thesmallest For every filter the final criterion resulted from thetotal sum of the marks of the previous parameters The studyshowed that Parzen filter is inappropriate for heart studyThecutoff frequency of 0325Nq and 05Nq gave the best overallresult for Hanning and Hamming filters respectively ForButterworth filter order 11 and cutoff 045Nq gave the bestimage quality and size accuracy
A determination of the appropriate filter for myocardialSPECT was conducted by Salihin and Zakaria [14] Inthis study a cardiac phantom was filled with 40 120583CimL(0148MBqmL) 99mTc solution The filters functions evalu-ated in this study included Butterworth HammingHanningand Parzen filters From these filters 272 combinations offilter parameters were selected and applied to the projectiondata For the determination of the best filter Tanavar etal [27] method was applied [20] The study suggested thatButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter produced thebest accurate size
The same group [28] has investigated the relationshipbetween the optimum cutoff frequency for Butterworth filterand lung-heart ratio in 99mTc myocardial SPECT For thestudy a cardiac phantom was used and the optimum cutofffrequency and order of Butterworth filter were determinedusing Takavar et al method [27] A linear relationshipbetween cutoff frequency and lung-heart ratio had beenfound which shows that the lung-heart ratio of each patientmust be taken into account in order to choose the optimumcutoff frequency for Butterworth filter
Links et al [20] examined the effect of Wiener filterin myocardial perfusion with 201Tl SPECT The study wasdone in 19 dogs and showed that Wiener filter improves thequantization of regional myocardial perfusion defects
In amyocardial perfusion studywith 99mTc sestamibi theinvestigators explore the effect of different filters on the con-trast of the defected location Calculations showed that max-imum contrast between normal and defected myocardiumcould be obtained using the Metz (FWHM 35ndash45 pixelorders of 8ndash95) Wiener (FWHMs 35ndash4) Butterworth (cut-offs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) [29]
4 IR versus FBP in Cardiac SPECT
Iterative reconstruction (IR) algorithms allow accurate mod-elling of statistical fluctuation (noise) produce accurateimages without streak artifacts as FBP and promise noisesuppression and improved resolution [30]
Themost commonly used IRmethod in SPECT studies isordered-subset expectation maximization (OSEM) Myocar-dial perfusion SPECT images reconstructed with OSEMIR algorithm have a superior quality than those processedwith FBP Perfusion defects anatomic variants and the right
(a) (b)
Figure 5 Comparison of vertical horizontal and short axis slicesof a stress perfusion imaging study reconstructed by FBP (a) and byOSEM (b) algorithm using the Butterworth filter (cutoff frequency03 cmminus1 and power 10) as a processing filter Data acquired byGE Starcam 4000 and reconstructed in Radiation Physics UnitUniversity Aretaieion Hospital Athens Greece 2013
ventricular myocardium are better visualized with OSEMLikewise image contrast is improved thereby better definingthe left ventricular endocardial borders The effect of OSEMon image quality improvement is more intense in lower countdensity studies [31]
Hatton et al [32] in myocardial perfusion SPECT studyshow that OSEM technique demonstrates fewer artifacts andimproves tolerance when projections are missing HoweverOSEM seems to be less tolerant in motion artifacts thanFBP [33] Won et al [34] in 2008 studied the impact of IRon myocardial perfusion imaging in 6 patients The resultsdemonstrate that there was no statistically significant differ-ence in the accuracy of myocardial perfusion interpretationbetween FBP and IR but there were statistically significantdifferences in functional results
A stress perfusion imaging study reconstructed bothby FBP and by OSEM algorithm using the Butterworthfilter is shown in Figure 5 It is believed that in such a casediagnostic information might be easier to obtain throughthe OSEM algorithm This is because corrections for imagedegrading effects such as attenuation scatter and resolutiondegradation as well as corrections for partial volume effectsand missing data are quite straightforward to be included inthe resulting image through iterative techniques [35]
5 Reconstruction and Processing of3D Cardiac SPECT Images
The 3-dimensional (3D) description of an organ and theinformation of an organrsquos surface can be obtained from asequence of 2D slices reconstructed from projections to forma volume image Volume visualization obtains volumetricsigns useful in diagnosis in a more familiar and realistic way
Cardiology Research and Practice 7
Filtering thresholding and gradient are necessary tools inthe production of diagnostic 3D images [36]
Cardiac SPECT provides information with respect to thedetection of myocardial perfusion defects the assessment ofthe pattern of defect reversibility and the overall detectionof coronary artery disease (CAD) There is a relationshipbetween the location and the degree of the stenosis in coro-nary arteries and the observed perfusion on the myocardialscintigraphy using data of 3D surface images ofmyocardiumThis allows us to predict the impact of evolution of thesestenoses to justify a coronarography or to avoid it
51 3-Dimensional Software Filter Application Seret andForthomme [37] have studied types of commercial softwarefor SPECT image processing It was also observed that therewere 2 definitions of the Butterworth filter For a fixed orderand a fixed cutoff frequency one definition led to a lesssmoothing filter which resulted in higher noise levels andsmaller FWHMs However differences in the FWHM weretranslated to differences in contrast only when they exceeded05 mm for the hot rods and 1 mm for the cold rods ofthe used phantom When considering the FWHM and noiselevel more noticeable differences between the workstationswere observed for OSEM reconstruction
All of the software types used in the study [37] behaved asexpected lowering the filter cutoff frequency in FBP resultedin larger FWHMs and in lower noise levels and reducedcontrast increasing the product number of subsets times thenumber of iterations in OSEM resulted in improved contrastand higher noise levels
Nowadays in many cases myocardium diagnosis is reliedon 3D surface shaded images 3D data obtained at stress andat rest of the LV myocardium respectively are analysed andthe deformation of both images is evaluated qualitatively andquantitatively
3D data reconstructed by IR were obtained by the GEVolumetrix software in the GE Xeleris processing systemat stress and rest MPI studies (Figure 6) Butterworth Filter(cutoff frequency 04 cmminus1 power 10) was used in bothreconstructions Chang attenuation correction was applied(coefficient = 01) These data were then used to evaluate theleft ventricle deformation in both stress and rest 3D surfaceimage series If a significant difference is obtained in rest andstress 3D data perfusion the location and the impact of thepathology of left ventricle myocardium are recognized
3D shaded surface display of a patient stress and rest per-fusion angular images (Figure 7) can be reconstructed by FBPor OSEM algorithm and improved usually by Butterworthor Hanning filter 3D reconstruction in studies by Tc99mtetrofosmin may show normal (or abnormal) myocardiumperfusion in apex base andwalls ofmyocardium Transaxialslices are used to be reconstructed and the created 3D volumeimages are displayedThrough base we recognize the cavity ofLV
52 3-Dimensional Reconstruction byMatLab Filters Applica-tion 3D reconstruction was also performed using a specified
(a)
(b)
Figure 6 3D reconstruction at stress (a) and rest (b) by OSEMiterative reconstruction (10 subsets) Butterworth filter (cutoff04Hz power 10 Chang AC coefficient 01) obtained by the GEVolumetrix software (GE Xeleris-2 processing system) The colourscale indicates a high perfusion in white and red regions and a lowerperfusion in the other regions Defected areas are seen on the aboveimage with a darker colour A perfusion recovery of the defects onthe rest images is observed Data acquired by GE Starcam 4000and reconstructed in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
(a)
(b)
Figure 7 Stress (a) and at rest (b) 3D surface angular images offemale myocardium Small defect at posterior-basal wall at stress isimproved almost completely at rest (2 rest defect) threshold value50 of maximum OSEM iterative reconstruction Defect lesionunder stress is recovered in rest condition (seen on the first structurein both above and below image)
MatLab code in order to evaluate the different filters used(Figure 10) and also to compare myocardium volume at restand at stress (Figure 11) In MatLab volume visualizationcan be achieved by constructing a 3D surface plot whichuses the pixel identities for (119909 119910) axes and the pixel valueis transformed into surface plot height and consequentlycolour Apart from that 3D voxel images can be constructedSPECT projections are acquired isocontours are depicted onthem including a number of voxels and finally all of them canbe added in order to create the desirable volume image [17]
8 Cardiology Research and Practice
40
35
30
25
20
15
25 30 35 40 45 50
(a)
34
32
30
28
26
24
22
20
36 38 40 42 44 46 48 50
(b)
Figure 8 Isocontour surfaces for threshold value determination in rest [17] Images obtained in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
40
35
30
25
20
15
30 35 40 45 50 55
(a)
34
32
30
28
26
24
22
20
34 36 38 40 42 44 46 48
(b)
Figure 9 Isocontour surfaces for threshold value determination in stress [17] Images obtained in Radiation Physics Unit UniversityAretaieio hospital Athens Greece 2013
Themethod is illustrated in Figures 8 and 9 for rest and stressconditions respectively
The volume rendered by MatLab is slow enough but sim-ilar to other codesrsquo volume renderings
The volume rendering used in 3D myocardium usedzoom angles of 56 degrees and a focal length in pixels de-pending on the organsrsquo sizeThe size of the reprojection is thesame as the main size of input image
6 4D Gated SPECT Imaging
In some cases SPECT imaging can be gated to the cardiacelectrocardiogram signal allowing data from specific parts ofthe cardiac cycle to be isolated and providing a spatiotem-poral approach (4D) It also allows a combined evaluation ofboth myocardial perfusion and left ventricular (LV) functionin one study which can provide additional information thatperfusion imaging cannot provide alone An example of sucha case are patients suffering from a 3-vessel coronary diseasewhere gated SPECThas been noted to yield significantlymoreabnormal segments than perfusion does alone [38]
As in a regular SPECT acquisition a 120574-camera registersphotons emitted from the object atmultiple projection anglesalong an arc of usually 180 degrees At each projection insteadof one static image several dynamic images are acquired
spanning the length of the cardiac cycle at equal intervalsThe cardiac cycle is marked within the R-R interval whichcorresponds to the end-diastole and is divided in 8-16 equalframes For each frame image data are acquired overmultiplecardiac cycles and stored All data for a specific frame are thenadded together to form an image representing a specific phaseof the cardiac cycle If temporal frames are added togetherthe resulting set of images is equivalent to a standard set ofungated perfusion images
During reconstruction in gated SPECT a significant levelof smoothing is required in comparison to ungated orsummedprojection data because of the relatively poor counts[39] This is done by using appropriate filters Several studieshave been made to establish the most appropriate filters forthis purpose
In a 201Tl gated SPECT study concerning patients withmajor myocardial infarction [40] a Butterworth filter oforder 5 with six cutoff frequencies (013 015 020 025030 and 035 cyclepixel) was successively testedThe reportshowed that filtering affects end diastolic volume (EDV) endsystolic volume (ESV) and left ventricular ejection fraction(LVEF) Marie et al [41] suggested that the best results forcardiac gated SPECT image reconstruction with 201Tl wereachieved using a Butterworth filter with an order of 5 andcutoff frequency 030 cyclespixel
Cardiology Research and Practice 9
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(a)
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(b)
Figure 10 3D volume of a normal myocardium reconstruction is obtained through a specifiedMatLab code in order to compare the differentfilters used Butterworth (a) and Hann (b) filetrs are used Insignificant voxel differences are observed Data acquired at Medical ImagingNuclear Medicine and MatLab algorithm in Radiation Physics Unit Aretaieion Hospital Athens
16
14
12
10
8
6
48
46
44
42
40
38
28 26 24 22 20 18 16
(a)
48
46
44
42
40
38
12
10
8
6
4
25
20
15
(b)
Figure 11 3Dmyocardium processed by aMatLab code in order to compare myocardium volume at rest (left) and at stress (right) (Lyra et al2010) The image does not depict the real volume but the voxelized one (the functional myocardium) Figure is obtained from citation [18]
In 2005 [42] the differences produced by change ofreconstruction filter in calculations of left-ventricular enddiastolic volume (EDV) end systolic volume (ESV) strokevolume (SV) and ejection fraction (LVEF) from 99mTc-sestamibi myocardial gated SPECT studies have been inves-tigated Butterworth order 4 cutoff frequency 025 cyclespixel and Metz order 8 full-width half maximum 40mmwere applied and compared With the Metz filter ratherthan the Butterworth filter left-ventricular EDV and ESVwere significantly larger and the LVEF and SV were notsignificantly changedThe results were consistent to previoussimilar studies [40 43]
7 Discussion
The SPECT filters can greatly affect the quality of clinicalimages Proper filter selection and adequate smoothing helpsthe physician in resultsrsquo interpretation and accurate diagnosis
Several studies on phantoms with respect to the mostappropriate filter for cardiac SPECT have been consideredThe studies showed that for the 3D SPECT reconstructionButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter producesthe best accurate size [20] Maximum contrast betweennormal and defected myocardium could be obtained using
10 Cardiology Research and Practice
the Metz (FWHM 35ndash45 pixel orders of 8ndash95) Wiener(FWHMs 35ndash4) Butterworth (cutoffs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) filters [29] The cutofffrequency of 0325 of Nq gave the best overall result for theHanning filter whereas for the Butterworth filter order 11and cut off of 045Nq gave the best image quality and sizeaccuracy [27]
For the 4DECG-gated SPECT reconstruction best resultswere obtained using a Butterworth filter with an order of 5and cutoff frequency of 030 cyclespixel [41]
As far as the reconstruction technique is concerned using3D OSEM with suitable AC may improve lesion detectabilitydue to the significant improvement of image contrast [35] 3Diterative reconstruction algorithms are likely to replace theFBP technique for many SPECT clinical applications
When a specified 3D reconstruction MatLab code wasused to compare both two chosen filters (Butterworth andHann) andmyocardium volume at rest and at stress accuratediagnostic images were produced
It is expected that further significant improvement inimage quality will be attained which in turn will increasethe confidence of image interpretation The development ofalgorithms for analysis of myocardial 3D images may allowbetter evaluation of small and nontransmural myocardialdefects For the diagnosis and treatment of heart diseasesthe accurate visualisation of the spatial heart shape 3Dvolume of the LV and the heart wall perfusion plays a crucialrole Surface shading is a valuable tool for determining thepresence extent and location of CAD
Further developments in cardiac diagnosis include anew promising tool computational cardiologyThe functionsof the diseased heart and the probable new techniques indiagnosis and treatment can be studied using state-of-the-art whole-heart models of electrophysiology and electrome-chanics A characteristic example of implementing such amodel is ventricular modelling where important aspects ofarrhythmias including dynamic characteristics of ventricu-lar fibrillation can be revealed Performing patient-specificcomputer simulations of the function of the diseased heart foreither diagnostic or treatment purposes could be an excitingnew implementation of computational cardiology [44]
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
References
[1] WHO Global Atlas on Cardiovascular Disease Prevention andControl WHO World Heart Federation World Stroke Organi-zation 2011 httpwwwwhointcardiovascular diseasesen
[2] S Agarwal M G Shlipak H Kramer A Jain and D MHerrington ldquoThe association of chronic kidney disease andmetabolic syndrome with incident cardiovascular events mul-tiethnic study of atherosclerosisrdquo Cardiology Research andPractice vol 2012 Article ID 806102 8 pages 2012
[3] H Jadvar H W Strauss and G M Segall ldquoSPECT and PET inthe evaluation of coronary artery diseaserdquo Radiographics vol19 no 4 pp 915ndash926 1999
[4] K van Laere M Koole I Lemahieu and R Dierckx ldquoImagefiltering in single-photon emission computed tomography Pri-nciples and applicationsrdquo Computerized Medical Imaging andGraphics vol 25 no 2 pp 127ndash133 2001
[5] E G DePuey D S Berman and E V Garcia Cardiac SPECTImaging Raven Press New York NY USA 1995
[6] G Germano ldquoTechnical aspects of myocardial SPECT imag-ingrdquo Journal of Nuclear Medicine vol 42 no 10 pp 1499ndash15072001
[7] S R Cherry J A Sorenson andM E Phelps Physics in NuclearMedicine Saunders Philadelphia Pa USA 2003
[8] J Qi and R M Leahy ldquoIterative reconstruction techniques inemission computed tomographyrdquo Physics in Medicine and Bi-ology vol 51 pp R541ndashR578 2006
[9] C Lee-Tzuu ldquoA method for attenuation correction in radionu-clide computed tomographyrdquo IEEE Transactions on NuclearScience vol 25 no 1 pp 638ndash643 1978
[10] P P Bruyant ldquoAnalytic and iterative reconstruction algorithmsin SPECTrdquo Journal of NuclearMedicine vol 43 no 10 pp 1343ndash1358 2002
[11] M Lyra and A Ploussi ldquoFiltering in SPECT image reconstruc-tionrdquo International Journal of Biomedical Imaging vol 2011Article ID 693795 14 pages 2011
[12] M W Groch and W D Erwin ldquoSPECT in the year 2000 basicprinciplesrdquo Journal of Nuclear Medicine Technology vol 28 no4 pp 233ndash244 2000
[13] M M Khalil Basic Sciences of Nuclear Medicine Springer Be-rlin Germany 2010
[14] M N Salihin and A Zakaria ldquoDetermination of the optimumfilter for qualitative and quantitative 99mTc myocardial SPECTimagingrdquo Iranian Journal of Radiation Research vol 6 no 4 pp173ndash182 2009
[15] A Sadremomtaz and P Taherparvar ldquoThe influence of filters onthe SPECT image of Carlson phantomrdquo Journal of BiomedicalScience and Engineering vol 6 pp 291ndash297 2013
[16] Society of Nuclear Medicine and Molecular Imaging (2012)Phantoms Cardiac SPECT simulator 2012 httpinteractivesnmorgindexcfmPageID=11666
[17] S SynefiaM SotiropoulosM Argyrou et al ldquo3D SPECTmyo-cardial volume estimation increases the reliability of perfusiondiagnosisrdquo e-Journal of Science and Technology In press
[18] M Lyra M Sotiropoulos N Lagopati and M GavrillelildquoQuantification of myocardial perfusion in 3D SPECT images-stressrest volume differences 3D myocardium images quan-tificationrdquo in Proceedings of the IEEE International Conferenceon Imaging Systems and Techniques (IST rsquo10) pp 31ndash35 Thessa-loniki Greece July 2010
[19] M A King S J Glick B C Penney R B Schwinger and PW Doherty ldquoInteractive visual optimization of SPECT prerec-onstruction filteringrdquo Journal of Nuclear Medicine vol 28 no 7pp 1192ndash1198 1987
[20] J M Links R W Jeremy S M Dyer T L Frank and L CBecker ldquoWiener filtering improves quantification of regionalmyocardial perfusion with thallium-201 SPECTrdquo Journal ofNuclear Medicine vol 31 no 7 pp 1230ndash1236 1990
[21] G V Heller A Mann and R C Hendel Nuclear CardiologyTechnical Applications McGraw-Hill New York NY USA2009
Cardiology Research and Practice 11
[22] B Tasdemir T Balci B Demirel I Karaca A Aydin and ZKoc ldquoComparison of myocardial perfusion scintigraphy andcomputed tomography (CT) angiography based on conven-tional coronary angiographyrdquo Natural Science vol 4 pp 976ndash982 2012
[23] S R Underwood C Anagnostopoulos M Cerqueira et alldquoMyocardial perfusion scintigraphy the evidencerdquo EuropeanJournal of Nuclear Medicine and Molecular Imaging vol 31 no2 pp 261ndash291 2004
[24] Y H Lue and F J Wackers Cardiovascular Imaging MansonPublishing 2010
[25] E G DePuey Imaging Guidelines for Nuclear Cardiology Proce-dures The American Society of Nuclear Cardiology 2006
[26] R A Carlson and J T Colvin ldquoFluke Biomedical Nuclear Asso-ciates 76ndash823 76ndash824 amp 76ndash825 PETSPECT Phantom SourceTank Phantom Inserts and Cardiac Insertrdquo 2006 httpwwwflukebiomedicalcomBiomedicalusenNuclear-MedicineQual-ity-Control-Phantoms76-825htmPID=55292
[27] A Takavar G Shamsipour M Sohrabi and M Eftekhari ldquoDe-termination of optimumfilter inmyocardial SPECT a phantomstudyrdquo Iranian Journal of Radiation Research vol 4 no 1 pp205ndash210 2004
[28] M N Salihin and A Zakaria ldquoRelationship between the opti-mum cut off frequency for Butterworth filter and lung-heartratio in 99mTcmyocardial SPECTrdquo Iranian Journal of RadiationResearch vol 8 no 1 pp 17ndash24 2010
[29] H Rajabi A Rajabi N Yaghoobi H Firouzabady and F Rust-gou ldquoDetermination of the optimum filter function for Tc99m-sestamibi myocardial perfusion SPECT imagingrdquo Indian Jour-nal of Nuclear Medicine vol 20 no 3 pp 77ndash82 2005
[30] S Vandenberghe Y DrsquoAsseler R van de Walle et al ldquoIterativereconstruction algorithms in nuclear medicinerdquo ComputerizedMedical Imaging and Graphics vol 25 no 2 pp 105ndash111 2001
[31] E G DePuey ldquoAdvances in SPECT camera software and hard-ware currently available and new on the horizonrdquo Journal ofNuclear Cardiology vol 19 no 3 pp 551ndash581 2012
[32] R L Hatton B F Hutton S Angelides K K L Choong andG Larcos ldquoImproved tolerance to missing data in myocardialperfusion SPET usingOSEM reconstructionrdquo European Journalof Nuclear Medicine and Molecular Imaging vol 31 no 6 pp857ndash861 2004
[33] S R Zakavi A Zonoozi V D Kakhki M Hajizadeh MMom-ennezhad and K Ariana ldquoImage reconstruction using filteredbackprojection and iterative method effect on motion artifactsin myocardial perfusion SPECTrdquo Journal of Nuclear MedicineTechnology vol 34 no 4 pp 220ndash223 2006
[34] KWon E KimMMar et al ldquoIs iterative reconstruction an im-provement over filtered back projection in processing gatedmyocardial perfusion SPECTrdquo The Open Medical ImagingJournal vol 2 pp 17ndash23 2008
[35] A Otte K Audenaert K Peremans K Heeringen and R Dier-ckx Nuclear Medicine in Psychiatry Springer Berlin Germany2004
[36] M Lyra ldquoSingle photon emission tomography (SPECT) and 3Dimages evaluation in nuclear medicinerdquo in Image ProcessingY S Chen Ed InTech 2009 httpwwwintechopencombooksimage-processingsingle-photon-emission-tomography-spect-and-3d-images-evaluation-in-nuclear-medicine
[37] A Seret and J Forthomme ldquoComparison of different types ofcommercial filtered backprojection and ordered-subset expec-tation maximization SPECT reconstruction softwarerdquo Journalof Nuclear Medicine Technology vol 37 no 3 pp 179ndash187 2009
[38] R S Lima D DWatson A R Goode et al ldquoIncremental valueof combined perfusion and function over perfusion alone bygated SPECT myocardial perfusion imaging for detection ofsevere three-vessel coronary artery diseaserdquo Journal of theAmerican College of Cardiology vol 42 no 1 pp 64ndash70 2003
[39] A K Paul andH A Nabi ldquoGatedmyocardial perfusion SPECTbasic principles technical aspects and clinical applicationsrdquoJournal of Nuclear Medicine Technology vol 32 no 4 pp 179ndash187 2004
[40] P Vera A Manrique V Pontvianne A Hitzel R Koningand A Cribier ldquoThallium-gated SPECT in patients with majormyocardial infarction effect of filtering and zooming in com-parison with equilibrium radionuclide imaging and left ven-triculographyrdquo Journal of Nuclear Medicine vol 40 no 4 pp513ndash521 1999
[41] P Y Marie W Djaballah P R Franken et al ldquoOSEM recon-struction associated with temporal Fourier and depth-dependant resolution recovery filtering enhances results fromsestamibi and 201T1 16-Interval Gated SPECTrdquo Journal ofNuclear Medicine vol 46 no 11 pp 1789ndash1795 2005
[42] T Vakhtangandze D O Hall F V Zananiri and M R ReesldquoThe effect of Butterworth and Metz reconstruction filters onvolume and ejection fraction calculations with 99Tcm gatedmyocardial SPECTrdquoBritish Journal of Radiology vol 78 no 932pp 733ndash736 2005
[43] G A Wright M McDade W Martin and I Hutton ldquoQuan-titative gated SPECT the effect of reconstruction filter oncalculated left ventricular ejection fractions and volumesrdquoPhysics in Medicine and Biology vol 47 no 8 pp 99ndash105 2002
[44] N Trayanova ldquoComputational cardiology the heart of thematterrdquo ISRN Cardiology vol 2012 Article ID 269680 15 pages2012
Figure 3 (a)TheCarlson phantom showing the individual inserts for resolution and contrast evaluation (b) the phantomassembled showingall inserts including hot and cold regions (c) schematic diagrams of the pairs holes as hot regions and drawn line profiles for evaluation ofhot regions (a)ndash(c) obtained from citation [15] (d) Cardiac insert with solidfillable defect set (Model ECTCARI)
rest provides information on myocardial viability inducibleperfusion abnormalities regional myocardial motion andthickening In cardiac SPECT the most commonly usedradiotracers are thallium-201 (201Tl) and technetium-99m( 99mTc) labeled agents such as sestamibi and tetrafosminAccording to the literature the sensitivity specificity andaccuracy of cardiac SPECT varies from 71 to 98 33 to89 and 72 to 95 respectively [22 23]
The quality of the myocardium SPECT images is degrad-ed by several factors The most important factors affect-ing image quality of myocardial perfusion SPECT are thestatistical fluctuation in photon detection the attenuationof photons through the tissues and the scatter radiation[24] Especially nuclear cardiology images because of theirrelatively low counts statistics (breast attenuation obesitypatients) tend to have greater amount of image noise [25]Image filtering is necessary to compensate these effects andtherefore to improve image quality
In order to test and improve the image quality in SPECTspecially constructed phantoms are used for measurementsAn example of such a phantom is the PETSPECT perfor-mance phantom designed and developed by Carlson andColvin [26] Fluke Biomedical Nuclear Associates (Figure 3)The effect of implementing different filters on the hot regionof Carlson phantom SPECT image was tested in order toevaluate the perceived image quality of the hot region and alsoits detectability as far as filters are concerned The findingsshowed that the more accurate locations of radionuclidedistribution were produced when using the Ram-Lak andShepp-Logan filters with cutoff frequency of 04 [15]
A cardiac insert (Figure 3(d)) may be used with theCarlson phantom to mimic the human heart for myocardialperfusion study The ldquoheartrdquo is approximately 8 cm in diame-ter and has a 15 cm thick hollow ldquowallrdquo which may be filledwith a solution containing 201Tl or 99mTcThe insert is placedwithin the source tank which could be filled with radioactivebackground solution [26] Evaluation of cardiac ECT dataacquisition and reconstruction methods can be performed aswell as a quantitative evaluation of nonuniform attenuationand scatter compensation methods Reconstruction of heartinsert images helps in standardization
Figure 4 The SNMMI 2012 Cardiac SPECT phantom simulatorshowing the myocardium insert manufacturedby Medical DesignsInc (MDI) Figure is obtained from citation [16]
Another three-dimensional simulator was created tomeet the imaging needs of general and cardiac nuclearimaging departments by Medical Designs Inc (MDI) TheSNMMI 2012 cardiac SPECT phantom simulator makespossible for myocardial perfusion studies to be performedand for areas of perfusion abnormality to be quantifiedFindings can then be evaluated as far as their diagnosticand prognostic significance is concerned [16] One can useit to perform both visual and semiquantitative evaluation ofthe images A picture of SNMMI cardiac phantom is shownbelow (Figure 4)
The standardization of image processing confines thefilter types for myocardium SPECT imaging to certain filtersMoreover only specific values of cutoff frequency and orderor power are selected to optimize image processing time andclinical results
Takavar et al [27] studied the determination of theoptimum filter in 99mTc myocardial SPECT using a phantomthat simulates the heart left ventricle Filters such as ParzenHanning Hamming and Butterworth and a combination oftheir characteristic parameters were applied on the phantom
6 Cardiology Research and Practice
images To choose the optimumfilter for quantitative analysiscontrast signal-to-noise ratio (SNR) and defect size criteriawere analyzed In each of these criteria were given a numberfrom 1 to 20 1 for the worst and 20 for the best contrastand SNR while 1 for the largest defect size and 20 for thesmallest For every filter the final criterion resulted from thetotal sum of the marks of the previous parameters The studyshowed that Parzen filter is inappropriate for heart studyThecutoff frequency of 0325Nq and 05Nq gave the best overallresult for Hanning and Hamming filters respectively ForButterworth filter order 11 and cutoff 045Nq gave the bestimage quality and size accuracy
A determination of the appropriate filter for myocardialSPECT was conducted by Salihin and Zakaria [14] Inthis study a cardiac phantom was filled with 40 120583CimL(0148MBqmL) 99mTc solution The filters functions evalu-ated in this study included Butterworth HammingHanningand Parzen filters From these filters 272 combinations offilter parameters were selected and applied to the projectiondata For the determination of the best filter Tanavar etal [27] method was applied [20] The study suggested thatButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter produced thebest accurate size
The same group [28] has investigated the relationshipbetween the optimum cutoff frequency for Butterworth filterand lung-heart ratio in 99mTc myocardial SPECT For thestudy a cardiac phantom was used and the optimum cutofffrequency and order of Butterworth filter were determinedusing Takavar et al method [27] A linear relationshipbetween cutoff frequency and lung-heart ratio had beenfound which shows that the lung-heart ratio of each patientmust be taken into account in order to choose the optimumcutoff frequency for Butterworth filter
Links et al [20] examined the effect of Wiener filterin myocardial perfusion with 201Tl SPECT The study wasdone in 19 dogs and showed that Wiener filter improves thequantization of regional myocardial perfusion defects
In amyocardial perfusion studywith 99mTc sestamibi theinvestigators explore the effect of different filters on the con-trast of the defected location Calculations showed that max-imum contrast between normal and defected myocardiumcould be obtained using the Metz (FWHM 35ndash45 pixelorders of 8ndash95) Wiener (FWHMs 35ndash4) Butterworth (cut-offs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) [29]
4 IR versus FBP in Cardiac SPECT
Iterative reconstruction (IR) algorithms allow accurate mod-elling of statistical fluctuation (noise) produce accurateimages without streak artifacts as FBP and promise noisesuppression and improved resolution [30]
Themost commonly used IRmethod in SPECT studies isordered-subset expectation maximization (OSEM) Myocar-dial perfusion SPECT images reconstructed with OSEMIR algorithm have a superior quality than those processedwith FBP Perfusion defects anatomic variants and the right
(a) (b)
Figure 5 Comparison of vertical horizontal and short axis slicesof a stress perfusion imaging study reconstructed by FBP (a) and byOSEM (b) algorithm using the Butterworth filter (cutoff frequency03 cmminus1 and power 10) as a processing filter Data acquired byGE Starcam 4000 and reconstructed in Radiation Physics UnitUniversity Aretaieion Hospital Athens Greece 2013
ventricular myocardium are better visualized with OSEMLikewise image contrast is improved thereby better definingthe left ventricular endocardial borders The effect of OSEMon image quality improvement is more intense in lower countdensity studies [31]
Hatton et al [32] in myocardial perfusion SPECT studyshow that OSEM technique demonstrates fewer artifacts andimproves tolerance when projections are missing HoweverOSEM seems to be less tolerant in motion artifacts thanFBP [33] Won et al [34] in 2008 studied the impact of IRon myocardial perfusion imaging in 6 patients The resultsdemonstrate that there was no statistically significant differ-ence in the accuracy of myocardial perfusion interpretationbetween FBP and IR but there were statistically significantdifferences in functional results
A stress perfusion imaging study reconstructed bothby FBP and by OSEM algorithm using the Butterworthfilter is shown in Figure 5 It is believed that in such a casediagnostic information might be easier to obtain throughthe OSEM algorithm This is because corrections for imagedegrading effects such as attenuation scatter and resolutiondegradation as well as corrections for partial volume effectsand missing data are quite straightforward to be included inthe resulting image through iterative techniques [35]
5 Reconstruction and Processing of3D Cardiac SPECT Images
The 3-dimensional (3D) description of an organ and theinformation of an organrsquos surface can be obtained from asequence of 2D slices reconstructed from projections to forma volume image Volume visualization obtains volumetricsigns useful in diagnosis in a more familiar and realistic way
Cardiology Research and Practice 7
Filtering thresholding and gradient are necessary tools inthe production of diagnostic 3D images [36]
Cardiac SPECT provides information with respect to thedetection of myocardial perfusion defects the assessment ofthe pattern of defect reversibility and the overall detectionof coronary artery disease (CAD) There is a relationshipbetween the location and the degree of the stenosis in coro-nary arteries and the observed perfusion on the myocardialscintigraphy using data of 3D surface images ofmyocardiumThis allows us to predict the impact of evolution of thesestenoses to justify a coronarography or to avoid it
51 3-Dimensional Software Filter Application Seret andForthomme [37] have studied types of commercial softwarefor SPECT image processing It was also observed that therewere 2 definitions of the Butterworth filter For a fixed orderand a fixed cutoff frequency one definition led to a lesssmoothing filter which resulted in higher noise levels andsmaller FWHMs However differences in the FWHM weretranslated to differences in contrast only when they exceeded05 mm for the hot rods and 1 mm for the cold rods ofthe used phantom When considering the FWHM and noiselevel more noticeable differences between the workstationswere observed for OSEM reconstruction
All of the software types used in the study [37] behaved asexpected lowering the filter cutoff frequency in FBP resultedin larger FWHMs and in lower noise levels and reducedcontrast increasing the product number of subsets times thenumber of iterations in OSEM resulted in improved contrastand higher noise levels
Nowadays in many cases myocardium diagnosis is reliedon 3D surface shaded images 3D data obtained at stress andat rest of the LV myocardium respectively are analysed andthe deformation of both images is evaluated qualitatively andquantitatively
3D data reconstructed by IR were obtained by the GEVolumetrix software in the GE Xeleris processing systemat stress and rest MPI studies (Figure 6) Butterworth Filter(cutoff frequency 04 cmminus1 power 10) was used in bothreconstructions Chang attenuation correction was applied(coefficient = 01) These data were then used to evaluate theleft ventricle deformation in both stress and rest 3D surfaceimage series If a significant difference is obtained in rest andstress 3D data perfusion the location and the impact of thepathology of left ventricle myocardium are recognized
3D shaded surface display of a patient stress and rest per-fusion angular images (Figure 7) can be reconstructed by FBPor OSEM algorithm and improved usually by Butterworthor Hanning filter 3D reconstruction in studies by Tc99mtetrofosmin may show normal (or abnormal) myocardiumperfusion in apex base andwalls ofmyocardium Transaxialslices are used to be reconstructed and the created 3D volumeimages are displayedThrough base we recognize the cavity ofLV
52 3-Dimensional Reconstruction byMatLab Filters Applica-tion 3D reconstruction was also performed using a specified
(a)
(b)
Figure 6 3D reconstruction at stress (a) and rest (b) by OSEMiterative reconstruction (10 subsets) Butterworth filter (cutoff04Hz power 10 Chang AC coefficient 01) obtained by the GEVolumetrix software (GE Xeleris-2 processing system) The colourscale indicates a high perfusion in white and red regions and a lowerperfusion in the other regions Defected areas are seen on the aboveimage with a darker colour A perfusion recovery of the defects onthe rest images is observed Data acquired by GE Starcam 4000and reconstructed in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
(a)
(b)
Figure 7 Stress (a) and at rest (b) 3D surface angular images offemale myocardium Small defect at posterior-basal wall at stress isimproved almost completely at rest (2 rest defect) threshold value50 of maximum OSEM iterative reconstruction Defect lesionunder stress is recovered in rest condition (seen on the first structurein both above and below image)
MatLab code in order to evaluate the different filters used(Figure 10) and also to compare myocardium volume at restand at stress (Figure 11) In MatLab volume visualizationcan be achieved by constructing a 3D surface plot whichuses the pixel identities for (119909 119910) axes and the pixel valueis transformed into surface plot height and consequentlycolour Apart from that 3D voxel images can be constructedSPECT projections are acquired isocontours are depicted onthem including a number of voxels and finally all of them canbe added in order to create the desirable volume image [17]
8 Cardiology Research and Practice
40
35
30
25
20
15
25 30 35 40 45 50
(a)
34
32
30
28
26
24
22
20
36 38 40 42 44 46 48 50
(b)
Figure 8 Isocontour surfaces for threshold value determination in rest [17] Images obtained in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
40
35
30
25
20
15
30 35 40 45 50 55
(a)
34
32
30
28
26
24
22
20
34 36 38 40 42 44 46 48
(b)
Figure 9 Isocontour surfaces for threshold value determination in stress [17] Images obtained in Radiation Physics Unit UniversityAretaieio hospital Athens Greece 2013
Themethod is illustrated in Figures 8 and 9 for rest and stressconditions respectively
The volume rendered by MatLab is slow enough but sim-ilar to other codesrsquo volume renderings
The volume rendering used in 3D myocardium usedzoom angles of 56 degrees and a focal length in pixels de-pending on the organsrsquo sizeThe size of the reprojection is thesame as the main size of input image
6 4D Gated SPECT Imaging
In some cases SPECT imaging can be gated to the cardiacelectrocardiogram signal allowing data from specific parts ofthe cardiac cycle to be isolated and providing a spatiotem-poral approach (4D) It also allows a combined evaluation ofboth myocardial perfusion and left ventricular (LV) functionin one study which can provide additional information thatperfusion imaging cannot provide alone An example of sucha case are patients suffering from a 3-vessel coronary diseasewhere gated SPECThas been noted to yield significantlymoreabnormal segments than perfusion does alone [38]
As in a regular SPECT acquisition a 120574-camera registersphotons emitted from the object atmultiple projection anglesalong an arc of usually 180 degrees At each projection insteadof one static image several dynamic images are acquired
spanning the length of the cardiac cycle at equal intervalsThe cardiac cycle is marked within the R-R interval whichcorresponds to the end-diastole and is divided in 8-16 equalframes For each frame image data are acquired overmultiplecardiac cycles and stored All data for a specific frame are thenadded together to form an image representing a specific phaseof the cardiac cycle If temporal frames are added togetherthe resulting set of images is equivalent to a standard set ofungated perfusion images
During reconstruction in gated SPECT a significant levelof smoothing is required in comparison to ungated orsummedprojection data because of the relatively poor counts[39] This is done by using appropriate filters Several studieshave been made to establish the most appropriate filters forthis purpose
In a 201Tl gated SPECT study concerning patients withmajor myocardial infarction [40] a Butterworth filter oforder 5 with six cutoff frequencies (013 015 020 025030 and 035 cyclepixel) was successively testedThe reportshowed that filtering affects end diastolic volume (EDV) endsystolic volume (ESV) and left ventricular ejection fraction(LVEF) Marie et al [41] suggested that the best results forcardiac gated SPECT image reconstruction with 201Tl wereachieved using a Butterworth filter with an order of 5 andcutoff frequency 030 cyclespixel
Cardiology Research and Practice 9
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(a)
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(b)
Figure 10 3D volume of a normal myocardium reconstruction is obtained through a specifiedMatLab code in order to compare the differentfilters used Butterworth (a) and Hann (b) filetrs are used Insignificant voxel differences are observed Data acquired at Medical ImagingNuclear Medicine and MatLab algorithm in Radiation Physics Unit Aretaieion Hospital Athens
16
14
12
10
8
6
48
46
44
42
40
38
28 26 24 22 20 18 16
(a)
48
46
44
42
40
38
12
10
8
6
4
25
20
15
(b)
Figure 11 3Dmyocardium processed by aMatLab code in order to compare myocardium volume at rest (left) and at stress (right) (Lyra et al2010) The image does not depict the real volume but the voxelized one (the functional myocardium) Figure is obtained from citation [18]
In 2005 [42] the differences produced by change ofreconstruction filter in calculations of left-ventricular enddiastolic volume (EDV) end systolic volume (ESV) strokevolume (SV) and ejection fraction (LVEF) from 99mTc-sestamibi myocardial gated SPECT studies have been inves-tigated Butterworth order 4 cutoff frequency 025 cyclespixel and Metz order 8 full-width half maximum 40mmwere applied and compared With the Metz filter ratherthan the Butterworth filter left-ventricular EDV and ESVwere significantly larger and the LVEF and SV were notsignificantly changedThe results were consistent to previoussimilar studies [40 43]
7 Discussion
The SPECT filters can greatly affect the quality of clinicalimages Proper filter selection and adequate smoothing helpsthe physician in resultsrsquo interpretation and accurate diagnosis
Several studies on phantoms with respect to the mostappropriate filter for cardiac SPECT have been consideredThe studies showed that for the 3D SPECT reconstructionButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter producesthe best accurate size [20] Maximum contrast betweennormal and defected myocardium could be obtained using
10 Cardiology Research and Practice
the Metz (FWHM 35ndash45 pixel orders of 8ndash95) Wiener(FWHMs 35ndash4) Butterworth (cutoffs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) filters [29] The cutofffrequency of 0325 of Nq gave the best overall result for theHanning filter whereas for the Butterworth filter order 11and cut off of 045Nq gave the best image quality and sizeaccuracy [27]
For the 4DECG-gated SPECT reconstruction best resultswere obtained using a Butterworth filter with an order of 5and cutoff frequency of 030 cyclespixel [41]
As far as the reconstruction technique is concerned using3D OSEM with suitable AC may improve lesion detectabilitydue to the significant improvement of image contrast [35] 3Diterative reconstruction algorithms are likely to replace theFBP technique for many SPECT clinical applications
When a specified 3D reconstruction MatLab code wasused to compare both two chosen filters (Butterworth andHann) andmyocardium volume at rest and at stress accuratediagnostic images were produced
It is expected that further significant improvement inimage quality will be attained which in turn will increasethe confidence of image interpretation The development ofalgorithms for analysis of myocardial 3D images may allowbetter evaluation of small and nontransmural myocardialdefects For the diagnosis and treatment of heart diseasesthe accurate visualisation of the spatial heart shape 3Dvolume of the LV and the heart wall perfusion plays a crucialrole Surface shading is a valuable tool for determining thepresence extent and location of CAD
Further developments in cardiac diagnosis include anew promising tool computational cardiologyThe functionsof the diseased heart and the probable new techniques indiagnosis and treatment can be studied using state-of-the-art whole-heart models of electrophysiology and electrome-chanics A characteristic example of implementing such amodel is ventricular modelling where important aspects ofarrhythmias including dynamic characteristics of ventricu-lar fibrillation can be revealed Performing patient-specificcomputer simulations of the function of the diseased heart foreither diagnostic or treatment purposes could be an excitingnew implementation of computational cardiology [44]
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
References
[1] WHO Global Atlas on Cardiovascular Disease Prevention andControl WHO World Heart Federation World Stroke Organi-zation 2011 httpwwwwhointcardiovascular diseasesen
[2] S Agarwal M G Shlipak H Kramer A Jain and D MHerrington ldquoThe association of chronic kidney disease andmetabolic syndrome with incident cardiovascular events mul-tiethnic study of atherosclerosisrdquo Cardiology Research andPractice vol 2012 Article ID 806102 8 pages 2012
[3] H Jadvar H W Strauss and G M Segall ldquoSPECT and PET inthe evaluation of coronary artery diseaserdquo Radiographics vol19 no 4 pp 915ndash926 1999
[4] K van Laere M Koole I Lemahieu and R Dierckx ldquoImagefiltering in single-photon emission computed tomography Pri-nciples and applicationsrdquo Computerized Medical Imaging andGraphics vol 25 no 2 pp 127ndash133 2001
[5] E G DePuey D S Berman and E V Garcia Cardiac SPECTImaging Raven Press New York NY USA 1995
[6] G Germano ldquoTechnical aspects of myocardial SPECT imag-ingrdquo Journal of Nuclear Medicine vol 42 no 10 pp 1499ndash15072001
[7] S R Cherry J A Sorenson andM E Phelps Physics in NuclearMedicine Saunders Philadelphia Pa USA 2003
[8] J Qi and R M Leahy ldquoIterative reconstruction techniques inemission computed tomographyrdquo Physics in Medicine and Bi-ology vol 51 pp R541ndashR578 2006
[9] C Lee-Tzuu ldquoA method for attenuation correction in radionu-clide computed tomographyrdquo IEEE Transactions on NuclearScience vol 25 no 1 pp 638ndash643 1978
[10] P P Bruyant ldquoAnalytic and iterative reconstruction algorithmsin SPECTrdquo Journal of NuclearMedicine vol 43 no 10 pp 1343ndash1358 2002
[11] M Lyra and A Ploussi ldquoFiltering in SPECT image reconstruc-tionrdquo International Journal of Biomedical Imaging vol 2011Article ID 693795 14 pages 2011
[12] M W Groch and W D Erwin ldquoSPECT in the year 2000 basicprinciplesrdquo Journal of Nuclear Medicine Technology vol 28 no4 pp 233ndash244 2000
[13] M M Khalil Basic Sciences of Nuclear Medicine Springer Be-rlin Germany 2010
[14] M N Salihin and A Zakaria ldquoDetermination of the optimumfilter for qualitative and quantitative 99mTc myocardial SPECTimagingrdquo Iranian Journal of Radiation Research vol 6 no 4 pp173ndash182 2009
[15] A Sadremomtaz and P Taherparvar ldquoThe influence of filters onthe SPECT image of Carlson phantomrdquo Journal of BiomedicalScience and Engineering vol 6 pp 291ndash297 2013
[16] Society of Nuclear Medicine and Molecular Imaging (2012)Phantoms Cardiac SPECT simulator 2012 httpinteractivesnmorgindexcfmPageID=11666
[17] S SynefiaM SotiropoulosM Argyrou et al ldquo3D SPECTmyo-cardial volume estimation increases the reliability of perfusiondiagnosisrdquo e-Journal of Science and Technology In press
[18] M Lyra M Sotiropoulos N Lagopati and M GavrillelildquoQuantification of myocardial perfusion in 3D SPECT images-stressrest volume differences 3D myocardium images quan-tificationrdquo in Proceedings of the IEEE International Conferenceon Imaging Systems and Techniques (IST rsquo10) pp 31ndash35 Thessa-loniki Greece July 2010
[19] M A King S J Glick B C Penney R B Schwinger and PW Doherty ldquoInteractive visual optimization of SPECT prerec-onstruction filteringrdquo Journal of Nuclear Medicine vol 28 no 7pp 1192ndash1198 1987
[20] J M Links R W Jeremy S M Dyer T L Frank and L CBecker ldquoWiener filtering improves quantification of regionalmyocardial perfusion with thallium-201 SPECTrdquo Journal ofNuclear Medicine vol 31 no 7 pp 1230ndash1236 1990
[21] G V Heller A Mann and R C Hendel Nuclear CardiologyTechnical Applications McGraw-Hill New York NY USA2009
Cardiology Research and Practice 11
[22] B Tasdemir T Balci B Demirel I Karaca A Aydin and ZKoc ldquoComparison of myocardial perfusion scintigraphy andcomputed tomography (CT) angiography based on conven-tional coronary angiographyrdquo Natural Science vol 4 pp 976ndash982 2012
[23] S R Underwood C Anagnostopoulos M Cerqueira et alldquoMyocardial perfusion scintigraphy the evidencerdquo EuropeanJournal of Nuclear Medicine and Molecular Imaging vol 31 no2 pp 261ndash291 2004
[24] Y H Lue and F J Wackers Cardiovascular Imaging MansonPublishing 2010
[25] E G DePuey Imaging Guidelines for Nuclear Cardiology Proce-dures The American Society of Nuclear Cardiology 2006
[26] R A Carlson and J T Colvin ldquoFluke Biomedical Nuclear Asso-ciates 76ndash823 76ndash824 amp 76ndash825 PETSPECT Phantom SourceTank Phantom Inserts and Cardiac Insertrdquo 2006 httpwwwflukebiomedicalcomBiomedicalusenNuclear-MedicineQual-ity-Control-Phantoms76-825htmPID=55292
[27] A Takavar G Shamsipour M Sohrabi and M Eftekhari ldquoDe-termination of optimumfilter inmyocardial SPECT a phantomstudyrdquo Iranian Journal of Radiation Research vol 4 no 1 pp205ndash210 2004
[28] M N Salihin and A Zakaria ldquoRelationship between the opti-mum cut off frequency for Butterworth filter and lung-heartratio in 99mTcmyocardial SPECTrdquo Iranian Journal of RadiationResearch vol 8 no 1 pp 17ndash24 2010
[29] H Rajabi A Rajabi N Yaghoobi H Firouzabady and F Rust-gou ldquoDetermination of the optimum filter function for Tc99m-sestamibi myocardial perfusion SPECT imagingrdquo Indian Jour-nal of Nuclear Medicine vol 20 no 3 pp 77ndash82 2005
[30] S Vandenberghe Y DrsquoAsseler R van de Walle et al ldquoIterativereconstruction algorithms in nuclear medicinerdquo ComputerizedMedical Imaging and Graphics vol 25 no 2 pp 105ndash111 2001
[31] E G DePuey ldquoAdvances in SPECT camera software and hard-ware currently available and new on the horizonrdquo Journal ofNuclear Cardiology vol 19 no 3 pp 551ndash581 2012
[32] R L Hatton B F Hutton S Angelides K K L Choong andG Larcos ldquoImproved tolerance to missing data in myocardialperfusion SPET usingOSEM reconstructionrdquo European Journalof Nuclear Medicine and Molecular Imaging vol 31 no 6 pp857ndash861 2004
[33] S R Zakavi A Zonoozi V D Kakhki M Hajizadeh MMom-ennezhad and K Ariana ldquoImage reconstruction using filteredbackprojection and iterative method effect on motion artifactsin myocardial perfusion SPECTrdquo Journal of Nuclear MedicineTechnology vol 34 no 4 pp 220ndash223 2006
[34] KWon E KimMMar et al ldquoIs iterative reconstruction an im-provement over filtered back projection in processing gatedmyocardial perfusion SPECTrdquo The Open Medical ImagingJournal vol 2 pp 17ndash23 2008
[35] A Otte K Audenaert K Peremans K Heeringen and R Dier-ckx Nuclear Medicine in Psychiatry Springer Berlin Germany2004
[36] M Lyra ldquoSingle photon emission tomography (SPECT) and 3Dimages evaluation in nuclear medicinerdquo in Image ProcessingY S Chen Ed InTech 2009 httpwwwintechopencombooksimage-processingsingle-photon-emission-tomography-spect-and-3d-images-evaluation-in-nuclear-medicine
[37] A Seret and J Forthomme ldquoComparison of different types ofcommercial filtered backprojection and ordered-subset expec-tation maximization SPECT reconstruction softwarerdquo Journalof Nuclear Medicine Technology vol 37 no 3 pp 179ndash187 2009
[38] R S Lima D DWatson A R Goode et al ldquoIncremental valueof combined perfusion and function over perfusion alone bygated SPECT myocardial perfusion imaging for detection ofsevere three-vessel coronary artery diseaserdquo Journal of theAmerican College of Cardiology vol 42 no 1 pp 64ndash70 2003
[39] A K Paul andH A Nabi ldquoGatedmyocardial perfusion SPECTbasic principles technical aspects and clinical applicationsrdquoJournal of Nuclear Medicine Technology vol 32 no 4 pp 179ndash187 2004
[40] P Vera A Manrique V Pontvianne A Hitzel R Koningand A Cribier ldquoThallium-gated SPECT in patients with majormyocardial infarction effect of filtering and zooming in com-parison with equilibrium radionuclide imaging and left ven-triculographyrdquo Journal of Nuclear Medicine vol 40 no 4 pp513ndash521 1999
[41] P Y Marie W Djaballah P R Franken et al ldquoOSEM recon-struction associated with temporal Fourier and depth-dependant resolution recovery filtering enhances results fromsestamibi and 201T1 16-Interval Gated SPECTrdquo Journal ofNuclear Medicine vol 46 no 11 pp 1789ndash1795 2005
[42] T Vakhtangandze D O Hall F V Zananiri and M R ReesldquoThe effect of Butterworth and Metz reconstruction filters onvolume and ejection fraction calculations with 99Tcm gatedmyocardial SPECTrdquoBritish Journal of Radiology vol 78 no 932pp 733ndash736 2005
[43] G A Wright M McDade W Martin and I Hutton ldquoQuan-titative gated SPECT the effect of reconstruction filter oncalculated left ventricular ejection fractions and volumesrdquoPhysics in Medicine and Biology vol 47 no 8 pp 99ndash105 2002
[44] N Trayanova ldquoComputational cardiology the heart of thematterrdquo ISRN Cardiology vol 2012 Article ID 269680 15 pages2012
images To choose the optimumfilter for quantitative analysiscontrast signal-to-noise ratio (SNR) and defect size criteriawere analyzed In each of these criteria were given a numberfrom 1 to 20 1 for the worst and 20 for the best contrastand SNR while 1 for the largest defect size and 20 for thesmallest For every filter the final criterion resulted from thetotal sum of the marks of the previous parameters The studyshowed that Parzen filter is inappropriate for heart studyThecutoff frequency of 0325Nq and 05Nq gave the best overallresult for Hanning and Hamming filters respectively ForButterworth filter order 11 and cutoff 045Nq gave the bestimage quality and size accuracy
A determination of the appropriate filter for myocardialSPECT was conducted by Salihin and Zakaria [14] Inthis study a cardiac phantom was filled with 40 120583CimL(0148MBqmL) 99mTc solution The filters functions evalu-ated in this study included Butterworth HammingHanningand Parzen filters From these filters 272 combinations offilter parameters were selected and applied to the projectiondata For the determination of the best filter Tanavar etal [27] method was applied [20] The study suggested thatButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter produced thebest accurate size
The same group [28] has investigated the relationshipbetween the optimum cutoff frequency for Butterworth filterand lung-heart ratio in 99mTc myocardial SPECT For thestudy a cardiac phantom was used and the optimum cutofffrequency and order of Butterworth filter were determinedusing Takavar et al method [27] A linear relationshipbetween cutoff frequency and lung-heart ratio had beenfound which shows that the lung-heart ratio of each patientmust be taken into account in order to choose the optimumcutoff frequency for Butterworth filter
Links et al [20] examined the effect of Wiener filterin myocardial perfusion with 201Tl SPECT The study wasdone in 19 dogs and showed that Wiener filter improves thequantization of regional myocardial perfusion defects
In amyocardial perfusion studywith 99mTc sestamibi theinvestigators explore the effect of different filters on the con-trast of the defected location Calculations showed that max-imum contrast between normal and defected myocardiumcould be obtained using the Metz (FWHM 35ndash45 pixelorders of 8ndash95) Wiener (FWHMs 35ndash4) Butterworth (cut-offs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) [29]
4 IR versus FBP in Cardiac SPECT
Iterative reconstruction (IR) algorithms allow accurate mod-elling of statistical fluctuation (noise) produce accurateimages without streak artifacts as FBP and promise noisesuppression and improved resolution [30]
Themost commonly used IRmethod in SPECT studies isordered-subset expectation maximization (OSEM) Myocar-dial perfusion SPECT images reconstructed with OSEMIR algorithm have a superior quality than those processedwith FBP Perfusion defects anatomic variants and the right
(a) (b)
Figure 5 Comparison of vertical horizontal and short axis slicesof a stress perfusion imaging study reconstructed by FBP (a) and byOSEM (b) algorithm using the Butterworth filter (cutoff frequency03 cmminus1 and power 10) as a processing filter Data acquired byGE Starcam 4000 and reconstructed in Radiation Physics UnitUniversity Aretaieion Hospital Athens Greece 2013
ventricular myocardium are better visualized with OSEMLikewise image contrast is improved thereby better definingthe left ventricular endocardial borders The effect of OSEMon image quality improvement is more intense in lower countdensity studies [31]
Hatton et al [32] in myocardial perfusion SPECT studyshow that OSEM technique demonstrates fewer artifacts andimproves tolerance when projections are missing HoweverOSEM seems to be less tolerant in motion artifacts thanFBP [33] Won et al [34] in 2008 studied the impact of IRon myocardial perfusion imaging in 6 patients The resultsdemonstrate that there was no statistically significant differ-ence in the accuracy of myocardial perfusion interpretationbetween FBP and IR but there were statistically significantdifferences in functional results
A stress perfusion imaging study reconstructed bothby FBP and by OSEM algorithm using the Butterworthfilter is shown in Figure 5 It is believed that in such a casediagnostic information might be easier to obtain throughthe OSEM algorithm This is because corrections for imagedegrading effects such as attenuation scatter and resolutiondegradation as well as corrections for partial volume effectsand missing data are quite straightforward to be included inthe resulting image through iterative techniques [35]
5 Reconstruction and Processing of3D Cardiac SPECT Images
The 3-dimensional (3D) description of an organ and theinformation of an organrsquos surface can be obtained from asequence of 2D slices reconstructed from projections to forma volume image Volume visualization obtains volumetricsigns useful in diagnosis in a more familiar and realistic way
Cardiology Research and Practice 7
Filtering thresholding and gradient are necessary tools inthe production of diagnostic 3D images [36]
Cardiac SPECT provides information with respect to thedetection of myocardial perfusion defects the assessment ofthe pattern of defect reversibility and the overall detectionof coronary artery disease (CAD) There is a relationshipbetween the location and the degree of the stenosis in coro-nary arteries and the observed perfusion on the myocardialscintigraphy using data of 3D surface images ofmyocardiumThis allows us to predict the impact of evolution of thesestenoses to justify a coronarography or to avoid it
51 3-Dimensional Software Filter Application Seret andForthomme [37] have studied types of commercial softwarefor SPECT image processing It was also observed that therewere 2 definitions of the Butterworth filter For a fixed orderand a fixed cutoff frequency one definition led to a lesssmoothing filter which resulted in higher noise levels andsmaller FWHMs However differences in the FWHM weretranslated to differences in contrast only when they exceeded05 mm for the hot rods and 1 mm for the cold rods ofthe used phantom When considering the FWHM and noiselevel more noticeable differences between the workstationswere observed for OSEM reconstruction
All of the software types used in the study [37] behaved asexpected lowering the filter cutoff frequency in FBP resultedin larger FWHMs and in lower noise levels and reducedcontrast increasing the product number of subsets times thenumber of iterations in OSEM resulted in improved contrastand higher noise levels
Nowadays in many cases myocardium diagnosis is reliedon 3D surface shaded images 3D data obtained at stress andat rest of the LV myocardium respectively are analysed andthe deformation of both images is evaluated qualitatively andquantitatively
3D data reconstructed by IR were obtained by the GEVolumetrix software in the GE Xeleris processing systemat stress and rest MPI studies (Figure 6) Butterworth Filter(cutoff frequency 04 cmminus1 power 10) was used in bothreconstructions Chang attenuation correction was applied(coefficient = 01) These data were then used to evaluate theleft ventricle deformation in both stress and rest 3D surfaceimage series If a significant difference is obtained in rest andstress 3D data perfusion the location and the impact of thepathology of left ventricle myocardium are recognized
3D shaded surface display of a patient stress and rest per-fusion angular images (Figure 7) can be reconstructed by FBPor OSEM algorithm and improved usually by Butterworthor Hanning filter 3D reconstruction in studies by Tc99mtetrofosmin may show normal (or abnormal) myocardiumperfusion in apex base andwalls ofmyocardium Transaxialslices are used to be reconstructed and the created 3D volumeimages are displayedThrough base we recognize the cavity ofLV
52 3-Dimensional Reconstruction byMatLab Filters Applica-tion 3D reconstruction was also performed using a specified
(a)
(b)
Figure 6 3D reconstruction at stress (a) and rest (b) by OSEMiterative reconstruction (10 subsets) Butterworth filter (cutoff04Hz power 10 Chang AC coefficient 01) obtained by the GEVolumetrix software (GE Xeleris-2 processing system) The colourscale indicates a high perfusion in white and red regions and a lowerperfusion in the other regions Defected areas are seen on the aboveimage with a darker colour A perfusion recovery of the defects onthe rest images is observed Data acquired by GE Starcam 4000and reconstructed in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
(a)
(b)
Figure 7 Stress (a) and at rest (b) 3D surface angular images offemale myocardium Small defect at posterior-basal wall at stress isimproved almost completely at rest (2 rest defect) threshold value50 of maximum OSEM iterative reconstruction Defect lesionunder stress is recovered in rest condition (seen on the first structurein both above and below image)
MatLab code in order to evaluate the different filters used(Figure 10) and also to compare myocardium volume at restand at stress (Figure 11) In MatLab volume visualizationcan be achieved by constructing a 3D surface plot whichuses the pixel identities for (119909 119910) axes and the pixel valueis transformed into surface plot height and consequentlycolour Apart from that 3D voxel images can be constructedSPECT projections are acquired isocontours are depicted onthem including a number of voxels and finally all of them canbe added in order to create the desirable volume image [17]
8 Cardiology Research and Practice
40
35
30
25
20
15
25 30 35 40 45 50
(a)
34
32
30
28
26
24
22
20
36 38 40 42 44 46 48 50
(b)
Figure 8 Isocontour surfaces for threshold value determination in rest [17] Images obtained in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
40
35
30
25
20
15
30 35 40 45 50 55
(a)
34
32
30
28
26
24
22
20
34 36 38 40 42 44 46 48
(b)
Figure 9 Isocontour surfaces for threshold value determination in stress [17] Images obtained in Radiation Physics Unit UniversityAretaieio hospital Athens Greece 2013
Themethod is illustrated in Figures 8 and 9 for rest and stressconditions respectively
The volume rendered by MatLab is slow enough but sim-ilar to other codesrsquo volume renderings
The volume rendering used in 3D myocardium usedzoom angles of 56 degrees and a focal length in pixels de-pending on the organsrsquo sizeThe size of the reprojection is thesame as the main size of input image
6 4D Gated SPECT Imaging
In some cases SPECT imaging can be gated to the cardiacelectrocardiogram signal allowing data from specific parts ofthe cardiac cycle to be isolated and providing a spatiotem-poral approach (4D) It also allows a combined evaluation ofboth myocardial perfusion and left ventricular (LV) functionin one study which can provide additional information thatperfusion imaging cannot provide alone An example of sucha case are patients suffering from a 3-vessel coronary diseasewhere gated SPECThas been noted to yield significantlymoreabnormal segments than perfusion does alone [38]
As in a regular SPECT acquisition a 120574-camera registersphotons emitted from the object atmultiple projection anglesalong an arc of usually 180 degrees At each projection insteadof one static image several dynamic images are acquired
spanning the length of the cardiac cycle at equal intervalsThe cardiac cycle is marked within the R-R interval whichcorresponds to the end-diastole and is divided in 8-16 equalframes For each frame image data are acquired overmultiplecardiac cycles and stored All data for a specific frame are thenadded together to form an image representing a specific phaseof the cardiac cycle If temporal frames are added togetherthe resulting set of images is equivalent to a standard set ofungated perfusion images
During reconstruction in gated SPECT a significant levelof smoothing is required in comparison to ungated orsummedprojection data because of the relatively poor counts[39] This is done by using appropriate filters Several studieshave been made to establish the most appropriate filters forthis purpose
In a 201Tl gated SPECT study concerning patients withmajor myocardial infarction [40] a Butterworth filter oforder 5 with six cutoff frequencies (013 015 020 025030 and 035 cyclepixel) was successively testedThe reportshowed that filtering affects end diastolic volume (EDV) endsystolic volume (ESV) and left ventricular ejection fraction(LVEF) Marie et al [41] suggested that the best results forcardiac gated SPECT image reconstruction with 201Tl wereachieved using a Butterworth filter with an order of 5 andcutoff frequency 030 cyclespixel
Cardiology Research and Practice 9
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(a)
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(b)
Figure 10 3D volume of a normal myocardium reconstruction is obtained through a specifiedMatLab code in order to compare the differentfilters used Butterworth (a) and Hann (b) filetrs are used Insignificant voxel differences are observed Data acquired at Medical ImagingNuclear Medicine and MatLab algorithm in Radiation Physics Unit Aretaieion Hospital Athens
16
14
12
10
8
6
48
46
44
42
40
38
28 26 24 22 20 18 16
(a)
48
46
44
42
40
38
12
10
8
6
4
25
20
15
(b)
Figure 11 3Dmyocardium processed by aMatLab code in order to compare myocardium volume at rest (left) and at stress (right) (Lyra et al2010) The image does not depict the real volume but the voxelized one (the functional myocardium) Figure is obtained from citation [18]
In 2005 [42] the differences produced by change ofreconstruction filter in calculations of left-ventricular enddiastolic volume (EDV) end systolic volume (ESV) strokevolume (SV) and ejection fraction (LVEF) from 99mTc-sestamibi myocardial gated SPECT studies have been inves-tigated Butterworth order 4 cutoff frequency 025 cyclespixel and Metz order 8 full-width half maximum 40mmwere applied and compared With the Metz filter ratherthan the Butterworth filter left-ventricular EDV and ESVwere significantly larger and the LVEF and SV were notsignificantly changedThe results were consistent to previoussimilar studies [40 43]
7 Discussion
The SPECT filters can greatly affect the quality of clinicalimages Proper filter selection and adequate smoothing helpsthe physician in resultsrsquo interpretation and accurate diagnosis
Several studies on phantoms with respect to the mostappropriate filter for cardiac SPECT have been consideredThe studies showed that for the 3D SPECT reconstructionButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter producesthe best accurate size [20] Maximum contrast betweennormal and defected myocardium could be obtained using
10 Cardiology Research and Practice
the Metz (FWHM 35ndash45 pixel orders of 8ndash95) Wiener(FWHMs 35ndash4) Butterworth (cutoffs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) filters [29] The cutofffrequency of 0325 of Nq gave the best overall result for theHanning filter whereas for the Butterworth filter order 11and cut off of 045Nq gave the best image quality and sizeaccuracy [27]
For the 4DECG-gated SPECT reconstruction best resultswere obtained using a Butterworth filter with an order of 5and cutoff frequency of 030 cyclespixel [41]
As far as the reconstruction technique is concerned using3D OSEM with suitable AC may improve lesion detectabilitydue to the significant improvement of image contrast [35] 3Diterative reconstruction algorithms are likely to replace theFBP technique for many SPECT clinical applications
When a specified 3D reconstruction MatLab code wasused to compare both two chosen filters (Butterworth andHann) andmyocardium volume at rest and at stress accuratediagnostic images were produced
It is expected that further significant improvement inimage quality will be attained which in turn will increasethe confidence of image interpretation The development ofalgorithms for analysis of myocardial 3D images may allowbetter evaluation of small and nontransmural myocardialdefects For the diagnosis and treatment of heart diseasesthe accurate visualisation of the spatial heart shape 3Dvolume of the LV and the heart wall perfusion plays a crucialrole Surface shading is a valuable tool for determining thepresence extent and location of CAD
Further developments in cardiac diagnosis include anew promising tool computational cardiologyThe functionsof the diseased heart and the probable new techniques indiagnosis and treatment can be studied using state-of-the-art whole-heart models of electrophysiology and electrome-chanics A characteristic example of implementing such amodel is ventricular modelling where important aspects ofarrhythmias including dynamic characteristics of ventricu-lar fibrillation can be revealed Performing patient-specificcomputer simulations of the function of the diseased heart foreither diagnostic or treatment purposes could be an excitingnew implementation of computational cardiology [44]
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
References
[1] WHO Global Atlas on Cardiovascular Disease Prevention andControl WHO World Heart Federation World Stroke Organi-zation 2011 httpwwwwhointcardiovascular diseasesen
[2] S Agarwal M G Shlipak H Kramer A Jain and D MHerrington ldquoThe association of chronic kidney disease andmetabolic syndrome with incident cardiovascular events mul-tiethnic study of atherosclerosisrdquo Cardiology Research andPractice vol 2012 Article ID 806102 8 pages 2012
[3] H Jadvar H W Strauss and G M Segall ldquoSPECT and PET inthe evaluation of coronary artery diseaserdquo Radiographics vol19 no 4 pp 915ndash926 1999
[4] K van Laere M Koole I Lemahieu and R Dierckx ldquoImagefiltering in single-photon emission computed tomography Pri-nciples and applicationsrdquo Computerized Medical Imaging andGraphics vol 25 no 2 pp 127ndash133 2001
[5] E G DePuey D S Berman and E V Garcia Cardiac SPECTImaging Raven Press New York NY USA 1995
[6] G Germano ldquoTechnical aspects of myocardial SPECT imag-ingrdquo Journal of Nuclear Medicine vol 42 no 10 pp 1499ndash15072001
[7] S R Cherry J A Sorenson andM E Phelps Physics in NuclearMedicine Saunders Philadelphia Pa USA 2003
[8] J Qi and R M Leahy ldquoIterative reconstruction techniques inemission computed tomographyrdquo Physics in Medicine and Bi-ology vol 51 pp R541ndashR578 2006
[9] C Lee-Tzuu ldquoA method for attenuation correction in radionu-clide computed tomographyrdquo IEEE Transactions on NuclearScience vol 25 no 1 pp 638ndash643 1978
[10] P P Bruyant ldquoAnalytic and iterative reconstruction algorithmsin SPECTrdquo Journal of NuclearMedicine vol 43 no 10 pp 1343ndash1358 2002
[11] M Lyra and A Ploussi ldquoFiltering in SPECT image reconstruc-tionrdquo International Journal of Biomedical Imaging vol 2011Article ID 693795 14 pages 2011
[12] M W Groch and W D Erwin ldquoSPECT in the year 2000 basicprinciplesrdquo Journal of Nuclear Medicine Technology vol 28 no4 pp 233ndash244 2000
[13] M M Khalil Basic Sciences of Nuclear Medicine Springer Be-rlin Germany 2010
[14] M N Salihin and A Zakaria ldquoDetermination of the optimumfilter for qualitative and quantitative 99mTc myocardial SPECTimagingrdquo Iranian Journal of Radiation Research vol 6 no 4 pp173ndash182 2009
[15] A Sadremomtaz and P Taherparvar ldquoThe influence of filters onthe SPECT image of Carlson phantomrdquo Journal of BiomedicalScience and Engineering vol 6 pp 291ndash297 2013
[16] Society of Nuclear Medicine and Molecular Imaging (2012)Phantoms Cardiac SPECT simulator 2012 httpinteractivesnmorgindexcfmPageID=11666
[17] S SynefiaM SotiropoulosM Argyrou et al ldquo3D SPECTmyo-cardial volume estimation increases the reliability of perfusiondiagnosisrdquo e-Journal of Science and Technology In press
[18] M Lyra M Sotiropoulos N Lagopati and M GavrillelildquoQuantification of myocardial perfusion in 3D SPECT images-stressrest volume differences 3D myocardium images quan-tificationrdquo in Proceedings of the IEEE International Conferenceon Imaging Systems and Techniques (IST rsquo10) pp 31ndash35 Thessa-loniki Greece July 2010
[19] M A King S J Glick B C Penney R B Schwinger and PW Doherty ldquoInteractive visual optimization of SPECT prerec-onstruction filteringrdquo Journal of Nuclear Medicine vol 28 no 7pp 1192ndash1198 1987
[20] J M Links R W Jeremy S M Dyer T L Frank and L CBecker ldquoWiener filtering improves quantification of regionalmyocardial perfusion with thallium-201 SPECTrdquo Journal ofNuclear Medicine vol 31 no 7 pp 1230ndash1236 1990
[21] G V Heller A Mann and R C Hendel Nuclear CardiologyTechnical Applications McGraw-Hill New York NY USA2009
Cardiology Research and Practice 11
[22] B Tasdemir T Balci B Demirel I Karaca A Aydin and ZKoc ldquoComparison of myocardial perfusion scintigraphy andcomputed tomography (CT) angiography based on conven-tional coronary angiographyrdquo Natural Science vol 4 pp 976ndash982 2012
[23] S R Underwood C Anagnostopoulos M Cerqueira et alldquoMyocardial perfusion scintigraphy the evidencerdquo EuropeanJournal of Nuclear Medicine and Molecular Imaging vol 31 no2 pp 261ndash291 2004
[24] Y H Lue and F J Wackers Cardiovascular Imaging MansonPublishing 2010
[25] E G DePuey Imaging Guidelines for Nuclear Cardiology Proce-dures The American Society of Nuclear Cardiology 2006
[26] R A Carlson and J T Colvin ldquoFluke Biomedical Nuclear Asso-ciates 76ndash823 76ndash824 amp 76ndash825 PETSPECT Phantom SourceTank Phantom Inserts and Cardiac Insertrdquo 2006 httpwwwflukebiomedicalcomBiomedicalusenNuclear-MedicineQual-ity-Control-Phantoms76-825htmPID=55292
[27] A Takavar G Shamsipour M Sohrabi and M Eftekhari ldquoDe-termination of optimumfilter inmyocardial SPECT a phantomstudyrdquo Iranian Journal of Radiation Research vol 4 no 1 pp205ndash210 2004
[28] M N Salihin and A Zakaria ldquoRelationship between the opti-mum cut off frequency for Butterworth filter and lung-heartratio in 99mTcmyocardial SPECTrdquo Iranian Journal of RadiationResearch vol 8 no 1 pp 17ndash24 2010
[29] H Rajabi A Rajabi N Yaghoobi H Firouzabady and F Rust-gou ldquoDetermination of the optimum filter function for Tc99m-sestamibi myocardial perfusion SPECT imagingrdquo Indian Jour-nal of Nuclear Medicine vol 20 no 3 pp 77ndash82 2005
[30] S Vandenberghe Y DrsquoAsseler R van de Walle et al ldquoIterativereconstruction algorithms in nuclear medicinerdquo ComputerizedMedical Imaging and Graphics vol 25 no 2 pp 105ndash111 2001
[31] E G DePuey ldquoAdvances in SPECT camera software and hard-ware currently available and new on the horizonrdquo Journal ofNuclear Cardiology vol 19 no 3 pp 551ndash581 2012
[32] R L Hatton B F Hutton S Angelides K K L Choong andG Larcos ldquoImproved tolerance to missing data in myocardialperfusion SPET usingOSEM reconstructionrdquo European Journalof Nuclear Medicine and Molecular Imaging vol 31 no 6 pp857ndash861 2004
[33] S R Zakavi A Zonoozi V D Kakhki M Hajizadeh MMom-ennezhad and K Ariana ldquoImage reconstruction using filteredbackprojection and iterative method effect on motion artifactsin myocardial perfusion SPECTrdquo Journal of Nuclear MedicineTechnology vol 34 no 4 pp 220ndash223 2006
[34] KWon E KimMMar et al ldquoIs iterative reconstruction an im-provement over filtered back projection in processing gatedmyocardial perfusion SPECTrdquo The Open Medical ImagingJournal vol 2 pp 17ndash23 2008
[35] A Otte K Audenaert K Peremans K Heeringen and R Dier-ckx Nuclear Medicine in Psychiatry Springer Berlin Germany2004
[36] M Lyra ldquoSingle photon emission tomography (SPECT) and 3Dimages evaluation in nuclear medicinerdquo in Image ProcessingY S Chen Ed InTech 2009 httpwwwintechopencombooksimage-processingsingle-photon-emission-tomography-spect-and-3d-images-evaluation-in-nuclear-medicine
[37] A Seret and J Forthomme ldquoComparison of different types ofcommercial filtered backprojection and ordered-subset expec-tation maximization SPECT reconstruction softwarerdquo Journalof Nuclear Medicine Technology vol 37 no 3 pp 179ndash187 2009
[38] R S Lima D DWatson A R Goode et al ldquoIncremental valueof combined perfusion and function over perfusion alone bygated SPECT myocardial perfusion imaging for detection ofsevere three-vessel coronary artery diseaserdquo Journal of theAmerican College of Cardiology vol 42 no 1 pp 64ndash70 2003
[39] A K Paul andH A Nabi ldquoGatedmyocardial perfusion SPECTbasic principles technical aspects and clinical applicationsrdquoJournal of Nuclear Medicine Technology vol 32 no 4 pp 179ndash187 2004
[40] P Vera A Manrique V Pontvianne A Hitzel R Koningand A Cribier ldquoThallium-gated SPECT in patients with majormyocardial infarction effect of filtering and zooming in com-parison with equilibrium radionuclide imaging and left ven-triculographyrdquo Journal of Nuclear Medicine vol 40 no 4 pp513ndash521 1999
[41] P Y Marie W Djaballah P R Franken et al ldquoOSEM recon-struction associated with temporal Fourier and depth-dependant resolution recovery filtering enhances results fromsestamibi and 201T1 16-Interval Gated SPECTrdquo Journal ofNuclear Medicine vol 46 no 11 pp 1789ndash1795 2005
[42] T Vakhtangandze D O Hall F V Zananiri and M R ReesldquoThe effect of Butterworth and Metz reconstruction filters onvolume and ejection fraction calculations with 99Tcm gatedmyocardial SPECTrdquoBritish Journal of Radiology vol 78 no 932pp 733ndash736 2005
[43] G A Wright M McDade W Martin and I Hutton ldquoQuan-titative gated SPECT the effect of reconstruction filter oncalculated left ventricular ejection fractions and volumesrdquoPhysics in Medicine and Biology vol 47 no 8 pp 99ndash105 2002
[44] N Trayanova ldquoComputational cardiology the heart of thematterrdquo ISRN Cardiology vol 2012 Article ID 269680 15 pages2012
Filtering thresholding and gradient are necessary tools inthe production of diagnostic 3D images [36]
Cardiac SPECT provides information with respect to thedetection of myocardial perfusion defects the assessment ofthe pattern of defect reversibility and the overall detectionof coronary artery disease (CAD) There is a relationshipbetween the location and the degree of the stenosis in coro-nary arteries and the observed perfusion on the myocardialscintigraphy using data of 3D surface images ofmyocardiumThis allows us to predict the impact of evolution of thesestenoses to justify a coronarography or to avoid it
51 3-Dimensional Software Filter Application Seret andForthomme [37] have studied types of commercial softwarefor SPECT image processing It was also observed that therewere 2 definitions of the Butterworth filter For a fixed orderand a fixed cutoff frequency one definition led to a lesssmoothing filter which resulted in higher noise levels andsmaller FWHMs However differences in the FWHM weretranslated to differences in contrast only when they exceeded05 mm for the hot rods and 1 mm for the cold rods ofthe used phantom When considering the FWHM and noiselevel more noticeable differences between the workstationswere observed for OSEM reconstruction
All of the software types used in the study [37] behaved asexpected lowering the filter cutoff frequency in FBP resultedin larger FWHMs and in lower noise levels and reducedcontrast increasing the product number of subsets times thenumber of iterations in OSEM resulted in improved contrastand higher noise levels
Nowadays in many cases myocardium diagnosis is reliedon 3D surface shaded images 3D data obtained at stress andat rest of the LV myocardium respectively are analysed andthe deformation of both images is evaluated qualitatively andquantitatively
3D data reconstructed by IR were obtained by the GEVolumetrix software in the GE Xeleris processing systemat stress and rest MPI studies (Figure 6) Butterworth Filter(cutoff frequency 04 cmminus1 power 10) was used in bothreconstructions Chang attenuation correction was applied(coefficient = 01) These data were then used to evaluate theleft ventricle deformation in both stress and rest 3D surfaceimage series If a significant difference is obtained in rest andstress 3D data perfusion the location and the impact of thepathology of left ventricle myocardium are recognized
3D shaded surface display of a patient stress and rest per-fusion angular images (Figure 7) can be reconstructed by FBPor OSEM algorithm and improved usually by Butterworthor Hanning filter 3D reconstruction in studies by Tc99mtetrofosmin may show normal (or abnormal) myocardiumperfusion in apex base andwalls ofmyocardium Transaxialslices are used to be reconstructed and the created 3D volumeimages are displayedThrough base we recognize the cavity ofLV
52 3-Dimensional Reconstruction byMatLab Filters Applica-tion 3D reconstruction was also performed using a specified
(a)
(b)
Figure 6 3D reconstruction at stress (a) and rest (b) by OSEMiterative reconstruction (10 subsets) Butterworth filter (cutoff04Hz power 10 Chang AC coefficient 01) obtained by the GEVolumetrix software (GE Xeleris-2 processing system) The colourscale indicates a high perfusion in white and red regions and a lowerperfusion in the other regions Defected areas are seen on the aboveimage with a darker colour A perfusion recovery of the defects onthe rest images is observed Data acquired by GE Starcam 4000and reconstructed in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
(a)
(b)
Figure 7 Stress (a) and at rest (b) 3D surface angular images offemale myocardium Small defect at posterior-basal wall at stress isimproved almost completely at rest (2 rest defect) threshold value50 of maximum OSEM iterative reconstruction Defect lesionunder stress is recovered in rest condition (seen on the first structurein both above and below image)
MatLab code in order to evaluate the different filters used(Figure 10) and also to compare myocardium volume at restand at stress (Figure 11) In MatLab volume visualizationcan be achieved by constructing a 3D surface plot whichuses the pixel identities for (119909 119910) axes and the pixel valueis transformed into surface plot height and consequentlycolour Apart from that 3D voxel images can be constructedSPECT projections are acquired isocontours are depicted onthem including a number of voxels and finally all of them canbe added in order to create the desirable volume image [17]
8 Cardiology Research and Practice
40
35
30
25
20
15
25 30 35 40 45 50
(a)
34
32
30
28
26
24
22
20
36 38 40 42 44 46 48 50
(b)
Figure 8 Isocontour surfaces for threshold value determination in rest [17] Images obtained in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
40
35
30
25
20
15
30 35 40 45 50 55
(a)
34
32
30
28
26
24
22
20
34 36 38 40 42 44 46 48
(b)
Figure 9 Isocontour surfaces for threshold value determination in stress [17] Images obtained in Radiation Physics Unit UniversityAretaieio hospital Athens Greece 2013
Themethod is illustrated in Figures 8 and 9 for rest and stressconditions respectively
The volume rendered by MatLab is slow enough but sim-ilar to other codesrsquo volume renderings
The volume rendering used in 3D myocardium usedzoom angles of 56 degrees and a focal length in pixels de-pending on the organsrsquo sizeThe size of the reprojection is thesame as the main size of input image
6 4D Gated SPECT Imaging
In some cases SPECT imaging can be gated to the cardiacelectrocardiogram signal allowing data from specific parts ofthe cardiac cycle to be isolated and providing a spatiotem-poral approach (4D) It also allows a combined evaluation ofboth myocardial perfusion and left ventricular (LV) functionin one study which can provide additional information thatperfusion imaging cannot provide alone An example of sucha case are patients suffering from a 3-vessel coronary diseasewhere gated SPECThas been noted to yield significantlymoreabnormal segments than perfusion does alone [38]
As in a regular SPECT acquisition a 120574-camera registersphotons emitted from the object atmultiple projection anglesalong an arc of usually 180 degrees At each projection insteadof one static image several dynamic images are acquired
spanning the length of the cardiac cycle at equal intervalsThe cardiac cycle is marked within the R-R interval whichcorresponds to the end-diastole and is divided in 8-16 equalframes For each frame image data are acquired overmultiplecardiac cycles and stored All data for a specific frame are thenadded together to form an image representing a specific phaseof the cardiac cycle If temporal frames are added togetherthe resulting set of images is equivalent to a standard set ofungated perfusion images
During reconstruction in gated SPECT a significant levelof smoothing is required in comparison to ungated orsummedprojection data because of the relatively poor counts[39] This is done by using appropriate filters Several studieshave been made to establish the most appropriate filters forthis purpose
In a 201Tl gated SPECT study concerning patients withmajor myocardial infarction [40] a Butterworth filter oforder 5 with six cutoff frequencies (013 015 020 025030 and 035 cyclepixel) was successively testedThe reportshowed that filtering affects end diastolic volume (EDV) endsystolic volume (ESV) and left ventricular ejection fraction(LVEF) Marie et al [41] suggested that the best results forcardiac gated SPECT image reconstruction with 201Tl wereachieved using a Butterworth filter with an order of 5 andcutoff frequency 030 cyclespixel
Cardiology Research and Practice 9
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(a)
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(b)
Figure 10 3D volume of a normal myocardium reconstruction is obtained through a specifiedMatLab code in order to compare the differentfilters used Butterworth (a) and Hann (b) filetrs are used Insignificant voxel differences are observed Data acquired at Medical ImagingNuclear Medicine and MatLab algorithm in Radiation Physics Unit Aretaieion Hospital Athens
16
14
12
10
8
6
48
46
44
42
40
38
28 26 24 22 20 18 16
(a)
48
46
44
42
40
38
12
10
8
6
4
25
20
15
(b)
Figure 11 3Dmyocardium processed by aMatLab code in order to compare myocardium volume at rest (left) and at stress (right) (Lyra et al2010) The image does not depict the real volume but the voxelized one (the functional myocardium) Figure is obtained from citation [18]
In 2005 [42] the differences produced by change ofreconstruction filter in calculations of left-ventricular enddiastolic volume (EDV) end systolic volume (ESV) strokevolume (SV) and ejection fraction (LVEF) from 99mTc-sestamibi myocardial gated SPECT studies have been inves-tigated Butterworth order 4 cutoff frequency 025 cyclespixel and Metz order 8 full-width half maximum 40mmwere applied and compared With the Metz filter ratherthan the Butterworth filter left-ventricular EDV and ESVwere significantly larger and the LVEF and SV were notsignificantly changedThe results were consistent to previoussimilar studies [40 43]
7 Discussion
The SPECT filters can greatly affect the quality of clinicalimages Proper filter selection and adequate smoothing helpsthe physician in resultsrsquo interpretation and accurate diagnosis
Several studies on phantoms with respect to the mostappropriate filter for cardiac SPECT have been consideredThe studies showed that for the 3D SPECT reconstructionButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter producesthe best accurate size [20] Maximum contrast betweennormal and defected myocardium could be obtained using
10 Cardiology Research and Practice
the Metz (FWHM 35ndash45 pixel orders of 8ndash95) Wiener(FWHMs 35ndash4) Butterworth (cutoffs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) filters [29] The cutofffrequency of 0325 of Nq gave the best overall result for theHanning filter whereas for the Butterworth filter order 11and cut off of 045Nq gave the best image quality and sizeaccuracy [27]
For the 4DECG-gated SPECT reconstruction best resultswere obtained using a Butterworth filter with an order of 5and cutoff frequency of 030 cyclespixel [41]
As far as the reconstruction technique is concerned using3D OSEM with suitable AC may improve lesion detectabilitydue to the significant improvement of image contrast [35] 3Diterative reconstruction algorithms are likely to replace theFBP technique for many SPECT clinical applications
When a specified 3D reconstruction MatLab code wasused to compare both two chosen filters (Butterworth andHann) andmyocardium volume at rest and at stress accuratediagnostic images were produced
It is expected that further significant improvement inimage quality will be attained which in turn will increasethe confidence of image interpretation The development ofalgorithms for analysis of myocardial 3D images may allowbetter evaluation of small and nontransmural myocardialdefects For the diagnosis and treatment of heart diseasesthe accurate visualisation of the spatial heart shape 3Dvolume of the LV and the heart wall perfusion plays a crucialrole Surface shading is a valuable tool for determining thepresence extent and location of CAD
Further developments in cardiac diagnosis include anew promising tool computational cardiologyThe functionsof the diseased heart and the probable new techniques indiagnosis and treatment can be studied using state-of-the-art whole-heart models of electrophysiology and electrome-chanics A characteristic example of implementing such amodel is ventricular modelling where important aspects ofarrhythmias including dynamic characteristics of ventricu-lar fibrillation can be revealed Performing patient-specificcomputer simulations of the function of the diseased heart foreither diagnostic or treatment purposes could be an excitingnew implementation of computational cardiology [44]
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
References
[1] WHO Global Atlas on Cardiovascular Disease Prevention andControl WHO World Heart Federation World Stroke Organi-zation 2011 httpwwwwhointcardiovascular diseasesen
[2] S Agarwal M G Shlipak H Kramer A Jain and D MHerrington ldquoThe association of chronic kidney disease andmetabolic syndrome with incident cardiovascular events mul-tiethnic study of atherosclerosisrdquo Cardiology Research andPractice vol 2012 Article ID 806102 8 pages 2012
[3] H Jadvar H W Strauss and G M Segall ldquoSPECT and PET inthe evaluation of coronary artery diseaserdquo Radiographics vol19 no 4 pp 915ndash926 1999
[4] K van Laere M Koole I Lemahieu and R Dierckx ldquoImagefiltering in single-photon emission computed tomography Pri-nciples and applicationsrdquo Computerized Medical Imaging andGraphics vol 25 no 2 pp 127ndash133 2001
[5] E G DePuey D S Berman and E V Garcia Cardiac SPECTImaging Raven Press New York NY USA 1995
[6] G Germano ldquoTechnical aspects of myocardial SPECT imag-ingrdquo Journal of Nuclear Medicine vol 42 no 10 pp 1499ndash15072001
[7] S R Cherry J A Sorenson andM E Phelps Physics in NuclearMedicine Saunders Philadelphia Pa USA 2003
[8] J Qi and R M Leahy ldquoIterative reconstruction techniques inemission computed tomographyrdquo Physics in Medicine and Bi-ology vol 51 pp R541ndashR578 2006
[9] C Lee-Tzuu ldquoA method for attenuation correction in radionu-clide computed tomographyrdquo IEEE Transactions on NuclearScience vol 25 no 1 pp 638ndash643 1978
[10] P P Bruyant ldquoAnalytic and iterative reconstruction algorithmsin SPECTrdquo Journal of NuclearMedicine vol 43 no 10 pp 1343ndash1358 2002
[11] M Lyra and A Ploussi ldquoFiltering in SPECT image reconstruc-tionrdquo International Journal of Biomedical Imaging vol 2011Article ID 693795 14 pages 2011
[12] M W Groch and W D Erwin ldquoSPECT in the year 2000 basicprinciplesrdquo Journal of Nuclear Medicine Technology vol 28 no4 pp 233ndash244 2000
[13] M M Khalil Basic Sciences of Nuclear Medicine Springer Be-rlin Germany 2010
[14] M N Salihin and A Zakaria ldquoDetermination of the optimumfilter for qualitative and quantitative 99mTc myocardial SPECTimagingrdquo Iranian Journal of Radiation Research vol 6 no 4 pp173ndash182 2009
[15] A Sadremomtaz and P Taherparvar ldquoThe influence of filters onthe SPECT image of Carlson phantomrdquo Journal of BiomedicalScience and Engineering vol 6 pp 291ndash297 2013
[16] Society of Nuclear Medicine and Molecular Imaging (2012)Phantoms Cardiac SPECT simulator 2012 httpinteractivesnmorgindexcfmPageID=11666
[17] S SynefiaM SotiropoulosM Argyrou et al ldquo3D SPECTmyo-cardial volume estimation increases the reliability of perfusiondiagnosisrdquo e-Journal of Science and Technology In press
[18] M Lyra M Sotiropoulos N Lagopati and M GavrillelildquoQuantification of myocardial perfusion in 3D SPECT images-stressrest volume differences 3D myocardium images quan-tificationrdquo in Proceedings of the IEEE International Conferenceon Imaging Systems and Techniques (IST rsquo10) pp 31ndash35 Thessa-loniki Greece July 2010
[19] M A King S J Glick B C Penney R B Schwinger and PW Doherty ldquoInteractive visual optimization of SPECT prerec-onstruction filteringrdquo Journal of Nuclear Medicine vol 28 no 7pp 1192ndash1198 1987
[20] J M Links R W Jeremy S M Dyer T L Frank and L CBecker ldquoWiener filtering improves quantification of regionalmyocardial perfusion with thallium-201 SPECTrdquo Journal ofNuclear Medicine vol 31 no 7 pp 1230ndash1236 1990
[21] G V Heller A Mann and R C Hendel Nuclear CardiologyTechnical Applications McGraw-Hill New York NY USA2009
Cardiology Research and Practice 11
[22] B Tasdemir T Balci B Demirel I Karaca A Aydin and ZKoc ldquoComparison of myocardial perfusion scintigraphy andcomputed tomography (CT) angiography based on conven-tional coronary angiographyrdquo Natural Science vol 4 pp 976ndash982 2012
[23] S R Underwood C Anagnostopoulos M Cerqueira et alldquoMyocardial perfusion scintigraphy the evidencerdquo EuropeanJournal of Nuclear Medicine and Molecular Imaging vol 31 no2 pp 261ndash291 2004
[24] Y H Lue and F J Wackers Cardiovascular Imaging MansonPublishing 2010
[25] E G DePuey Imaging Guidelines for Nuclear Cardiology Proce-dures The American Society of Nuclear Cardiology 2006
[26] R A Carlson and J T Colvin ldquoFluke Biomedical Nuclear Asso-ciates 76ndash823 76ndash824 amp 76ndash825 PETSPECT Phantom SourceTank Phantom Inserts and Cardiac Insertrdquo 2006 httpwwwflukebiomedicalcomBiomedicalusenNuclear-MedicineQual-ity-Control-Phantoms76-825htmPID=55292
[27] A Takavar G Shamsipour M Sohrabi and M Eftekhari ldquoDe-termination of optimumfilter inmyocardial SPECT a phantomstudyrdquo Iranian Journal of Radiation Research vol 4 no 1 pp205ndash210 2004
[28] M N Salihin and A Zakaria ldquoRelationship between the opti-mum cut off frequency for Butterworth filter and lung-heartratio in 99mTcmyocardial SPECTrdquo Iranian Journal of RadiationResearch vol 8 no 1 pp 17ndash24 2010
[29] H Rajabi A Rajabi N Yaghoobi H Firouzabady and F Rust-gou ldquoDetermination of the optimum filter function for Tc99m-sestamibi myocardial perfusion SPECT imagingrdquo Indian Jour-nal of Nuclear Medicine vol 20 no 3 pp 77ndash82 2005
[30] S Vandenberghe Y DrsquoAsseler R van de Walle et al ldquoIterativereconstruction algorithms in nuclear medicinerdquo ComputerizedMedical Imaging and Graphics vol 25 no 2 pp 105ndash111 2001
[31] E G DePuey ldquoAdvances in SPECT camera software and hard-ware currently available and new on the horizonrdquo Journal ofNuclear Cardiology vol 19 no 3 pp 551ndash581 2012
[32] R L Hatton B F Hutton S Angelides K K L Choong andG Larcos ldquoImproved tolerance to missing data in myocardialperfusion SPET usingOSEM reconstructionrdquo European Journalof Nuclear Medicine and Molecular Imaging vol 31 no 6 pp857ndash861 2004
[33] S R Zakavi A Zonoozi V D Kakhki M Hajizadeh MMom-ennezhad and K Ariana ldquoImage reconstruction using filteredbackprojection and iterative method effect on motion artifactsin myocardial perfusion SPECTrdquo Journal of Nuclear MedicineTechnology vol 34 no 4 pp 220ndash223 2006
[34] KWon E KimMMar et al ldquoIs iterative reconstruction an im-provement over filtered back projection in processing gatedmyocardial perfusion SPECTrdquo The Open Medical ImagingJournal vol 2 pp 17ndash23 2008
[35] A Otte K Audenaert K Peremans K Heeringen and R Dier-ckx Nuclear Medicine in Psychiatry Springer Berlin Germany2004
[36] M Lyra ldquoSingle photon emission tomography (SPECT) and 3Dimages evaluation in nuclear medicinerdquo in Image ProcessingY S Chen Ed InTech 2009 httpwwwintechopencombooksimage-processingsingle-photon-emission-tomography-spect-and-3d-images-evaluation-in-nuclear-medicine
[37] A Seret and J Forthomme ldquoComparison of different types ofcommercial filtered backprojection and ordered-subset expec-tation maximization SPECT reconstruction softwarerdquo Journalof Nuclear Medicine Technology vol 37 no 3 pp 179ndash187 2009
[38] R S Lima D DWatson A R Goode et al ldquoIncremental valueof combined perfusion and function over perfusion alone bygated SPECT myocardial perfusion imaging for detection ofsevere three-vessel coronary artery diseaserdquo Journal of theAmerican College of Cardiology vol 42 no 1 pp 64ndash70 2003
[39] A K Paul andH A Nabi ldquoGatedmyocardial perfusion SPECTbasic principles technical aspects and clinical applicationsrdquoJournal of Nuclear Medicine Technology vol 32 no 4 pp 179ndash187 2004
[40] P Vera A Manrique V Pontvianne A Hitzel R Koningand A Cribier ldquoThallium-gated SPECT in patients with majormyocardial infarction effect of filtering and zooming in com-parison with equilibrium radionuclide imaging and left ven-triculographyrdquo Journal of Nuclear Medicine vol 40 no 4 pp513ndash521 1999
[41] P Y Marie W Djaballah P R Franken et al ldquoOSEM recon-struction associated with temporal Fourier and depth-dependant resolution recovery filtering enhances results fromsestamibi and 201T1 16-Interval Gated SPECTrdquo Journal ofNuclear Medicine vol 46 no 11 pp 1789ndash1795 2005
[42] T Vakhtangandze D O Hall F V Zananiri and M R ReesldquoThe effect of Butterworth and Metz reconstruction filters onvolume and ejection fraction calculations with 99Tcm gatedmyocardial SPECTrdquoBritish Journal of Radiology vol 78 no 932pp 733ndash736 2005
[43] G A Wright M McDade W Martin and I Hutton ldquoQuan-titative gated SPECT the effect of reconstruction filter oncalculated left ventricular ejection fractions and volumesrdquoPhysics in Medicine and Biology vol 47 no 8 pp 99ndash105 2002
[44] N Trayanova ldquoComputational cardiology the heart of thematterrdquo ISRN Cardiology vol 2012 Article ID 269680 15 pages2012
Figure 8 Isocontour surfaces for threshold value determination in rest [17] Images obtained in Radiation Physics Unit University Aretaieiohospital Athens Greece 2013
40
35
30
25
20
15
30 35 40 45 50 55
(a)
34
32
30
28
26
24
22
20
34 36 38 40 42 44 46 48
(b)
Figure 9 Isocontour surfaces for threshold value determination in stress [17] Images obtained in Radiation Physics Unit UniversityAretaieio hospital Athens Greece 2013
Themethod is illustrated in Figures 8 and 9 for rest and stressconditions respectively
The volume rendered by MatLab is slow enough but sim-ilar to other codesrsquo volume renderings
The volume rendering used in 3D myocardium usedzoom angles of 56 degrees and a focal length in pixels de-pending on the organsrsquo sizeThe size of the reprojection is thesame as the main size of input image
6 4D Gated SPECT Imaging
In some cases SPECT imaging can be gated to the cardiacelectrocardiogram signal allowing data from specific parts ofthe cardiac cycle to be isolated and providing a spatiotem-poral approach (4D) It also allows a combined evaluation ofboth myocardial perfusion and left ventricular (LV) functionin one study which can provide additional information thatperfusion imaging cannot provide alone An example of sucha case are patients suffering from a 3-vessel coronary diseasewhere gated SPECThas been noted to yield significantlymoreabnormal segments than perfusion does alone [38]
As in a regular SPECT acquisition a 120574-camera registersphotons emitted from the object atmultiple projection anglesalong an arc of usually 180 degrees At each projection insteadof one static image several dynamic images are acquired
spanning the length of the cardiac cycle at equal intervalsThe cardiac cycle is marked within the R-R interval whichcorresponds to the end-diastole and is divided in 8-16 equalframes For each frame image data are acquired overmultiplecardiac cycles and stored All data for a specific frame are thenadded together to form an image representing a specific phaseof the cardiac cycle If temporal frames are added togetherthe resulting set of images is equivalent to a standard set ofungated perfusion images
During reconstruction in gated SPECT a significant levelof smoothing is required in comparison to ungated orsummedprojection data because of the relatively poor counts[39] This is done by using appropriate filters Several studieshave been made to establish the most appropriate filters forthis purpose
In a 201Tl gated SPECT study concerning patients withmajor myocardial infarction [40] a Butterworth filter oforder 5 with six cutoff frequencies (013 015 020 025030 and 035 cyclepixel) was successively testedThe reportshowed that filtering affects end diastolic volume (EDV) endsystolic volume (ESV) and left ventricular ejection fraction(LVEF) Marie et al [41] suggested that the best results forcardiac gated SPECT image reconstruction with 201Tl wereachieved using a Butterworth filter with an order of 5 andcutoff frequency 030 cyclespixel
Cardiology Research and Practice 9
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(a)
18
16
14
12
10
8
6
4
2
30 28 26 24 22 20 18 16 14 1230
40
50
(b)
Figure 10 3D volume of a normal myocardium reconstruction is obtained through a specifiedMatLab code in order to compare the differentfilters used Butterworth (a) and Hann (b) filetrs are used Insignificant voxel differences are observed Data acquired at Medical ImagingNuclear Medicine and MatLab algorithm in Radiation Physics Unit Aretaieion Hospital Athens
16
14
12
10
8
6
48
46
44
42
40
38
28 26 24 22 20 18 16
(a)
48
46
44
42
40
38
12
10
8
6
4
25
20
15
(b)
Figure 11 3Dmyocardium processed by aMatLab code in order to compare myocardium volume at rest (left) and at stress (right) (Lyra et al2010) The image does not depict the real volume but the voxelized one (the functional myocardium) Figure is obtained from citation [18]
In 2005 [42] the differences produced by change ofreconstruction filter in calculations of left-ventricular enddiastolic volume (EDV) end systolic volume (ESV) strokevolume (SV) and ejection fraction (LVEF) from 99mTc-sestamibi myocardial gated SPECT studies have been inves-tigated Butterworth order 4 cutoff frequency 025 cyclespixel and Metz order 8 full-width half maximum 40mmwere applied and compared With the Metz filter ratherthan the Butterworth filter left-ventricular EDV and ESVwere significantly larger and the LVEF and SV were notsignificantly changedThe results were consistent to previoussimilar studies [40 43]
7 Discussion
The SPECT filters can greatly affect the quality of clinicalimages Proper filter selection and adequate smoothing helpsthe physician in resultsrsquo interpretation and accurate diagnosis
Several studies on phantoms with respect to the mostappropriate filter for cardiac SPECT have been consideredThe studies showed that for the 3D SPECT reconstructionButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter producesthe best accurate size [20] Maximum contrast betweennormal and defected myocardium could be obtained using
10 Cardiology Research and Practice
the Metz (FWHM 35ndash45 pixel orders of 8ndash95) Wiener(FWHMs 35ndash4) Butterworth (cutoffs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) filters [29] The cutofffrequency of 0325 of Nq gave the best overall result for theHanning filter whereas for the Butterworth filter order 11and cut off of 045Nq gave the best image quality and sizeaccuracy [27]
For the 4DECG-gated SPECT reconstruction best resultswere obtained using a Butterworth filter with an order of 5and cutoff frequency of 030 cyclespixel [41]
As far as the reconstruction technique is concerned using3D OSEM with suitable AC may improve lesion detectabilitydue to the significant improvement of image contrast [35] 3Diterative reconstruction algorithms are likely to replace theFBP technique for many SPECT clinical applications
When a specified 3D reconstruction MatLab code wasused to compare both two chosen filters (Butterworth andHann) andmyocardium volume at rest and at stress accuratediagnostic images were produced
It is expected that further significant improvement inimage quality will be attained which in turn will increasethe confidence of image interpretation The development ofalgorithms for analysis of myocardial 3D images may allowbetter evaluation of small and nontransmural myocardialdefects For the diagnosis and treatment of heart diseasesthe accurate visualisation of the spatial heart shape 3Dvolume of the LV and the heart wall perfusion plays a crucialrole Surface shading is a valuable tool for determining thepresence extent and location of CAD
Further developments in cardiac diagnosis include anew promising tool computational cardiologyThe functionsof the diseased heart and the probable new techniques indiagnosis and treatment can be studied using state-of-the-art whole-heart models of electrophysiology and electrome-chanics A characteristic example of implementing such amodel is ventricular modelling where important aspects ofarrhythmias including dynamic characteristics of ventricu-lar fibrillation can be revealed Performing patient-specificcomputer simulations of the function of the diseased heart foreither diagnostic or treatment purposes could be an excitingnew implementation of computational cardiology [44]
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
References
[1] WHO Global Atlas on Cardiovascular Disease Prevention andControl WHO World Heart Federation World Stroke Organi-zation 2011 httpwwwwhointcardiovascular diseasesen
[2] S Agarwal M G Shlipak H Kramer A Jain and D MHerrington ldquoThe association of chronic kidney disease andmetabolic syndrome with incident cardiovascular events mul-tiethnic study of atherosclerosisrdquo Cardiology Research andPractice vol 2012 Article ID 806102 8 pages 2012
[3] H Jadvar H W Strauss and G M Segall ldquoSPECT and PET inthe evaluation of coronary artery diseaserdquo Radiographics vol19 no 4 pp 915ndash926 1999
[4] K van Laere M Koole I Lemahieu and R Dierckx ldquoImagefiltering in single-photon emission computed tomography Pri-nciples and applicationsrdquo Computerized Medical Imaging andGraphics vol 25 no 2 pp 127ndash133 2001
[5] E G DePuey D S Berman and E V Garcia Cardiac SPECTImaging Raven Press New York NY USA 1995
[6] G Germano ldquoTechnical aspects of myocardial SPECT imag-ingrdquo Journal of Nuclear Medicine vol 42 no 10 pp 1499ndash15072001
[7] S R Cherry J A Sorenson andM E Phelps Physics in NuclearMedicine Saunders Philadelphia Pa USA 2003
[8] J Qi and R M Leahy ldquoIterative reconstruction techniques inemission computed tomographyrdquo Physics in Medicine and Bi-ology vol 51 pp R541ndashR578 2006
[9] C Lee-Tzuu ldquoA method for attenuation correction in radionu-clide computed tomographyrdquo IEEE Transactions on NuclearScience vol 25 no 1 pp 638ndash643 1978
[10] P P Bruyant ldquoAnalytic and iterative reconstruction algorithmsin SPECTrdquo Journal of NuclearMedicine vol 43 no 10 pp 1343ndash1358 2002
[11] M Lyra and A Ploussi ldquoFiltering in SPECT image reconstruc-tionrdquo International Journal of Biomedical Imaging vol 2011Article ID 693795 14 pages 2011
[12] M W Groch and W D Erwin ldquoSPECT in the year 2000 basicprinciplesrdquo Journal of Nuclear Medicine Technology vol 28 no4 pp 233ndash244 2000
[13] M M Khalil Basic Sciences of Nuclear Medicine Springer Be-rlin Germany 2010
[14] M N Salihin and A Zakaria ldquoDetermination of the optimumfilter for qualitative and quantitative 99mTc myocardial SPECTimagingrdquo Iranian Journal of Radiation Research vol 6 no 4 pp173ndash182 2009
[15] A Sadremomtaz and P Taherparvar ldquoThe influence of filters onthe SPECT image of Carlson phantomrdquo Journal of BiomedicalScience and Engineering vol 6 pp 291ndash297 2013
[16] Society of Nuclear Medicine and Molecular Imaging (2012)Phantoms Cardiac SPECT simulator 2012 httpinteractivesnmorgindexcfmPageID=11666
[17] S SynefiaM SotiropoulosM Argyrou et al ldquo3D SPECTmyo-cardial volume estimation increases the reliability of perfusiondiagnosisrdquo e-Journal of Science and Technology In press
[18] M Lyra M Sotiropoulos N Lagopati and M GavrillelildquoQuantification of myocardial perfusion in 3D SPECT images-stressrest volume differences 3D myocardium images quan-tificationrdquo in Proceedings of the IEEE International Conferenceon Imaging Systems and Techniques (IST rsquo10) pp 31ndash35 Thessa-loniki Greece July 2010
[19] M A King S J Glick B C Penney R B Schwinger and PW Doherty ldquoInteractive visual optimization of SPECT prerec-onstruction filteringrdquo Journal of Nuclear Medicine vol 28 no 7pp 1192ndash1198 1987
[20] J M Links R W Jeremy S M Dyer T L Frank and L CBecker ldquoWiener filtering improves quantification of regionalmyocardial perfusion with thallium-201 SPECTrdquo Journal ofNuclear Medicine vol 31 no 7 pp 1230ndash1236 1990
[21] G V Heller A Mann and R C Hendel Nuclear CardiologyTechnical Applications McGraw-Hill New York NY USA2009
Cardiology Research and Practice 11
[22] B Tasdemir T Balci B Demirel I Karaca A Aydin and ZKoc ldquoComparison of myocardial perfusion scintigraphy andcomputed tomography (CT) angiography based on conven-tional coronary angiographyrdquo Natural Science vol 4 pp 976ndash982 2012
[23] S R Underwood C Anagnostopoulos M Cerqueira et alldquoMyocardial perfusion scintigraphy the evidencerdquo EuropeanJournal of Nuclear Medicine and Molecular Imaging vol 31 no2 pp 261ndash291 2004
[24] Y H Lue and F J Wackers Cardiovascular Imaging MansonPublishing 2010
[25] E G DePuey Imaging Guidelines for Nuclear Cardiology Proce-dures The American Society of Nuclear Cardiology 2006
[26] R A Carlson and J T Colvin ldquoFluke Biomedical Nuclear Asso-ciates 76ndash823 76ndash824 amp 76ndash825 PETSPECT Phantom SourceTank Phantom Inserts and Cardiac Insertrdquo 2006 httpwwwflukebiomedicalcomBiomedicalusenNuclear-MedicineQual-ity-Control-Phantoms76-825htmPID=55292
[27] A Takavar G Shamsipour M Sohrabi and M Eftekhari ldquoDe-termination of optimumfilter inmyocardial SPECT a phantomstudyrdquo Iranian Journal of Radiation Research vol 4 no 1 pp205ndash210 2004
[28] M N Salihin and A Zakaria ldquoRelationship between the opti-mum cut off frequency for Butterworth filter and lung-heartratio in 99mTcmyocardial SPECTrdquo Iranian Journal of RadiationResearch vol 8 no 1 pp 17ndash24 2010
[29] H Rajabi A Rajabi N Yaghoobi H Firouzabady and F Rust-gou ldquoDetermination of the optimum filter function for Tc99m-sestamibi myocardial perfusion SPECT imagingrdquo Indian Jour-nal of Nuclear Medicine vol 20 no 3 pp 77ndash82 2005
[30] S Vandenberghe Y DrsquoAsseler R van de Walle et al ldquoIterativereconstruction algorithms in nuclear medicinerdquo ComputerizedMedical Imaging and Graphics vol 25 no 2 pp 105ndash111 2001
[31] E G DePuey ldquoAdvances in SPECT camera software and hard-ware currently available and new on the horizonrdquo Journal ofNuclear Cardiology vol 19 no 3 pp 551ndash581 2012
[32] R L Hatton B F Hutton S Angelides K K L Choong andG Larcos ldquoImproved tolerance to missing data in myocardialperfusion SPET usingOSEM reconstructionrdquo European Journalof Nuclear Medicine and Molecular Imaging vol 31 no 6 pp857ndash861 2004
[33] S R Zakavi A Zonoozi V D Kakhki M Hajizadeh MMom-ennezhad and K Ariana ldquoImage reconstruction using filteredbackprojection and iterative method effect on motion artifactsin myocardial perfusion SPECTrdquo Journal of Nuclear MedicineTechnology vol 34 no 4 pp 220ndash223 2006
[34] KWon E KimMMar et al ldquoIs iterative reconstruction an im-provement over filtered back projection in processing gatedmyocardial perfusion SPECTrdquo The Open Medical ImagingJournal vol 2 pp 17ndash23 2008
[35] A Otte K Audenaert K Peremans K Heeringen and R Dier-ckx Nuclear Medicine in Psychiatry Springer Berlin Germany2004
[36] M Lyra ldquoSingle photon emission tomography (SPECT) and 3Dimages evaluation in nuclear medicinerdquo in Image ProcessingY S Chen Ed InTech 2009 httpwwwintechopencombooksimage-processingsingle-photon-emission-tomography-spect-and-3d-images-evaluation-in-nuclear-medicine
[37] A Seret and J Forthomme ldquoComparison of different types ofcommercial filtered backprojection and ordered-subset expec-tation maximization SPECT reconstruction softwarerdquo Journalof Nuclear Medicine Technology vol 37 no 3 pp 179ndash187 2009
[38] R S Lima D DWatson A R Goode et al ldquoIncremental valueof combined perfusion and function over perfusion alone bygated SPECT myocardial perfusion imaging for detection ofsevere three-vessel coronary artery diseaserdquo Journal of theAmerican College of Cardiology vol 42 no 1 pp 64ndash70 2003
[39] A K Paul andH A Nabi ldquoGatedmyocardial perfusion SPECTbasic principles technical aspects and clinical applicationsrdquoJournal of Nuclear Medicine Technology vol 32 no 4 pp 179ndash187 2004
[40] P Vera A Manrique V Pontvianne A Hitzel R Koningand A Cribier ldquoThallium-gated SPECT in patients with majormyocardial infarction effect of filtering and zooming in com-parison with equilibrium radionuclide imaging and left ven-triculographyrdquo Journal of Nuclear Medicine vol 40 no 4 pp513ndash521 1999
[41] P Y Marie W Djaballah P R Franken et al ldquoOSEM recon-struction associated with temporal Fourier and depth-dependant resolution recovery filtering enhances results fromsestamibi and 201T1 16-Interval Gated SPECTrdquo Journal ofNuclear Medicine vol 46 no 11 pp 1789ndash1795 2005
[42] T Vakhtangandze D O Hall F V Zananiri and M R ReesldquoThe effect of Butterworth and Metz reconstruction filters onvolume and ejection fraction calculations with 99Tcm gatedmyocardial SPECTrdquoBritish Journal of Radiology vol 78 no 932pp 733ndash736 2005
[43] G A Wright M McDade W Martin and I Hutton ldquoQuan-titative gated SPECT the effect of reconstruction filter oncalculated left ventricular ejection fractions and volumesrdquoPhysics in Medicine and Biology vol 47 no 8 pp 99ndash105 2002
[44] N Trayanova ldquoComputational cardiology the heart of thematterrdquo ISRN Cardiology vol 2012 Article ID 269680 15 pages2012
Figure 10 3D volume of a normal myocardium reconstruction is obtained through a specifiedMatLab code in order to compare the differentfilters used Butterworth (a) and Hann (b) filetrs are used Insignificant voxel differences are observed Data acquired at Medical ImagingNuclear Medicine and MatLab algorithm in Radiation Physics Unit Aretaieion Hospital Athens
16
14
12
10
8
6
48
46
44
42
40
38
28 26 24 22 20 18 16
(a)
48
46
44
42
40
38
12
10
8
6
4
25
20
15
(b)
Figure 11 3Dmyocardium processed by aMatLab code in order to compare myocardium volume at rest (left) and at stress (right) (Lyra et al2010) The image does not depict the real volume but the voxelized one (the functional myocardium) Figure is obtained from citation [18]
In 2005 [42] the differences produced by change ofreconstruction filter in calculations of left-ventricular enddiastolic volume (EDV) end systolic volume (ESV) strokevolume (SV) and ejection fraction (LVEF) from 99mTc-sestamibi myocardial gated SPECT studies have been inves-tigated Butterworth order 4 cutoff frequency 025 cyclespixel and Metz order 8 full-width half maximum 40mmwere applied and compared With the Metz filter ratherthan the Butterworth filter left-ventricular EDV and ESVwere significantly larger and the LVEF and SV were notsignificantly changedThe results were consistent to previoussimilar studies [40 43]
7 Discussion
The SPECT filters can greatly affect the quality of clinicalimages Proper filter selection and adequate smoothing helpsthe physician in resultsrsquo interpretation and accurate diagnosis
Several studies on phantoms with respect to the mostappropriate filter for cardiac SPECT have been consideredThe studies showed that for the 3D SPECT reconstructionButterworth filter succeeds the best compromise betweenSNR and detail in the image while Parzen filter producesthe best accurate size [20] Maximum contrast betweennormal and defected myocardium could be obtained using
10 Cardiology Research and Practice
the Metz (FWHM 35ndash45 pixel orders of 8ndash95) Wiener(FWHMs 35ndash4) Butterworth (cutoffs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) filters [29] The cutofffrequency of 0325 of Nq gave the best overall result for theHanning filter whereas for the Butterworth filter order 11and cut off of 045Nq gave the best image quality and sizeaccuracy [27]
For the 4DECG-gated SPECT reconstruction best resultswere obtained using a Butterworth filter with an order of 5and cutoff frequency of 030 cyclespixel [41]
As far as the reconstruction technique is concerned using3D OSEM with suitable AC may improve lesion detectabilitydue to the significant improvement of image contrast [35] 3Diterative reconstruction algorithms are likely to replace theFBP technique for many SPECT clinical applications
When a specified 3D reconstruction MatLab code wasused to compare both two chosen filters (Butterworth andHann) andmyocardium volume at rest and at stress accuratediagnostic images were produced
It is expected that further significant improvement inimage quality will be attained which in turn will increasethe confidence of image interpretation The development ofalgorithms for analysis of myocardial 3D images may allowbetter evaluation of small and nontransmural myocardialdefects For the diagnosis and treatment of heart diseasesthe accurate visualisation of the spatial heart shape 3Dvolume of the LV and the heart wall perfusion plays a crucialrole Surface shading is a valuable tool for determining thepresence extent and location of CAD
Further developments in cardiac diagnosis include anew promising tool computational cardiologyThe functionsof the diseased heart and the probable new techniques indiagnosis and treatment can be studied using state-of-the-art whole-heart models of electrophysiology and electrome-chanics A characteristic example of implementing such amodel is ventricular modelling where important aspects ofarrhythmias including dynamic characteristics of ventricu-lar fibrillation can be revealed Performing patient-specificcomputer simulations of the function of the diseased heart foreither diagnostic or treatment purposes could be an excitingnew implementation of computational cardiology [44]
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
References
[1] WHO Global Atlas on Cardiovascular Disease Prevention andControl WHO World Heart Federation World Stroke Organi-zation 2011 httpwwwwhointcardiovascular diseasesen
[2] S Agarwal M G Shlipak H Kramer A Jain and D MHerrington ldquoThe association of chronic kidney disease andmetabolic syndrome with incident cardiovascular events mul-tiethnic study of atherosclerosisrdquo Cardiology Research andPractice vol 2012 Article ID 806102 8 pages 2012
[3] H Jadvar H W Strauss and G M Segall ldquoSPECT and PET inthe evaluation of coronary artery diseaserdquo Radiographics vol19 no 4 pp 915ndash926 1999
[4] K van Laere M Koole I Lemahieu and R Dierckx ldquoImagefiltering in single-photon emission computed tomography Pri-nciples and applicationsrdquo Computerized Medical Imaging andGraphics vol 25 no 2 pp 127ndash133 2001
[5] E G DePuey D S Berman and E V Garcia Cardiac SPECTImaging Raven Press New York NY USA 1995
[6] G Germano ldquoTechnical aspects of myocardial SPECT imag-ingrdquo Journal of Nuclear Medicine vol 42 no 10 pp 1499ndash15072001
[7] S R Cherry J A Sorenson andM E Phelps Physics in NuclearMedicine Saunders Philadelphia Pa USA 2003
[8] J Qi and R M Leahy ldquoIterative reconstruction techniques inemission computed tomographyrdquo Physics in Medicine and Bi-ology vol 51 pp R541ndashR578 2006
[9] C Lee-Tzuu ldquoA method for attenuation correction in radionu-clide computed tomographyrdquo IEEE Transactions on NuclearScience vol 25 no 1 pp 638ndash643 1978
[10] P P Bruyant ldquoAnalytic and iterative reconstruction algorithmsin SPECTrdquo Journal of NuclearMedicine vol 43 no 10 pp 1343ndash1358 2002
[11] M Lyra and A Ploussi ldquoFiltering in SPECT image reconstruc-tionrdquo International Journal of Biomedical Imaging vol 2011Article ID 693795 14 pages 2011
[12] M W Groch and W D Erwin ldquoSPECT in the year 2000 basicprinciplesrdquo Journal of Nuclear Medicine Technology vol 28 no4 pp 233ndash244 2000
[13] M M Khalil Basic Sciences of Nuclear Medicine Springer Be-rlin Germany 2010
[14] M N Salihin and A Zakaria ldquoDetermination of the optimumfilter for qualitative and quantitative 99mTc myocardial SPECTimagingrdquo Iranian Journal of Radiation Research vol 6 no 4 pp173ndash182 2009
[15] A Sadremomtaz and P Taherparvar ldquoThe influence of filters onthe SPECT image of Carlson phantomrdquo Journal of BiomedicalScience and Engineering vol 6 pp 291ndash297 2013
[16] Society of Nuclear Medicine and Molecular Imaging (2012)Phantoms Cardiac SPECT simulator 2012 httpinteractivesnmorgindexcfmPageID=11666
[17] S SynefiaM SotiropoulosM Argyrou et al ldquo3D SPECTmyo-cardial volume estimation increases the reliability of perfusiondiagnosisrdquo e-Journal of Science and Technology In press
[18] M Lyra M Sotiropoulos N Lagopati and M GavrillelildquoQuantification of myocardial perfusion in 3D SPECT images-stressrest volume differences 3D myocardium images quan-tificationrdquo in Proceedings of the IEEE International Conferenceon Imaging Systems and Techniques (IST rsquo10) pp 31ndash35 Thessa-loniki Greece July 2010
[19] M A King S J Glick B C Penney R B Schwinger and PW Doherty ldquoInteractive visual optimization of SPECT prerec-onstruction filteringrdquo Journal of Nuclear Medicine vol 28 no 7pp 1192ndash1198 1987
[20] J M Links R W Jeremy S M Dyer T L Frank and L CBecker ldquoWiener filtering improves quantification of regionalmyocardial perfusion with thallium-201 SPECTrdquo Journal ofNuclear Medicine vol 31 no 7 pp 1230ndash1236 1990
[21] G V Heller A Mann and R C Hendel Nuclear CardiologyTechnical Applications McGraw-Hill New York NY USA2009
Cardiology Research and Practice 11
[22] B Tasdemir T Balci B Demirel I Karaca A Aydin and ZKoc ldquoComparison of myocardial perfusion scintigraphy andcomputed tomography (CT) angiography based on conven-tional coronary angiographyrdquo Natural Science vol 4 pp 976ndash982 2012
[23] S R Underwood C Anagnostopoulos M Cerqueira et alldquoMyocardial perfusion scintigraphy the evidencerdquo EuropeanJournal of Nuclear Medicine and Molecular Imaging vol 31 no2 pp 261ndash291 2004
[24] Y H Lue and F J Wackers Cardiovascular Imaging MansonPublishing 2010
[25] E G DePuey Imaging Guidelines for Nuclear Cardiology Proce-dures The American Society of Nuclear Cardiology 2006
[26] R A Carlson and J T Colvin ldquoFluke Biomedical Nuclear Asso-ciates 76ndash823 76ndash824 amp 76ndash825 PETSPECT Phantom SourceTank Phantom Inserts and Cardiac Insertrdquo 2006 httpwwwflukebiomedicalcomBiomedicalusenNuclear-MedicineQual-ity-Control-Phantoms76-825htmPID=55292
[27] A Takavar G Shamsipour M Sohrabi and M Eftekhari ldquoDe-termination of optimumfilter inmyocardial SPECT a phantomstudyrdquo Iranian Journal of Radiation Research vol 4 no 1 pp205ndash210 2004
[28] M N Salihin and A Zakaria ldquoRelationship between the opti-mum cut off frequency for Butterworth filter and lung-heartratio in 99mTcmyocardial SPECTrdquo Iranian Journal of RadiationResearch vol 8 no 1 pp 17ndash24 2010
[29] H Rajabi A Rajabi N Yaghoobi H Firouzabady and F Rust-gou ldquoDetermination of the optimum filter function for Tc99m-sestamibi myocardial perfusion SPECT imagingrdquo Indian Jour-nal of Nuclear Medicine vol 20 no 3 pp 77ndash82 2005
[30] S Vandenberghe Y DrsquoAsseler R van de Walle et al ldquoIterativereconstruction algorithms in nuclear medicinerdquo ComputerizedMedical Imaging and Graphics vol 25 no 2 pp 105ndash111 2001
[31] E G DePuey ldquoAdvances in SPECT camera software and hard-ware currently available and new on the horizonrdquo Journal ofNuclear Cardiology vol 19 no 3 pp 551ndash581 2012
[32] R L Hatton B F Hutton S Angelides K K L Choong andG Larcos ldquoImproved tolerance to missing data in myocardialperfusion SPET usingOSEM reconstructionrdquo European Journalof Nuclear Medicine and Molecular Imaging vol 31 no 6 pp857ndash861 2004
[33] S R Zakavi A Zonoozi V D Kakhki M Hajizadeh MMom-ennezhad and K Ariana ldquoImage reconstruction using filteredbackprojection and iterative method effect on motion artifactsin myocardial perfusion SPECTrdquo Journal of Nuclear MedicineTechnology vol 34 no 4 pp 220ndash223 2006
[34] KWon E KimMMar et al ldquoIs iterative reconstruction an im-provement over filtered back projection in processing gatedmyocardial perfusion SPECTrdquo The Open Medical ImagingJournal vol 2 pp 17ndash23 2008
[35] A Otte K Audenaert K Peremans K Heeringen and R Dier-ckx Nuclear Medicine in Psychiatry Springer Berlin Germany2004
[36] M Lyra ldquoSingle photon emission tomography (SPECT) and 3Dimages evaluation in nuclear medicinerdquo in Image ProcessingY S Chen Ed InTech 2009 httpwwwintechopencombooksimage-processingsingle-photon-emission-tomography-spect-and-3d-images-evaluation-in-nuclear-medicine
[37] A Seret and J Forthomme ldquoComparison of different types ofcommercial filtered backprojection and ordered-subset expec-tation maximization SPECT reconstruction softwarerdquo Journalof Nuclear Medicine Technology vol 37 no 3 pp 179ndash187 2009
[38] R S Lima D DWatson A R Goode et al ldquoIncremental valueof combined perfusion and function over perfusion alone bygated SPECT myocardial perfusion imaging for detection ofsevere three-vessel coronary artery diseaserdquo Journal of theAmerican College of Cardiology vol 42 no 1 pp 64ndash70 2003
[39] A K Paul andH A Nabi ldquoGatedmyocardial perfusion SPECTbasic principles technical aspects and clinical applicationsrdquoJournal of Nuclear Medicine Technology vol 32 no 4 pp 179ndash187 2004
[40] P Vera A Manrique V Pontvianne A Hitzel R Koningand A Cribier ldquoThallium-gated SPECT in patients with majormyocardial infarction effect of filtering and zooming in com-parison with equilibrium radionuclide imaging and left ven-triculographyrdquo Journal of Nuclear Medicine vol 40 no 4 pp513ndash521 1999
[41] P Y Marie W Djaballah P R Franken et al ldquoOSEM recon-struction associated with temporal Fourier and depth-dependant resolution recovery filtering enhances results fromsestamibi and 201T1 16-Interval Gated SPECTrdquo Journal ofNuclear Medicine vol 46 no 11 pp 1789ndash1795 2005
[42] T Vakhtangandze D O Hall F V Zananiri and M R ReesldquoThe effect of Butterworth and Metz reconstruction filters onvolume and ejection fraction calculations with 99Tcm gatedmyocardial SPECTrdquoBritish Journal of Radiology vol 78 no 932pp 733ndash736 2005
[43] G A Wright M McDade W Martin and I Hutton ldquoQuan-titative gated SPECT the effect of reconstruction filter oncalculated left ventricular ejection fractions and volumesrdquoPhysics in Medicine and Biology vol 47 no 8 pp 99ndash105 2002
[44] N Trayanova ldquoComputational cardiology the heart of thematterrdquo ISRN Cardiology vol 2012 Article ID 269680 15 pages2012
the Metz (FWHM 35ndash45 pixel orders of 8ndash95) Wiener(FWHMs 35ndash4) Butterworth (cutoffs 03ndash05 orders 3ndash9) and Hanning (cutoffs 043ndash05) filters [29] The cutofffrequency of 0325 of Nq gave the best overall result for theHanning filter whereas for the Butterworth filter order 11and cut off of 045Nq gave the best image quality and sizeaccuracy [27]
For the 4DECG-gated SPECT reconstruction best resultswere obtained using a Butterworth filter with an order of 5and cutoff frequency of 030 cyclespixel [41]
As far as the reconstruction technique is concerned using3D OSEM with suitable AC may improve lesion detectabilitydue to the significant improvement of image contrast [35] 3Diterative reconstruction algorithms are likely to replace theFBP technique for many SPECT clinical applications
When a specified 3D reconstruction MatLab code wasused to compare both two chosen filters (Butterworth andHann) andmyocardium volume at rest and at stress accuratediagnostic images were produced
It is expected that further significant improvement inimage quality will be attained which in turn will increasethe confidence of image interpretation The development ofalgorithms for analysis of myocardial 3D images may allowbetter evaluation of small and nontransmural myocardialdefects For the diagnosis and treatment of heart diseasesthe accurate visualisation of the spatial heart shape 3Dvolume of the LV and the heart wall perfusion plays a crucialrole Surface shading is a valuable tool for determining thepresence extent and location of CAD
Further developments in cardiac diagnosis include anew promising tool computational cardiologyThe functionsof the diseased heart and the probable new techniques indiagnosis and treatment can be studied using state-of-the-art whole-heart models of electrophysiology and electrome-chanics A characteristic example of implementing such amodel is ventricular modelling where important aspects ofarrhythmias including dynamic characteristics of ventricu-lar fibrillation can be revealed Performing patient-specificcomputer simulations of the function of the diseased heart foreither diagnostic or treatment purposes could be an excitingnew implementation of computational cardiology [44]
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
References
[1] WHO Global Atlas on Cardiovascular Disease Prevention andControl WHO World Heart Federation World Stroke Organi-zation 2011 httpwwwwhointcardiovascular diseasesen
[2] S Agarwal M G Shlipak H Kramer A Jain and D MHerrington ldquoThe association of chronic kidney disease andmetabolic syndrome with incident cardiovascular events mul-tiethnic study of atherosclerosisrdquo Cardiology Research andPractice vol 2012 Article ID 806102 8 pages 2012
[3] H Jadvar H W Strauss and G M Segall ldquoSPECT and PET inthe evaluation of coronary artery diseaserdquo Radiographics vol19 no 4 pp 915ndash926 1999
[4] K van Laere M Koole I Lemahieu and R Dierckx ldquoImagefiltering in single-photon emission computed tomography Pri-nciples and applicationsrdquo Computerized Medical Imaging andGraphics vol 25 no 2 pp 127ndash133 2001
[5] E G DePuey D S Berman and E V Garcia Cardiac SPECTImaging Raven Press New York NY USA 1995
[6] G Germano ldquoTechnical aspects of myocardial SPECT imag-ingrdquo Journal of Nuclear Medicine vol 42 no 10 pp 1499ndash15072001
[7] S R Cherry J A Sorenson andM E Phelps Physics in NuclearMedicine Saunders Philadelphia Pa USA 2003
[8] J Qi and R M Leahy ldquoIterative reconstruction techniques inemission computed tomographyrdquo Physics in Medicine and Bi-ology vol 51 pp R541ndashR578 2006
[9] C Lee-Tzuu ldquoA method for attenuation correction in radionu-clide computed tomographyrdquo IEEE Transactions on NuclearScience vol 25 no 1 pp 638ndash643 1978
[10] P P Bruyant ldquoAnalytic and iterative reconstruction algorithmsin SPECTrdquo Journal of NuclearMedicine vol 43 no 10 pp 1343ndash1358 2002
[11] M Lyra and A Ploussi ldquoFiltering in SPECT image reconstruc-tionrdquo International Journal of Biomedical Imaging vol 2011Article ID 693795 14 pages 2011
[12] M W Groch and W D Erwin ldquoSPECT in the year 2000 basicprinciplesrdquo Journal of Nuclear Medicine Technology vol 28 no4 pp 233ndash244 2000
[13] M M Khalil Basic Sciences of Nuclear Medicine Springer Be-rlin Germany 2010
[14] M N Salihin and A Zakaria ldquoDetermination of the optimumfilter for qualitative and quantitative 99mTc myocardial SPECTimagingrdquo Iranian Journal of Radiation Research vol 6 no 4 pp173ndash182 2009
[15] A Sadremomtaz and P Taherparvar ldquoThe influence of filters onthe SPECT image of Carlson phantomrdquo Journal of BiomedicalScience and Engineering vol 6 pp 291ndash297 2013
[16] Society of Nuclear Medicine and Molecular Imaging (2012)Phantoms Cardiac SPECT simulator 2012 httpinteractivesnmorgindexcfmPageID=11666
[17] S SynefiaM SotiropoulosM Argyrou et al ldquo3D SPECTmyo-cardial volume estimation increases the reliability of perfusiondiagnosisrdquo e-Journal of Science and Technology In press
[18] M Lyra M Sotiropoulos N Lagopati and M GavrillelildquoQuantification of myocardial perfusion in 3D SPECT images-stressrest volume differences 3D myocardium images quan-tificationrdquo in Proceedings of the IEEE International Conferenceon Imaging Systems and Techniques (IST rsquo10) pp 31ndash35 Thessa-loniki Greece July 2010
[19] M A King S J Glick B C Penney R B Schwinger and PW Doherty ldquoInteractive visual optimization of SPECT prerec-onstruction filteringrdquo Journal of Nuclear Medicine vol 28 no 7pp 1192ndash1198 1987
[20] J M Links R W Jeremy S M Dyer T L Frank and L CBecker ldquoWiener filtering improves quantification of regionalmyocardial perfusion with thallium-201 SPECTrdquo Journal ofNuclear Medicine vol 31 no 7 pp 1230ndash1236 1990
[21] G V Heller A Mann and R C Hendel Nuclear CardiologyTechnical Applications McGraw-Hill New York NY USA2009
Cardiology Research and Practice 11
[22] B Tasdemir T Balci B Demirel I Karaca A Aydin and ZKoc ldquoComparison of myocardial perfusion scintigraphy andcomputed tomography (CT) angiography based on conven-tional coronary angiographyrdquo Natural Science vol 4 pp 976ndash982 2012
[23] S R Underwood C Anagnostopoulos M Cerqueira et alldquoMyocardial perfusion scintigraphy the evidencerdquo EuropeanJournal of Nuclear Medicine and Molecular Imaging vol 31 no2 pp 261ndash291 2004
[24] Y H Lue and F J Wackers Cardiovascular Imaging MansonPublishing 2010
[25] E G DePuey Imaging Guidelines for Nuclear Cardiology Proce-dures The American Society of Nuclear Cardiology 2006
[26] R A Carlson and J T Colvin ldquoFluke Biomedical Nuclear Asso-ciates 76ndash823 76ndash824 amp 76ndash825 PETSPECT Phantom SourceTank Phantom Inserts and Cardiac Insertrdquo 2006 httpwwwflukebiomedicalcomBiomedicalusenNuclear-MedicineQual-ity-Control-Phantoms76-825htmPID=55292
[27] A Takavar G Shamsipour M Sohrabi and M Eftekhari ldquoDe-termination of optimumfilter inmyocardial SPECT a phantomstudyrdquo Iranian Journal of Radiation Research vol 4 no 1 pp205ndash210 2004
[28] M N Salihin and A Zakaria ldquoRelationship between the opti-mum cut off frequency for Butterworth filter and lung-heartratio in 99mTcmyocardial SPECTrdquo Iranian Journal of RadiationResearch vol 8 no 1 pp 17ndash24 2010
[29] H Rajabi A Rajabi N Yaghoobi H Firouzabady and F Rust-gou ldquoDetermination of the optimum filter function for Tc99m-sestamibi myocardial perfusion SPECT imagingrdquo Indian Jour-nal of Nuclear Medicine vol 20 no 3 pp 77ndash82 2005
[30] S Vandenberghe Y DrsquoAsseler R van de Walle et al ldquoIterativereconstruction algorithms in nuclear medicinerdquo ComputerizedMedical Imaging and Graphics vol 25 no 2 pp 105ndash111 2001
[31] E G DePuey ldquoAdvances in SPECT camera software and hard-ware currently available and new on the horizonrdquo Journal ofNuclear Cardiology vol 19 no 3 pp 551ndash581 2012
[32] R L Hatton B F Hutton S Angelides K K L Choong andG Larcos ldquoImproved tolerance to missing data in myocardialperfusion SPET usingOSEM reconstructionrdquo European Journalof Nuclear Medicine and Molecular Imaging vol 31 no 6 pp857ndash861 2004
[33] S R Zakavi A Zonoozi V D Kakhki M Hajizadeh MMom-ennezhad and K Ariana ldquoImage reconstruction using filteredbackprojection and iterative method effect on motion artifactsin myocardial perfusion SPECTrdquo Journal of Nuclear MedicineTechnology vol 34 no 4 pp 220ndash223 2006
[34] KWon E KimMMar et al ldquoIs iterative reconstruction an im-provement over filtered back projection in processing gatedmyocardial perfusion SPECTrdquo The Open Medical ImagingJournal vol 2 pp 17ndash23 2008
[35] A Otte K Audenaert K Peremans K Heeringen and R Dier-ckx Nuclear Medicine in Psychiatry Springer Berlin Germany2004
[36] M Lyra ldquoSingle photon emission tomography (SPECT) and 3Dimages evaluation in nuclear medicinerdquo in Image ProcessingY S Chen Ed InTech 2009 httpwwwintechopencombooksimage-processingsingle-photon-emission-tomography-spect-and-3d-images-evaluation-in-nuclear-medicine
[37] A Seret and J Forthomme ldquoComparison of different types ofcommercial filtered backprojection and ordered-subset expec-tation maximization SPECT reconstruction softwarerdquo Journalof Nuclear Medicine Technology vol 37 no 3 pp 179ndash187 2009
[38] R S Lima D DWatson A R Goode et al ldquoIncremental valueof combined perfusion and function over perfusion alone bygated SPECT myocardial perfusion imaging for detection ofsevere three-vessel coronary artery diseaserdquo Journal of theAmerican College of Cardiology vol 42 no 1 pp 64ndash70 2003
[39] A K Paul andH A Nabi ldquoGatedmyocardial perfusion SPECTbasic principles technical aspects and clinical applicationsrdquoJournal of Nuclear Medicine Technology vol 32 no 4 pp 179ndash187 2004
[40] P Vera A Manrique V Pontvianne A Hitzel R Koningand A Cribier ldquoThallium-gated SPECT in patients with majormyocardial infarction effect of filtering and zooming in com-parison with equilibrium radionuclide imaging and left ven-triculographyrdquo Journal of Nuclear Medicine vol 40 no 4 pp513ndash521 1999
[41] P Y Marie W Djaballah P R Franken et al ldquoOSEM recon-struction associated with temporal Fourier and depth-dependant resolution recovery filtering enhances results fromsestamibi and 201T1 16-Interval Gated SPECTrdquo Journal ofNuclear Medicine vol 46 no 11 pp 1789ndash1795 2005
[42] T Vakhtangandze D O Hall F V Zananiri and M R ReesldquoThe effect of Butterworth and Metz reconstruction filters onvolume and ejection fraction calculations with 99Tcm gatedmyocardial SPECTrdquoBritish Journal of Radiology vol 78 no 932pp 733ndash736 2005
[43] G A Wright M McDade W Martin and I Hutton ldquoQuan-titative gated SPECT the effect of reconstruction filter oncalculated left ventricular ejection fractions and volumesrdquoPhysics in Medicine and Biology vol 47 no 8 pp 99ndash105 2002
[44] N Trayanova ldquoComputational cardiology the heart of thematterrdquo ISRN Cardiology vol 2012 Article ID 269680 15 pages2012
[22] B Tasdemir T Balci B Demirel I Karaca A Aydin and ZKoc ldquoComparison of myocardial perfusion scintigraphy andcomputed tomography (CT) angiography based on conven-tional coronary angiographyrdquo Natural Science vol 4 pp 976ndash982 2012
[23] S R Underwood C Anagnostopoulos M Cerqueira et alldquoMyocardial perfusion scintigraphy the evidencerdquo EuropeanJournal of Nuclear Medicine and Molecular Imaging vol 31 no2 pp 261ndash291 2004
[24] Y H Lue and F J Wackers Cardiovascular Imaging MansonPublishing 2010
[25] E G DePuey Imaging Guidelines for Nuclear Cardiology Proce-dures The American Society of Nuclear Cardiology 2006
[26] R A Carlson and J T Colvin ldquoFluke Biomedical Nuclear Asso-ciates 76ndash823 76ndash824 amp 76ndash825 PETSPECT Phantom SourceTank Phantom Inserts and Cardiac Insertrdquo 2006 httpwwwflukebiomedicalcomBiomedicalusenNuclear-MedicineQual-ity-Control-Phantoms76-825htmPID=55292
[27] A Takavar G Shamsipour M Sohrabi and M Eftekhari ldquoDe-termination of optimumfilter inmyocardial SPECT a phantomstudyrdquo Iranian Journal of Radiation Research vol 4 no 1 pp205ndash210 2004
[28] M N Salihin and A Zakaria ldquoRelationship between the opti-mum cut off frequency for Butterworth filter and lung-heartratio in 99mTcmyocardial SPECTrdquo Iranian Journal of RadiationResearch vol 8 no 1 pp 17ndash24 2010
[29] H Rajabi A Rajabi N Yaghoobi H Firouzabady and F Rust-gou ldquoDetermination of the optimum filter function for Tc99m-sestamibi myocardial perfusion SPECT imagingrdquo Indian Jour-nal of Nuclear Medicine vol 20 no 3 pp 77ndash82 2005
[30] S Vandenberghe Y DrsquoAsseler R van de Walle et al ldquoIterativereconstruction algorithms in nuclear medicinerdquo ComputerizedMedical Imaging and Graphics vol 25 no 2 pp 105ndash111 2001
[31] E G DePuey ldquoAdvances in SPECT camera software and hard-ware currently available and new on the horizonrdquo Journal ofNuclear Cardiology vol 19 no 3 pp 551ndash581 2012
[32] R L Hatton B F Hutton S Angelides K K L Choong andG Larcos ldquoImproved tolerance to missing data in myocardialperfusion SPET usingOSEM reconstructionrdquo European Journalof Nuclear Medicine and Molecular Imaging vol 31 no 6 pp857ndash861 2004
[33] S R Zakavi A Zonoozi V D Kakhki M Hajizadeh MMom-ennezhad and K Ariana ldquoImage reconstruction using filteredbackprojection and iterative method effect on motion artifactsin myocardial perfusion SPECTrdquo Journal of Nuclear MedicineTechnology vol 34 no 4 pp 220ndash223 2006
[34] KWon E KimMMar et al ldquoIs iterative reconstruction an im-provement over filtered back projection in processing gatedmyocardial perfusion SPECTrdquo The Open Medical ImagingJournal vol 2 pp 17ndash23 2008
[35] A Otte K Audenaert K Peremans K Heeringen and R Dier-ckx Nuclear Medicine in Psychiatry Springer Berlin Germany2004
[36] M Lyra ldquoSingle photon emission tomography (SPECT) and 3Dimages evaluation in nuclear medicinerdquo in Image ProcessingY S Chen Ed InTech 2009 httpwwwintechopencombooksimage-processingsingle-photon-emission-tomography-spect-and-3d-images-evaluation-in-nuclear-medicine
[37] A Seret and J Forthomme ldquoComparison of different types ofcommercial filtered backprojection and ordered-subset expec-tation maximization SPECT reconstruction softwarerdquo Journalof Nuclear Medicine Technology vol 37 no 3 pp 179ndash187 2009
[38] R S Lima D DWatson A R Goode et al ldquoIncremental valueof combined perfusion and function over perfusion alone bygated SPECT myocardial perfusion imaging for detection ofsevere three-vessel coronary artery diseaserdquo Journal of theAmerican College of Cardiology vol 42 no 1 pp 64ndash70 2003
[39] A K Paul andH A Nabi ldquoGatedmyocardial perfusion SPECTbasic principles technical aspects and clinical applicationsrdquoJournal of Nuclear Medicine Technology vol 32 no 4 pp 179ndash187 2004
[40] P Vera A Manrique V Pontvianne A Hitzel R Koningand A Cribier ldquoThallium-gated SPECT in patients with majormyocardial infarction effect of filtering and zooming in com-parison with equilibrium radionuclide imaging and left ven-triculographyrdquo Journal of Nuclear Medicine vol 40 no 4 pp513ndash521 1999
[41] P Y Marie W Djaballah P R Franken et al ldquoOSEM recon-struction associated with temporal Fourier and depth-dependant resolution recovery filtering enhances results fromsestamibi and 201T1 16-Interval Gated SPECTrdquo Journal ofNuclear Medicine vol 46 no 11 pp 1789ndash1795 2005
[42] T Vakhtangandze D O Hall F V Zananiri and M R ReesldquoThe effect of Butterworth and Metz reconstruction filters onvolume and ejection fraction calculations with 99Tcm gatedmyocardial SPECTrdquoBritish Journal of Radiology vol 78 no 932pp 733ndash736 2005
[43] G A Wright M McDade W Martin and I Hutton ldquoQuan-titative gated SPECT the effect of reconstruction filter oncalculated left ventricular ejection fractions and volumesrdquoPhysics in Medicine and Biology vol 47 no 8 pp 99ndash105 2002
[44] N Trayanova ldquoComputational cardiology the heart of thematterrdquo ISRN Cardiology vol 2012 Article ID 269680 15 pages2012
