6020 Ferumoxytol-enhanced Plural Contrast Imaging of the Human Brain

Samantha J Holdsworth1, Thomas Christen1, Kristen Yeom1, Jae Mo Park1, Greg Zaharchuk1, and Michael E Moseley1 1Department of Radiology, Stanford University, Stanford, CA, United States

Purpose: To exploit the 3D multi-echo GRE sequence coupled with and without the injection of ferumoxytol for plural-contrast clinical neuroimaging at 3T. Introduction: Ferumoxytol (Feraheme, AMAG Pharmaceuticals, Inc., Cambridge, MA), an FDA-approved ultra-small paramagnetic iron oxide (USPIO) compound, has been used as an “off label” contrast agent to study inflammatory processes, vascular lesions, tumor, or stroke [1-

6]. It is retained in the intravascular space early after injection and does not cross an intact blood brain barrier [7-8]. The high magnetic susceptibility of ferumoxytol considerably reduces the T2* and the long intravascular half-life allows high-resolution/high-SNR acquisitions that may be useful to study brain disorders[9]. Particularly in pediatric brain, where patient cooperation can be problematic, we are striving to generate and study multiple image contrasts from a single imaging sequence. The 3D multi-echo gradient-recalled echo (ME-GRE) technique is a particularly good candidate for this, as it allows for the simultaneous generation of naturally co-registered images with various contrasts[10-11]. Here we show preliminary data scanned with a 5:44-minute 3D ME-GRE sequence acquired both pre- and post ferumoxytol, with the subsequent generation of R2* maps, local field maps, Susceptibility-Weighted Imaging (SWI), Time-of-Flight Magnetic Resonance Angiography (TOF), and Quantitative Susceptibility Maps (QSM). Methods: With IRB approval, pediatric patients were scanned on a 3T GE scanner (MR750, GE Healthcare Systems, Waukesha, WI) equipped with an 8-channel head-coil. In addition to the regular clinical pediatric brain protocol, a flow-compensated 3D GRAPPA-accelerated ME-GRE sequence was scanned both before and after the intravenous injection of a single dose of ferumoxytol (0.1 mL Fe/kg). The following parameters were used: resolution = 0.57x0.86x2.5mm3, 66 z-partitions, acceleration factor = 2, 8 echoes ranging from TE = 4.3ms – 37.5ms with 4.7ms increments, TR = 40.8ms, scan time = 5:44min. On completion of the scan, the raw data from the scanner were automatically reconstructed using compiled threaded MATLAB (MathWorks Inc., Natick, MA, USA) code, with all images sent to the hospital database (PACS). First, the 8-channel coil data were combined with the complex sum-of-squares. Weighted magnitude images (wMag) were calculated using the echo time of each echo image as a weighting factor. R2* (1/T2*) maps were calculated from mono-exponential fit of echoes. Field maps were generated by first performing a complex fit across echoes[12-14], followed by phase unwrapping using a Laplacian algorithm[15] and projection onto dipole fields[16-18]. QSM images were generated from this field map using the MEDI algorithm[12,16-18]. SWI images were created by generating a phase mask (using a 2D Hanning window), and multiplying this mask 5 times by the weighted-magnitude image[19-20]. TOF images were produced by taking the Maximum Intensity Projection (MIP) over the first echo. Results: Fig. 1 shows the multiple contrasts acquired on an 11yr old post-surgical male patient using the 0.6x0.9x2mm3 3D ME-GRE sequence. Both pre- and post-ferumoxytol as well as the difference images are shown. The high spatial resolution and high SNR of the 3D ME-GRE images allows the visualization of fine vascular detail. The blooming effect seen on the field map are blood products at the surgical resection site. The R2* difference maps are proportional to the cerebral blood volume fraction according to the steady-state perfusion theory[21]. The spatial resolution achieved here is however much higher than the one usually obtained using Dynamic Susceptibility Contrast approaches. Since the vasculature was suppressed on the post-ferumoxytol TOF images (likely due to the severe T2* shortening effect), the TOF difference images appear background suppressed – corresponding reasonably well with the regular TOF-MRA (Fig. 2). Conclusion: Here we show that the use of just one 5:44-minute 3D ME-GRE sequence and subsequent post-processing toolkit has the potential to reveal complementary image features, by providing multiple contrast mechanisms such as R2* maps, Field maps, SWI, QSM, and TOF-MRA. This sequence has the potential to be a surrogate for other single-sequence alternatives in clinical practice. Further work is needed to determine the extent to which these contrasts improve our understanding of normal tissue anatomy as well as changes in tissue in various pathological conditions. This might be particularly adapted to study vascular malformations or lesions with heterogeneous tissue components such as brain tumors. References: [1] Neuwelt EA et al. Neurosurgery 60(4), 601-611 (2007). [2] Hunt MA et al. AJNR 26(5), 1084-1088 (2005). [3] Neuwelt EA et al Neuropathology and applied neurobiology 30(5), 456-471 (2004). [4] Taschner CA et al, AJR. 185(6), 1477-1486 (2005). [5] Nighoghossian N et al, Stroke. 2007 38(2):303-7. [6] Saleh A et al. Brain. 2004 Jul;127(Pt 7):1670-7. [7] Simon GH et al. Investigative radiology 41(1), 45-51 (2006). [8] Daldrup-Link H, Coussens LM: Oncoimmunology 1(4), 507-509 (2012). [9] Christen T et al. Magn Reson Med. 2012. [10] Luo J et al. NeuroImage 60: 1073–1082 (2012) [11] Deistung A et al. JMRI 29:1478–1484 (2009). [12] Liu T et al. MRM 2013;69(2):467-76. [13] Kressler B et al. IEEE TMI 29(2):273-81 (2010) [14] de Rochefort et al. MRM 60(4):1003-1009 (2008). [15] Schofield and Zhu, Opt. Lett. 28:1194-1196 (2003). [16] Liu T et al. NMR Biomed 24(9):1129-36 (2011). [17] de Rochefort et al. MRM 63(1):194-206 (2010). [18] Liu J et al. Neuroimage 2012;59(3):2560-8. [19] Reichenbach JR et al. Radiology 204:272-277 (1997). [20] Haacke EM et al MRM 52:612-618 (2004). [21] Tropres et al. MRM 45:397-408 (2001).Acknowledgements: The authors are grateful to Pascal Spincemaille from Cornell University for his helpful direction. Supported in part by the National Institute of Health (NIH 1R01NS066506, NIH 2RO1NS047607, NCRR 5P41RR09784).

Fig. 1: Plural contrasts generated from one 3D ME-GRE sequence, both pre- and post ferumoxytol. Difference images are shown in the far right column.

Fig. 2: Regular TOF-MRA (scan time = 5 mins).

6755 Faster pediatric MRI

Samantha J Holdsworth1, Stefan Skare2, Kristen Yeom3, and Michael E Moseley1 1Lucas Center for Imaging, Department of Radiology, Stanford University, Palo Alto, CA, United States, 2Clinical Neuroscience, Karolinksa Institute, Stockholm, Sweden, 3Lucile

Packard Children's Hospital, Department of Radiology, Stanford University, Palo Alto, CA, United States

Target Audience: Researchers and clinicians who are interested faster pediatric MRI. Introduction: MRI provides excellent contrast between the different soft tissues of the body, which makes it especially useful in imaging brain pathology. The main disadvantage of MRI is that is lengthy, taking up to one hour at our institution. Particularly in a pediatric setting, long protocols increases the risk of motion artifacts in the acquired images, thus GA is often used – at the expense of patient throughput, comfort, and cost. With the goal of shortening the overall scan time of pediatric MRI, here we present preliminary data acquired with the use of four MR methods that have been built in-house and that can be retrospectively corrected for patient motion: a T1-weighted 3D Short-Axis Propeller Echo Planar Imaging (SAP-EPI) sequence1; a T2-weighted 3D SAP-EPI sequence2, a novel Fluid Attenuated Inversion Recovery (FLAIR) sequence using the Readout-Segmented (RS)-EPI trajectory3; and a dual-echo Diffusion-Weighted-Imaging (DWI) sequence4. The first three of these methods are faster than their conventional counterparts; and the latter can also deliver R2 maps for free.

Materials & Methods: 10 pediatric patients ranging from 1mo to 18 years old were scanned with the above sequences on a 3T GE system (Waukesha, WI) and an 8-channel head coil after informed parental consent and assent were obtained. The scan parameters were: dual-echo DWI: FOV = 22cm, TR/TE1/TE2 = 4000/48/115ms, acquisition matrix = 1922, in-plane acceleration factor (R) = 3, signal averages (NEX) = 3, slthck/gap = 4/0mm, 29 slices, 1 b=0, tetrahedral encoding with b=800 s/mm2, scan time = 1:12min. T1-w 3D SAP-EPI: matrix size = 1922, R = NEX = 3, TR/TE/FA = 46ms/9ms/50º, 64 z-partitions, slthk = 2mm, 7 blades of width 64, scan time = 1:03min. T2-w 3D SAP-EPI: matrix size = 2522, R = NEX = 3, TR/TE/FA = 62ms/22ms/20º, 64 z-partitions, slthk = 2 mm, 9 blades of width 48, scan time = 1:42min. FLAIR RS-EPI: matrix size = 1922, R=NEX=2, TR/TE/TI = 10000/40/2250ms, slthk/gap = 4/0mm, 5 blades of width 64, scan time = 1:45min. R2 maps were also calculated using the

dual-echo b=0 and b=800 s/mm2 images.

Results: Figure 1 shows images acquired with the proposed research sequences on a pediatric patient. The patient had prior resection of a right temporal lobe glioblastoma. Aside from reactive white matter signal abnormality from tumor treatment (arrow), no soft tissue or diffusion abnormality was seen to suggest residual/recurrent tumor. Discussion & Conclusion: We have demonstrated preliminary data showing the promise of the use of four sequences that generate some of the leading contrast mechanisms required for pediatric brain imaging. Together, the four sequences take 5:42min – faster than the sum of their conventional alternatives scanned at our institution (totaling ~14min). Future work will assess the inherent motion-correction capability of these sequences. We will then investigate whether these sequences have the diagnostic potential to replace the need for the longer scan protocol acquired at our institution in the pediatric setting. References: [1] Holdsworth, SJ et al. 17th ISMRM, Hawaii, U.S.A 1239 (2009). [2] Holdsworth SJ, et al. 17th ISMRM, Hawaii, U.S.A 756 (2009). [3] Porter D. 16th ISMRM, Toronto, Ontario, Canada 3262 (2008). [4] Holdsworth, SJ et al. 20th ISMRM, Melbourne, Australia, 649 (2012).

Fig. 1 – Proposed sequences acquired on a 4 year old male patient.

2390 Fluid attenuated inversion recovery (FLAIR) with readout-segmented (rs)-EPI

Samantha J Holdsworth1, Stefan Skare2, Kristen Yeom3, and Michael E Moseley1 1Lucas Center for Imaging, Department of Radiology, Stanford University, Palo Alto, CA, United States, 2Clinical Neuroscience, Karolinksa Institute, Stockholm,

Sweden, 3Lucile Packard Children's Hospital, Department of Radiology, Stanford University, Palo Alto, CA, United States

Target Audience: Researchers and clinicians who are interested in a fast FLAIR sequence. Introduction: The fluid attenuating inversion recovery (FLAIR) MRI method1 is an important technique for the differentiation of brain lesions. Conventional FLAIR uses the Fast-Spin-Echo (FSE) method for image acquisition. However, the combination of long inversion recovery (TI) times and the inefficient sampling of the echo times (TEs) result in prolonged scan times, posing a challenge for motion-prone patients. More rapid FLAIR imaging of the brain can be achieved using the half-Fourier acquisition single-shot turbo-spin (HASTE)-FLAIR and Echo-Planar imaging (EPI)-FLAIR sequences2. However these sequences have relatively poor image quality and reduced ability to show smaller lesions compared with FLAIR-FSE2. Here, we show preliminary data using a readout-segmented (rs)-EPI3,4 FLAIR implementation. Rs-EPI has reduced susceptibility-related artifacts compared with EPI, is faster than FSE sequences, and is relatively robust to motion5. Materials & Methods: All scans were performed on a 3T GE system (Milwaukee, WI, USA; G of 40 mT/m, slew rate of 150 mT/m/s) using an 8-channel head coil. FLAIR datasets were acquired on a 6-year old pediatric patient after written formal consent was obtained from the patient’s parents. The rs-EPI-FLAIR pulse sequence and k-space trajectory is shown in Fig. 1. The rs-EPI-FLAIR sequence imaging parameters were: matrix size = 1922, segment width = 64, TE = 48ms, acceleration factor = 2, signal averages = 2, 32 slices, scan time = 1:45min. Parallel imaging and Nyquist-ghost correction was performed on the center segment, with resulting calibration parameters applied to each segment5. rs-EPI segments were then stitched together using gridding. For reference, a conventional FLAIR-FSE was acquired (matrix size = 353 x 224, TEeff = 146 ms, 29 slices, scan time = 2:45min) and an EPI-FLAIR (matrix size = 1922, acceleration factor = 2, signal averages = 2, TE = 80ms, 32 slices, scan time = 21sec). All sequences used TR/TI = 10s/2.2s, FOV = 22cm, and slthck = 4mm. Results: Fig. 2 compares FLAIR-FSE, EPI-FLAIR, and rs-EPI-FLAIR images. FLAIR-FSE shows superior contrast with regards to white matter signal abnormality than EPI and rs-EPI. rs-EPI shows reduced blurring compared to EPI. Discussion: This abstract shows that rs-EPI-FLAIR produces images with improved effective resolution and reduced blurring compared with EPI-FLAIR. Compared with FLAIR-FSE, the white matter contrast of rs-EPI (and EPI) was limited, likely due to the shorter TE selected. The scan time came at a 5-fold increase compared with FLAIR-EPI and a ~1.5-fold decrease compared with FLAIR-FSE. However, a further ~2-fold reduction in scan time for EPI and rs-EPI sequences can be achieved by using only one signal average. Next we will deploy rs-EPI-FLAIR together with a navigator echo and test its motion-correction capability on a larger cohort of patients. Conclusion: Here preliminary data are presented on the clinical application of FLAIR-rs-EPI. While the contrast within the white matter of this implementation of FLAIR-rs-EPI needs improvement relative to the FLAIR-FSE, it has reduced susceptibility artifacts compared with EPI-FLAIR. With a better selection of imaging parameters (such as TE), rs-EPI-FLAIR may be a useful rapid and motion-correctable alternative to conventional FLAIR and EPI-FLAIR in the clinics. References: [1] De Coene B, et al. AJNR 1;13(6):1555–64 (1992). [2] Filippi M, et al. A. AJR. 20(10):1931–8 (1999). [3] Holdsworth SJ, et al. EJR 65(1):36-46 (2008). [4] Porter DA, Heidemann RM. MRM 62(2):468–75 (2009). [5] Holdsworth SJ, et al. MRM 62:1629–40 (2009).

Figure 2: Comparing the FLAIR FSE, EPI-FLAIR, and rs-EPI-FLAIR images acquired on a 6-year old patient. Note the right-edge artifact on the rs-EPI is an unexplained issue with the reconstruction.

Figure 1: (A) Pulse sequence timing diagram for the rs-EPI-FLAIR sequence. The RF pulses are shown in this order: inversion 180º, spectral-spatial 90º, 180º spin echo, and refocusing180º. (B) Resulting segmented k-space. The central segment (bold black) is used for the parallel imaging calibration.

Fig. 2: Comparison of (a) EPI and (b) RS-EPI simultaneous multislice isoDWI data acquired with fat-suppressive PINS pulses.

6353 Simultaneous Multislice Readout-Segmented Diffusion-Weighted EPI with Blipped-Controlled Aliasing

Samantha J Holdsworth1, Rafael O'Halloran1, Anh T Van1, Eric Aboussouan1, William A Grissom2, Anuj Sharma2, Murat Aksoy3, Julian R Maclaren3, Stefan Skare4, and Roland Bammer3

1 (Equal contribution): Center for Quantitative Neuroimaging, Department of Radiology, Stanford University, Palo Alto, CA, United States, 2 (Equal contribution): Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States, 3Center for Quantitative Neuroimaging, Department of Radiology, Stanford

University, Palo Alto, CA, United States, 4Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden

TARGET AUDIENCE: For those interested in reducing distortion and reducing scan time in diffusion-weighted imaging. INTRODUCTION: Readout-segmented EPI (RS-EPI) is a promising candidate for reducing distortion in diffusion-weighted (DW)-EPI while being robust to motion-induced phase errors. However, the requirement of several adjacent segments (or 'blinds') in RS-EPI can make the scan time can prohibitively long, particularly for thin slices which require a large number of slices to achieve full brain coverage. A promising approach for reducing scan time is to use multi-band acquisitions – which make diffusion imaging with full brain coverage faster and more SNR-efficient by simultaneously acquiring multiple slices with limited g-factor penalty [1]. In this work, we reduce the minimum TR in RS-EPI with the use a simultaneous multislice acquisition using PINS multiband pulses [2] coupled with blipped-controlled aliasing [1]. METHODS: Acquisition – A multiband RS-EPI scan was performed on a healthy volunteer using a 3T GE system (GE 750) and a 32-channel head coil. Two slices separated by 8 cm were excited simultaneously using PINS excitation and refocusing pulses [1]. The PINS pulses are essentially a series of hard pulses spaced by 1/Δ in k-space, that excite and refocus a set of slices separated by a distance Δ. Here the separation of 8 cm was designed such that only 2 slices were excited in the z-FOV at once. Inherent fat suppression was achieved by using positive slice select gradients and negative refocusing slice gradients such that the bands of fat selected and refocused moved in opposing directions in z and thus did not intersect (Fig 1). For RS-EPI the navigator echo was acquired after a second 180° PINS refocusing pulse with negative polarity (Fig 1). Gz-blips were applied during the imaging and navigator readouts to shift the slices by FOV/2

and better exploit the coil sensitivity [1]. The following scan parameters were used for multiband RS-EPI: Stejskal Tanner diffusion preparation with xyz encoding (b = 1000 s/mm2), one b=0, matrix size = 1282, TR = 4s, 5 blinds of width 64, TE1 /TE2 = 63ms/110ms, FOV = 24cm, slthck/gap = 5 mm/0mm, and a scan time of 1:20min. For the slice-grappa calibration a b=0 scan (of the center blind only) was acquired by replacing the PINS 180° pulses with standard sinc pulses. EPI multiband (and calibration) data were acquired at the same target resolution. Reconstruction – The center imaging blind from the b=0 calibration and multiband image underwent FOV/2 ghost parameter estimation (image entropy-based approach) – followed by application of ghost parameters to all acquired blinds. The multiband imaging and navigator blinds were then unaliased using the calibration scan with a slice-grappa approach [1]. For RS-EPI, the imaging blinds were individually phase corrected (using the navigator blind) and were gridded together to form the final image. RESULTS: Fig. 2 shows multiband EPI and RS-EPI DWI data acquired on a volunteer. As expected, RS-EPI DWI images show better geometric fidelity than EPI. Note that the simultaneously excited slices appear in the same image (Fig 2 left column) with one slice aliased to FOV/2 due to the alternating blips in z. After the slice GRAPPA reconstruction (Fig 2 right column) both slices appear unaliased effectively providing the acceleration factor of 2. DISCUSSION AND CONCLUSION: One of the biggest concerns about the application of RS-EPI to DWI/DTI is the scan time, particularly for high-resolution applications which require a large number of slices and thus a long TR. One can get an extra ~2-fold acceleration of the imaging sequence with the use of simultaneous multislice approaches, and here we demonstrate that it is feasible to combine RS-EPI with this approach. Further scan efficiency was achieved by shifting the fat slice in opposite directions during the excitation and refocusing steps – removing the need for an upfront chemical saturation pulse. Further acceleration in RS-EPI can be achieved with the use of homodyne reconstruction in the kx-direction [3]. Here we show that one can accelerate RS-EPI DWI scans with the use of a fat-suppressive blipped-controlled multislice approach. References: [1] K Setsompop, et al. MRM 2012;67:1210–1224. MRM 68:441–451 (2012) [2] DG Norris et al, MRM, 66:1234-1240, 2011. [3] R Frost et al, MRM, 68:441–451 (2012). Acknowledgements: NIH (2R01 EB00271108-A1 , 5RO1 EB008706, 5R01 EB01165402-02), the Center of Advanced MR Technology at Stanford (P41 EB015891), Lucas Foundation, Oak Foundation.

Fig. 1: Pulse timing diagram of the multi-band RS-EPI trajectory. The multiband data is acquired using a PINS 90° and 180° pulse which selects two slices simultaneously. In RS-EPI each imaging blind is accompanied by a navigator blind in order to perform a phase correction between diffusion-weighted blinds. Note that the calibration scan used to perform the slice-grappa reconstruction is acquired using a pins 90° and standard 180° sinc pulse which selects one slice only.

Fig 3: 69yr patient with vasospasm. The R2 map brings out the hypointense signal associated with infarct (open arrow) as well as areas of hyperintense signal correlating with intraventricular hemorrhage(arrowhead) and basal ganglia calcification (closed arrow).

Fig. 2: Dual echo DWI and ADC images of a 66yr old embolic stroke patient.

Fig. 1: The dual-echo EPI sequence, with GRAPPA factor = interleaves = 3, FOV = 24cm, matrix = 1922, slthk/gap = 5mm/1.5mm, 24 partial Fourier overscans, TE1/TE2 = 48/105ms, 1b0/4directions, b=1000s/mm2, TR=3s, scan time 2:30min. With the set of imaging parameters used here, this approach does not increase the scan time compared to the single echo alternative since Echo 2 fills in the sequence dead-time.

6053 Dual-echo diffusion-weighted EPI for better sensitivity to acute stroke

Samantha J Holdsworth1, Stefan Skare2, Kristen Yeom1, Michael U. Antonucci1, Jalal B Andre3, Jarrett Rosenberg1, Matus Straka1, Nancy J Fischbein1, Greg Zaharchuk1, and Roland Bammer1

1Department of Radiology, Stanford University, Palo Alto, CA, United States, 2Karolinska Institute, Clinical Neuroscience, Stockholm, Sweden, 3Department of Radiology, University of Washington, Seattle, WA, United States

Target audience: Practitioners interested in improving diffusion lesion conspicuity in the setting of acute stroke. Introduction: Many diffusion-restricting lesions also have a prolonged T2 value compared to the surrounding tissue. We hypothesize that one may improve lesion conspicuity in acute stroke patients with the use of a longer TE than in conventional practice by means of an accelerated dual-echo diffusion-weighted (DW)-EPI approach (Fig. 1). Echo 1 provides a high SNR image used to calculate the apparent diffusion coefficient (ADC), while Echo 2 can be used for enhanced conspicuity. Furthermore, relaxivity (R2) maps can be calculated from the dual echo images to potentially reveal an additional source of image contrast. This study investigated the applicability of such a dual-echo sequence in the setting of acute stroke.

Methods: Dual-echo

DWI data were acquired on 50 patients suspected of stroke using a 1.5T GE scanner and 8-ch head coil. Three radiologists reviewed the echoes using the routine vendor-supplied DWI as a reference. Images were graded on lesion conspicuity and diagnostic confidence on the following Likert scale: 1–nondiagnostic, 2–poor, 3–acceptable, 4–standard, 5–above average, 6–very good, 7–outstanding. R2 maps calculated from the two echoes were evaluated for potential complementary information. Tests for differences in ratings between Echo 1 and Echo 2 were done with a two-tailed Wilcoxon signed-rank test. Results: Echo 2 was unanimously favored over Echo 1 for the evaluation of acute infarcts. Lesion conspicuity and diagnostic confidence were rated better for Echo 2 over Echo 1 (mean values of 6.5/4.9 and 5.9/5.4, respectively p<0.0001). 72 more lesions were found on Echo 2 across 34 patients diagnosed with acute stroke than on Echo 1. 93% of these were deemed as acute infarct on ADC, 4% were too small to assess, and 3% were non-restricting chronic lesions. Echo 2 was predicted to have changed the overall radiological impression in 20% of cases; and to have impacted stroke workup in 16% of cases, and potentially influenced 32% of cases. As shown in Fig. 3, while the

DWI of Echo 2 has higher lesion sensitivity, the ADC of Echo 1 is the best candidate for confirming acute lesions. Echo 2 was also favored for ruling out stroke from regions of heightened coil sensitivity (closed arrows). The R2 maps were also useful for detecting ischemic infarct, subarachnoid hemorrhage and basal ganglia calcification (Fig. 3). Discussion: Longer TEs than those typically used can increase the diagnostic sensitivity of DWI. Given that the DWI from Echo 2 was more useful for lesion delineation and detection, we recommend that the TE should be exploited to draw attention to lesions, and that the accelerated dual-echo EPI DWI approach is a good candidate.

Conclusion: Contradicting the common teaching to use short echo times to avoid T2-shine through, the long TE of Echo 2 gives rise to DW images with superior conspicuity of diffusion lesions compared to DW images acquired at a shorter TE or conventional T2-weighted imaging alone: Echo 1 provides high SNR ADC maps for specificity in acute stroke, and the information from both echoes is a potential source of complementary information for the assessment of blood and mineralization products. In conclusion, using the minimum TE to achieve maximum SNR and avoid T2-shine through may result in increased identification of stroke-related lesions on DWI, and a dual-echo approach should be considered when protocoling DWI scans in stroke patients. Acknowledgements: NIH (2R01 EB00271108-A1 , 5RO1 EB008706, 5R01 EB01165402-02), the Center of Advanced MR Technology at Stanford (P41 EB015891), Lucas Foundation, Oak Foundation.

Fig. 2 - Patient data acquired on an 88yr old male stroke patient. (a) Coil sensitivity-corrected isotropic DWI (b=1000s/mm2) dual echo images showing increased lesion conspicuity on the second echo (white arrows). (b) Single slice from the same dataset showing the isotropic ADC calculated from the b=0 and DWI images from echo 1 (top) and echo 2 (bottom), respectively. The isoDWI echo 2 may be useful for lesion conspicuity, while isoADC echo 1 could be used for its higher SNR.

GRAPPA-accelerated dual-echo diffusion-weighted EPI with intensity correction Samantha J Holdsworth1, Stefan Skare2, Matus Straka1,3, Manabu Inoue3, and Roland Bammer1

1Department of Radiology, Stanford University, Palo Alto, CA, United States, 2Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden, 3Stanford Stroke Center, Stanford University Medical Center, Stanford University, Palo Alto, CA, United States

Introduction: A well-known problem with standard single-shot (ss)-EPI for diffusion-weighted imaging (DWI) is geometric distortion and blurring. These artifacts can be reduced through the use of parallel imaging. The shortened readout also affords a shorter echo time - which reduces T2-shine through, but may result in reduced lesion conspicuity on DWI. Thus, in an attempt to both improve the image quality and retain the sensitivity of lesions through longer echo times, here we implement a GRAPPA-accelerated1,2, dual echo3 EPI DWI sequence on stroke patients and present our preliminary data. For cases of absent coil sensitivity calibration scans, we also demonstrate how the two echoes can be utilized to remove array coil-induced intensity modulations, which are often confused as potential ischemically challenged regions. Methods: Patient data was collected on 15 patients suspected of stroke using a 1.5T GE system and an 8-channel head coil. The following scan parameters were used: Stejskal Tanner diffusion preparation with tetrahedral encoding (b = 1000s/mm2) and one b=0, matrix size = 192 x 192, GRAPPA acceleration factor R = 3 and 3 interleaves (used for the ghost- and GRAPPA-weights estimation as well as to boost SNR), NEX = 2, TR = 3s, TE1/TE2 = 51ms/115ms, FOV = 24cm, slthck/gap = 5 mm/1.5mm, and a scan time of 2:15min. The first and second echo were corrected for signal intensity variation across the images using the following: for 1,2 Eq. 1 where Dci represents each corrected echo image, Di are the original echo images, CF is the Gaussian-filtered contribution of, C, given by:

∑ where log log Eq. 2 and C represents contributions to the signal intensity from coil sensitivity, proton density, original magnetization, and RF; and for the two echoes: t = TE, I are the b=0 images, D are the DWI images. Results: Fig. 1-2 shows GRAPPA-accelerated dual-echo EPI patient data acquired on two patients with strokes of the middle cerebral artery (MCA). The increased lesion conspicuity of echo 2 is apparent. Fig. 2b shows coil sensitivity-corrected maps, which remove the hyperintensity of the signal - particularly in the posterior regions where cortical regions are closer to individual coil elements. Fig. 2 shows patient data where the second echo on isoDWI provided increased diagnostic confidence. Fig. 2b shows isotropic ADC maps calculated from echo 1 and 2, suggesting that the first echo should always be used for its higher SNR. Discussion: Here we show that GRAPPA-accelerated DWI can be made even more applicable in a clinical setting with the acquisition of a second echo in the same TR. While the first echo can be used for high SNR ADC maps, the second echo can be used for lesion detection (Fig. 1-2). The use of the second echo for lesion detection goes against the common teaching that TE should be kept short to reduce T2-shine through. While this might be true for differentiating between acute and subacute lesions, for general lesion conspicuity longer echo times may yield greater diagnostic confidence. Interestingly, on long-TE DWIs, the combined effect of diffusion restriction and prolonged T2 gives additional contrast that is not necessarily observed on long TE T2-w FSE scans or FLAIR alone. The added information from quantitative ADC and T2 will further the ability to differentiate between acute and subacute lesions. In addition, the two echoes can be used to remove the contribution of coil sensitivity which can lead to misdiagnosis (since hyperintensity around the cortex on DWI can indicate pathology such as stroke, encephalitis, Creutzfeldt-Jakob disease, and epilepsy). This bias field removal may also improve automated

segmentation procedures such as used for diffusion-perfusion-mismatch calculation4. One could argue that a calibration scan could be acquired for coil-sensitivity correction - however this comes at an additional scan time cost. With the set of imaging parameters that we routinely use for our stroke protocol at our institution, the dual-echo DW-EPI approach does not increase the scan time since the second echo fills in the dead-time of the sequence.

Conclusion: Here we show that by observing DWI images acquired at two echo times, complementary information can be gleaned, at no additional scan time cost. In addition, the two echoes can be used to remove the coil sensitivity contribution to the DWI images, which may provide clinical confidence and will improve the performance of automated segmentation procedures used to suggest treatment outcome for stroke patients. References: [1] Griswold, M. et al. MRM 2002;47:1202-1210. [2] Qu, P. et al. JMR 2005;174(1):60-67. [3] Feinberg, D. et al. MRM 1994:31:461. [4] Straka, M. et al. JMRI 2010;32:1024. Acknowledgements: This work was supported in part by the NIH (5R01EB002711, 5R01EB008706, 3R01EB008706, 5R01EB006526, 5R21EB006860, 2P41RR009784), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, Oak Foundation, and the Swedish Research Council (K2007-53P-20322-01-4). An extra special thanks to Patricia Lassus, Murat Aksoy, and Nancy Fischbein for their insights.

Fig. 1: Data collected on a 91 yr old male stroke patient (a) Original dual echo images, and (b) the dual echo images with contribution from coil sensitivity, proton density, initial magnetization and B1 removed (as in (c)). The corrected images rule out any suspicion of posterior lesions (white arrows). Note the increased contrast of the stroke lesions on echo 2. (d) Relaxivity maps calculated from the average contribution of the T2-w and DWI dual-echo images.

649Proc. Intl. Soc. Mag. Reson. Med. 20 (2012)

Comparison between EPI and RS-EPI at high acceleration factors Samantha J Holdsworth1, Anh T Van1, Stefan Skare2, and Roland Bammer1

1'Center for Quantitative Neuroimaging, Department of Radiology, Stanford University, Palo Alto, CA, United States, 2Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden

Introduction: Readout-Segmented EPI (RS-EPI) [1] has been proposed in a number of studies (including several of our own) as a variant of EPI to reduce distortion in diffusion-weighted (DW) neuroimaging [1-3]. RS-EPI segments k-space into individual EPI ‘blinds’ along the readout direction, and requires an additional navigator blind (for phase correction of the off-center DW blinds). With the increasing number of coils coming available with advanced phased-array technology that increases the capacity of EPI to achieve higher acceleration factors (Fig. 1), and advanced distortion-correction methodology (such as the Reversed Gradient Polarity method (RGPM) [4,5]), we suspect that the utility of RS-EPI is perhaps more tailored to ultra-high resolution DWI. An initial qualitative demonstration of this is shown here, with EPI and RS-EPI data acquired with the highest acceptable GRAPPA [6,7]-acceleration factor that we have been using with our 32-channel coil.

Methods: Experiments were conducted on a 3T GE system (Gmax=50mT/m, Smax=200 mT/m/ms) and a 32-channel head coil channel (Nova Medical, Wilmington, MA, USA). In order to find a maximum GRAPPA acceleration factor, R, achievable with our set-up, scan-time matched EPI DWI datasets were acquired first on both a QA agar phantom and a human volunteer using acceleration factors of R = 1-6. With the selection of R = 5 as an acceptable choice of acceleration factor for EPI (Fig. 2), a distortion-matched RS-EPI dataset was acquired using R=2, as well as R=5 dataset. The following common parameters for EPI and RS-EPI were: twice-refocused diffusion preparation with x,y,z diffusion encoding, b = 1000s/mm2, one b = 0, a target resolution of 240 x 240, slice thickness = 5mm, TE/TR = 70ms/4000ms, FOV = 24 cm, partial Fourier encoding with 24 overscans. RS-EPI used 5 blinds of width 54. All scans were scan time matched (by using a larger NEX for EPI). For each dataset, a b = 0 image was acquired with an opposite phase-encoding gradient to enable subsequent distortion correction using the RPGM method.

Results: A comparison between the distortion- and scan-time matched EPI (R = 5) and RS-EPI (R = 2) datasets are shown in Fig. 3a-b. Despite the longer readout for EPI, the extent of image blurring appears to be similar between the two datasets thanks to the higher acceleration factor and hence larger step through phase-encoding k-space. However, because RS-EPI only uses the central (54 x 240) segment of k-space to estimate the GRAPPA weights, there appear to be residual GRAPPA noise in some slices (white arrows, Fig. 3b). As one moves to the highest acceleration factor capable with our system (achievable with EPI), the RS-EPI datasets are slightly less distorted, but become significantly noisier. Furthermore, since RS-EPI is essentially a multi-shot technique, the quality of the diffusion-weighted images relies on the robustness of the phase error correction. At very high acceleration factor, the low SNR of images reconstructed from individual blinds, especially the edge blinds, might negatively impact the phase correction procedure, resulting in poor quality images. Fig. 4 compares the original b = 0 images with those corrected for distortion using the RPGM method. Discussion & Conclusion: With the advent of more advanced phased-array head coils, an increasing maximum slew rate achievable by gradient coils, the image quality of standard EPI is becoming much improved. For standard clinical imaging EPI is likely to be the method of choice for its speed and high SNR, while RS-EPI may still have application to ultra-high resolution diffusion imaging at high field strengths [3] where scan time is not as critical. As shown in Fig. 4, with acceleration factors of R = 5 achievable with EPI, the residual distortion provides a good starting point for distortion correction methods (such as RGPM). Furthermore, the gain that one gets using RS-EPI with R = 5 in terms of reduced distortion is rather small and, in addition, much poorer image quality results due to the smaller central strip used for the

GRAPPA estimation. In fact, as this abstract has made apparent, a more robust GRAPPA estimation procedure may be required (such as the use of adjacent blinds), as GRAPPA noise in the RS-EPI images is visible with R = 2, and considerable with R = 5. A separate calibration scan could remedy this, but would have an additional scan time cost (in addition to the extra blinds required to fill k-space). RS-EPI has a number of additional practical limitations, including gaps in k-space (between blinds) in the presence of large motion; eddy current effects between blinds (due to the different kx-dephasing gradient) on poorly calibrated systems; and the requirement for an additional navigator reduces the number of slices that can be acquired per TR. References - [1] Porter D, MRM, 62:468, 2009. [2] Holdsworth, S et al. MRM, 62:1629, 2009 . [3] Heidemann et al. MRM, 64:9-14, 2010. [4] Andersson JL. Neuroimage 2003;20(2):870-888. [5] Skare S ISMRM 2010. [6] Griswold MA. et al. MRM 2002;47:1202-1210. [7] Qu P. et al. JMR 2005;174(1):60-67.

Fig. 1 - EPI and RS-EPI k-space traversal. A schematic representation of the k-space trajectory for EPI and RS-EPI for (a) smaller acceleration factors, and (b) larger acceleration factors achievable through the use of coils. The utility of RS-EPI is significantly reduced with increasing R since it results in a smaller scan time.

Fig. 3 - Isotropic DWI images acquired using (a) EPI with R = 5, (b) RS-EPI with R = 2 (distortion-matched with (a)), and (c) RS-EPI with R = 5. The white arrows depict regions where GRAPPA noise affects the image quality in RS-EPI. The red arrows depict regions of slightly reduced distortion achievable with RS-EPI R = 5.

Fig. 2 - DWI datasets acquired at 3T using a 32-channel head coil. (a) GRAPPA fit error calculated for R = 2-6 b=0 datasets on a QA agar phantom. From R = 5-6 the GRAPPA fit error begins to increase considerably. (b) b=0 images acquired on a volunteer using no acceleration (R=1) and with acceleration. The R = 2-5 images are reconstructed with GRAPPA. The R = 5 image retains good image quality and thus is the acceleration factor we chose for our EPI versus RS-EPI comparison.

Fig. 4 - Comparison of original and distortion-corrected b = 0 images acquired with EPI R = 2, RS-EPI R=2, and RS-EPI R=5. The acquisition matrix = 240x240.

4212Proc. Intl. Soc. Mag. Reson. Med. 20 (2012)

6619 Fast Susceptibility Weighted Imaging (SWI) using Readout-Segmented (RS)-EPI

S. J. Holdsworth1, R. O'Halloran1, S. Skare2, and R. Bammer1

1Department of Radiology, Stanford University, Palo Alto, CA, United States, 2Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden

Introduction: Susceptibility-weighted imaging (SWI) is an MRI technique that has been used to provide improved conspicuity of venous blood vessels and other sources of susceptibility effects [1,2]. The most commonly used SWI acquisition uses a 3D gradient echo (GRE) sequence, however due to the inefficient coverage of k-space per TR, 3D GRE suffers from a long scan time. In addition, even subtle motion in 3D GRE can considerably hamper the quality of final processed SWI image. A 3D EPI trajectory has been used as a faster alternative for SWI [3]. Unless 3D EPI is acquired with multiple interleaves (which consequently would also make it prone to motion artifacts), the images can suffer from significant blurring and geometric distortion. 3D Short-Axis Propeller (SAP)-EPI [4] has been proposed as a method to minimize distortion and blurring compared to 3D EPI for SWI, whilst keeping the scan time at a level appropriate for regular clinical use. A disadvantage of 3D SAP-EPI is the blurring that results from the combination of several EPI segments acquired at different angle. Readout-Segmented (RS)-EPI [5] is a similar technique to SAP-EPI, except that rather than acquiring several overlapping angular segments, adjacent overlapping segments are acquired. Since the segments are all acquired at the same angle, this results in reduced blurring in the final gridded image. Here we implement 3D RS-EPI as an alternative to 3D GRE and 3D SAP-EPI for SWI. Methods: The 3D RS-EPI k-space trajectory is shown in Fig. 1. Experiments were conducted on a healthy volunteer using a 3T GE system and an 8-ch head coil. The following scan parameters were used: matrix size = 288 x 288, 7 blinds of width 64, R = 3, NEX = 3, TR/TE/FA = 55ms/20ms/15º, FOV = 23 x 23 x 12.8cm3, 64 z-partitions, a 2 mm slice thickness, brick frame rate = 3.5s, and a scan time of 1:15min. For comparison a 3D SAP-EPI scan was acquired with equivalent scan parameters (1:15min scan time). A high resolution flow-compensated 3D GRE sequence was acquired for comparison using a matrix size = 512 x 256, rectangular FOV = 0.75, TR/TE/FA = 37ms/20ms/20º, z-partitions = 32, 2mm slice thickness, and a scan time = 4:40mins. All SWI images were produced by generating a phase mask using a 2D Hanning window for each individual coil, a multiplication of the phase mask by the magnitude coil by 5 times, followed by the sum of squares over coils. A minimum intensity projection (MinIP) was then taken over a 14mm thick stack of partitions.

Results: A comparison between the SWI images acquired with 3D GRE and 3D RS-EPI is shown in Fig. 2. Although the resolution and SNR is highest for the 3D GRE, the 3D RS-EPI images show that it is possible to acquire good quality SWI images with twice the brain coverage in about a third of the scan time. Fig. 3 shows a comparison between the SWI MinIPs for both 3D RS-EPI and 3D SAP-EPI acquired at the same target resolution and scan time. Because of the unidirectional distortion in 3D RS-EPI, it demonstrates better vessel conspicuity than 3D SAP-EPI. Discussion & Conclusion: Here we have shown that 3D RS-EPI is a fast alternative technique to 3D GRE for SWI (Fig. 2). The acquisition of 3D RS-EPI SWI images in 1:15min makes this technique applicable for routine use in the clinics. Parallel imaging with R = 3 was used in order to minimize distortion, whilst keeping each blind consistent (i.e. inter-blind motion is negligible). One can also reduce the scan time for 3D GRE for SWI through the use of parallel imaging, but our experiments have shown that this can come at a significant detriment to the SNR (data not shown). In addition, this study demonstrated superior resolution and conspicuity when using 3D RS-EPI over 3D SAP-EPI (Fig. 3). Even subtle motion can be a major problem for standard SWI imaging, as it can corrupt the phase image used for the SWI

processing. Due to the consistency of data within each brick, both 3D RS-EPI and 3D SAP-EPI image phase are significantly less sensitive to motion compared with both GRE and interleaved EPI. Furthermore, the small temporal footprint of the bricks (3.5s) for 3D RS-EPI makes it much easier than GRE to catch moderate motion and reacquire data if necessary. In addition, for jerky movement, as long as the brick frame rate in 3D RS-EPI is fast enough and there is enough overlap between bricks (to account for rotations of individual bricks), it may be possible to correct for motion between bricks in k-space in 3D. Future work will explore this claim. Further studies are warranted to perform a detailed comparative assessment of both 3D RS-EPI and 3D SAP-EPI methodologies to assess whether the (already demonstrated) motion-robust self-navigated 3D SAP-EPI is truly needed when the better resolved 3D RS-EPI can handle motion to an acceptable level as demonstrated in this study. Overall, the minimum gain in small vessel conspicuity of 3D GRE does not appear to justify the almost 4-fold longer scan time at half the coverage in cervico-caudal direction. References: [1] Reichenbach JR. Radiology 1997;204:272-77. [2] Hacke EM. MRM 2004;52:612-18. [3] Patel MR. Stroke 1996;27:2321–2324. [4] Holdsworth SJ. ISMRM 2009; 756. [5] Porter D. ISMRM 2008;3262. Acknowledgements: NIH (5R01EB002711, 5R01EB008706, 3R01EB008706, 5R01EB006526, 5R21EB006860, 2P41RR009784), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, Oak Foundation, and the Swedish Research Council (K2007-53P-20322-01-4).

Fig. 1: 3D RS-EPI k-space trajectory. One segment (or blind) is acquired for every z-partition – resulting in one ‘brick’. Multiple adjacent overlapping bricks are acquired (overlap not shown for clarity).

Fig. 3: Two slices from a 3D GRE and 3D RS-EPI sequence acquired with a matrix size of 512 x 256 and 288 x 288, respectively, and a partition thickness of 2mm and a FOV of 23cm. A 14mm thick MinIP is also shown. As depicted schematically on the far right, 3D RS-EPI acquired full brain coverage (twice the coverage compared with 3D GRE) in a significantly reduced scan time.

Fig. 3: (a) 3D RS-EPI, (b) 3D SAP-EPI SWI MinIP images acquired with the same scan time (1:15min). RS-EPI shows less blurring and better vessel conspicuity than SAP-EPI.

6571 Comparison of two alternative approaches for diffusion-weighted Readout-Segmented (RS)-EPI

S. J. Holdsworth1, S. Skare2, M. Aksoy1, R. O'Halloran1, and R. Bammer1

1Department of Radiology, Stanford University, Palo Alto, CA, United States, 2Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden

Introduction: Readout-segmented (RS)-EPI is a technique that has been used for reducing distortion in diffusion-weighted imaging (DWI) [1], whereby multiple EPI segments are used to fill up k-space (Fig. 1). Two alternatives have been described for filling k-space in RS-EPI: one recently demonstrated to reduce scan time by filling k-space with full readout segments (Fig. 1a) [2], and the other which minimizes the echo time (TE) through the use of partial readout segments (Fig. 1b) [3]. In first example, only three segments are acquired (requiring a full echo), with partial Fourier reconstruction performed in the kx direction (labeled ‘RS-EPI-X’). In the second example, five partial readout segments are used to fill up k-space, with partial Fourier encoding performed in ky (labeled ‘RS-EPI-Y’). Here we explore whether one gains from reducing the number of segments at the expense of a longer TE (RS-EPI-X), or from having a larger number of segments at the minimum TE (RS-EPI-Y). We performed an SNR comparison for the two approaches, comparing the SNR for both single- [4] and twice refocused [5] diffusion preparation, the latter which is commonly used to reduce the effects of eddy currents in diffusion imaging. Materials & Methods: GRAPPA-accelerated DW RS-EPI-X and RS-EPI-Y images were acquired on a healthy volunteer on a 1.5T whole-body GE system using an 8-channel head coil. Both single-refocused (1 x 180) and twice- refocused (2 x 180) DW preparation schemes were tested, together with two matrix sizes: (192 x 192, blind width = 48, number of overscans = 24) and 288 x 288 (blind width = 64, number of overscans = 32). The TE and maximum number of slices are reported in Table 1. Other parameters were: acceleration factor R = 3, NEX = 3, slice thickness = 5 mm, FOV = 24 cm, b = 1000 s/mm2, and TR = 3s. For SNR measurements, noise maps generated from three repeated b = 0 scans, and the SNR normalized for scan time efficiency ( / scan time/sliceη = SNR ) was calculated over 20 slices. For the post-processing stage, the

ghost calibration [6] and GRAPPA weights [7-8] were calculated from the central segment of first b = 0 scan and applied to each volume, followed by ramp sampling correction, POCS reconstruction [9-10], and sum-of-squares over coils.

Results: Table 1 shows the normalized SNR ratio ( Yη / Xη ).There

was no significant difference in normalized SNR for all cases except for the matrix size of 288 x 288 with the 2 x 180 diffusion preparation scheme. Human brain data showing scan time matched b = 0 and isotropic DW images for the matrix size of 288 x 288 and two diffusion preparation schemes are shown in Fig. 2. The effect of the SNR reduction for RS-EPI-X for 2 x 180 is particularly pronounced in isotropic DWI images. Note that the longer TE of the RS-EPI-X scheme resulted in b = 0 images with greater T2-weighting.

Discussion: Here we explored the SNR difference between two alternative RS-EPI techniques. While fewer segments are required for RS-EPI-X, the combination of the longer echo train and resulting reduction in the number of slices that can be acquired per TR reduces its scan time efficiency more than originally expected. The scan time efficiency was similar for all but one case tested here: the case of RS-EPI-Y with a 2 x 180 and 288 x 288 matrix size was a factor of 1.6 times more efficient – clearly evident in the isotropic DW images of Fig. 2. This is due to the excessively long TE brought about by the longer echo train for 2 x 180 RS-EPI-X. While it is reasonable to assume that the need to only acquire 3 segments (instead of 5) in RS-EPI-X (in this particular example) implies that one can scan faster, for most clinical purposes one needs to average several times to keep the SNR for DW RS-EPI at a reasonable level, so the scan time advantage of RS-EPI-X can be misleading. At our institution we use 2 x 180 DW preparation for the acquisition of reliable FA maps, and often acquire these with matrix sizes of 288 x 288 – thus RS-EPI-Y would be the best choice of implementation. Furthermore, as one moves to higher matrix sizes one can expect that RS-EPI-Y will become even more efficient, as the TE does not increase with matrix size.

References: [1] Porter D et al. ISMRM 2008;3262. [2] Frost R et al. ISMRM 2010; 1625. [3] Holdsworth SJ et al. ISMRM 2008;4. [4] Stejskal EO. J. Chem. Phys. 1965;43(10):3597–3603. [5] Reese TG et al. MRM 2003;49:177–82. [6] Nordell A et al. ISMRM 2007:1833. [7] Griswold M et al. MRM 2002;47:1202-1210. [8] Qu P. et al JMR 2005;174(1):60-67. [9] Haacke EM et al. JMR 1991;92:126–45.[10] Liang ZP et. al. MRM 1992;4:67–185. Acknowledgements: This work was supported in part by the NIH (5R01EB002711, 5R01EB008706, 3R01EB008706, 5R01EB006526, 5R21EB006860, 2P41RR009784), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, Oak Foundation, and the Swedish Research Council (K2007-53P-20322-01-4).

Blind width x final resolution

RS-EPI-X (1 x 180 / 2 x 180)

RS-EPI-Y (1 x 180 / 2 x 180)

/Y Xη η (1 x 180 / 2 x 180) TE (ms) Max. # slices TE (ms) Max. # slices

48 x 192 67/90 24/20 55/70 29/25 1.0/1.1 64 x 288 83/128 17/13 55/70 24/20 1.1/1.6

Table 1: Echo time (TE) and maximum number of slices achievable in a TR = 3s for RS-EPI-X and RS-EPI-Y. The SNR ratio (RS-EPI-Y/RS-EPI-X) is also shown.

Fig. 1. The two alternative approaches for RS-EPI (a) fully sampled segments in the ky direction, i.e. a full echo acquired with partial Fourier encoding in kx (b) partially sampled segments in the ky direction, i.e. minimizing the TE, which therefore requires partial Fourier reconstruction in the ky direction.

Fig. 2. Scan-time matched RS-EPI-X and RS-EPI-Y b = 0 and isotropic DW images of a healthy volunteer, acquired with 1 x 180 and 2 x 180 at a matrix size of 288 x 288.

6512 Diffusion Weighted Imaging of Spinal Tumors with Reduced Field of View EPI

S. J. Holdsworth1, R. O'Halloran1, K. Yeom1, M. Aksoy1, S. Skare2, and R. Bammer1

1Department of Radiology, Stanford University, Palo Alto, CA, United States, 2Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden

Introduction: At our institution, there is a great need for diffusion-weighted (DW) and diffusion-tensor (DT) imaging of the spinal cord for the assessment of cord lesions, including tumors, cysts, post traumatic cord contusions, as well as congenital anomalies. While DWI can provide insight into the nature of cord lesions, such as ischemia, infectious or toxic-metabolic processes, neoplasms, and dermoids/epidermoids, the relationship between these lesions and spinal tracts are difficult to define. DTI could further probe biology of the underlying lesion, elucidate integrity and location of the spinal tracts, reveal otherwise occult lesions, and potentially aid in surgical navigation. However, due to the geometric distortion that arises from the slow phase-encoding bandwidth in echo-planar imaging (EPI), our radiologists have largely given up on spinal cord diffusion imaging using conventional single-shot DW-EPI. The zonally oblique multislice (ZOOM)-EPI technique [1-3] is an approach which uses a tilted refocusing pulse to reduce the phase-encoding FOV, thus reducing geometric distortion and image blurring. Here we demonstrate the feasibility of ZOOM-EPI for assessing spinal tumors at 1.5T and 3T. To demonstrate the potential for further improvements in this technique we also present distortion-corrected images acquired on a healthy volunteer at 3T.

Methods: DTI datasets were acquired on a 1.5T and 3T whole-body GE system. Both magnets used a 4-channel spine coil. ZOOM-EPI DTI datasets were acquired on two patients: a 5 year old male with a suspected thoracic cord neoplasm (3T, FOV = 22cm x 5.5cm, matrix size = 224 x 56) and a 35 year old female with cervicomedullary neoplasm (1.5T, FOV = 18cm x 4.5cm, matrix size = 192 x 48). Imaging parameters common to both patients were: TR = 3s, seven slices with 3mm thickness and no gap, zoom-angle θ = 10º, TE/TR = 73ms/3s, partial Fourier encoding (18 overscans), 5 b = 0, 35 isotropically distributed DW directions with b = 500 s/mm2, and a scan time of 2mins. Both patients underwent surgical resection of the tumor, and the tumor grade was evaluated histopathologically. In addition, volunteer cervical and thoracic DTI data were acquired with the same parameters as above (3T, FOV = 22cm x 5.5cm, matrix size = 224 x 56), except that only four b = 0 images were acquired, and two of these were acquired with an opposite phase-encoding gradient to enable subsequent distortion correction using the reversed gradient polarity (RPGM) method [4].

Results: The ZOOM-EPI b = 0 s/mm2, isotropic DWI, color fractional anisotropy (FA), and tractography images for the two patients are shown in Figs.1-2. Fig. 1 shows a well-encapsulated tumor, which was found surgically to lack local tumor infiltration and also was confirmed pathologically to be a low-grade tumor (grade I pilocytic astrocytoma). Fig. 2 shows a more aggressive neoplasm with an infiltrative tumor biology where neoplastic cells infiltrate and traverse alongside spinal tracts. At surgery, the lesion was adherent and difficult to completely excise due to its infiltrative nature; pathologic assessment revealed infiltrating grade II astroctyoma, confirming our pre-operative diagnostic suspicion based on ZOOM-EPI data. Fig. 3 demonstrates distortion-corrected ZOOM-EPI data in a volunteer, showing that it is possible to make further improvements to ZOOM-EPI with post-processing. Discussion: This work shows the application of ZOOM-EPI in a useful clinical setting. Based on the utility of these first patient data acquired at our initiation, ZOOM-EPI DTI data enhanced diagnostic capacity for pathologic tumor grade, and further defined the relationship between spinal tracts and the underlying lesion, an important potential application in surgical management. There was initially some reservation about the multi-slice capability of ZOOM-EPI given that the tilted slice approach may saturate neighboring slices (and therefore significantly reduce the SNR). However, since the useful anatomical region typically resides in the center of the slice, it is possible to get away with small zoom-angles (10º), and thus reduced saturation effects. Our volunteer experiments have shown that multi-slice ZOOM-EPI only comes at a very small expense of SNR. Other reduced FOV approaches such as spatial-spectral selection [5] do not suffer from this saturation effect, however these approaches have a limited number of

slices that can be acquired. At present, we have limited the FOV to a maximum of 18cm at 3T in order to keep distortions at a reasonable level, but we are encouraged by volunteer data that larger rectangular FOV can be achieved in combination with distortion correction (with the use of an oppositely-acquired b = 0 image). Future work will explore a reasonable set of imaging parameters one should use clinically in combination with distortion correction. Summary: This work demonstrates that spinal cord DTI can be extremely useful for the clinical work up of patients, and that ZOOM-EPI is a useful acquisition method to keep distortions within a reasonable limit. Both patient DTI data acquired at 1.5T and 3T revealed important information. Future work will explore whether additional post-processing to reduce distortion can aid the clinical workup of patients. References: [1] Mansfield P. Phys. E: Sci. Instrum. 1988 21:275. [2] Symms M. ISMRM 2000;160. [3] Wheeler-Kingshott, MRM 2002 47:24. [4] Andersson JL. Neuroimage 2003;20(2):870-888. [5] Saritas E. MRM 2008;60:468. Acknowledgements: This work was supported in part by the NIH (5R01EB002711, 5R01EB008706, 3R01EB008706, 5R01EB006526, 5R21EB006860, 2P41RR009784), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, Oak Foundation, and the Swedish Research Council (K2007-53P-20322-01-4).

Figure 1: ZOOM-EPI images of a 35 year old patient with a low grade tumor. (a) b = 0, (b) isoDWI, (c) color FA, (d-e) tractography showing that the tumor is well-encapsulated. This was confirmed surgically.

Figure 2: ZOOM-EPI images of a 5 year old pediatric patient with an aggressive neoplasm. (a) b = 0, (b) isoDWI, (c) color FA, (d-e) tractography depicting infiltrating tracts that were consistent with surgical findings.

Figure 3: Thoracic b = 0 images (NEX = 2) (top row) No distortion correction. (bottom row) distortion-corrected images produced by using the displacement field calculated from the positive (+ve) and negative (-ve) images. The far right is the average of the positive and negative images.

Reduced-FOV Diffusion Imaging with ZOnal Oblique Multislice (ZOOM) combined with Readout-Segmented (RS)-EPI

S. J. Holdsworth1, S. Skare1, R. L. O'Hallaran1, and R. Bammer1 1Radiology, Stanford University, Palo Alto, CA, United States

Introduction: Diffusion-weighted imaging (DWI) using echo-planar imaging (EPI) has been limited by geometric distortion and blurring, particularly in regions with large off-resonance effects such as in the spinal-cord and in regions of the brain residing near tissue/air interfaces. Geometric distortion in EPI is proportional to the FOV in the phase encoding direction (FOVpe), as well as the echo-spacing between adjacent echoes in the EPI train (Tro). Parallel imaging, which is frequently used for distortion reduction in EPI scans, is difficult to use for certain geometric arrangements of coils (such as some spine array coils) and for small FOVs (such as in orbital scans). To reduce FOVpe and avoid aliasing, saturation pulses can be used, however the suppression efficiency is generally limited leading to partial aliasing. Spatially selective RF pulses [1,2] can be used, but have limitations in the number of slices that can be prescribed. The zonal oblique multislice EPI (ZOOM-EPI) technique [3-5] is another approach, which uses a tilted refocusing pulse as shown in Fig. 1. To reduce distortion further, Tro can be reduced by covering k-space with a series of consecutive segments or ‘blinds’, known as RS-EPI [6,7] (Fig. 2c). In this work, we implement both the ZOOM pulse together with the RS-EPI trajectory (ZOOM-RSEPI) to get the benefits of both methods for reducing distortion. Fig. 2 illustrates the theoretical reduction in distortion as one goes from a full FOV EPI, to ZOOM-EPI, and finally to ZOOM-RSEPI.

Methods: All diffusion images were acquired on a 3T whole-body GE DVMR750 system. ZOOM-EPI and ZOOM-RSEPI DW images were first acquired on a phantom (8-channel head coil, single-shot, FOV = 26cm x 7.8cm, matrix size = 180 x 54 (square pixels)). Second, thoracic spine DTI images were acquired on a volunteer using a 4-channel spine coil, followed by a scan of the orbits using a single-channel birdcage coil. The following common parameters were used: rectangular FOV = 30 x 10cm, Δz = 4 mm (zoom-angle θ = 5º, slthck90º = 4mm, slthck180º = 8mm), TR = 3s, a matrix size = 200 x 60 (square pixels), partial Fourier (18 overscans), 24 isotropically distributed DW directions with b = 500 s/mm2, and a scan time of 9:48mins. ZOOM-RSEPI used TEmin = 55 ms, 7 blinds of width = 32 and ZOOM-EPI used TEmin = 75 ms, and 7 NEX. For comparison, full FOV images were acquired on the phantom and volunteer. For the orbital scan, the parameters as above were used with Δz = 5 mm, b = 600 s/mm2, 60 diffusion directions and 4 b = 0 (ZOOM-EPI), 8 diffusion directions with 1 b = 0 (ZOOM-RSEPI), and a scan time of 3:12min.

Results: The EPI and RS-EPI b = 0 s/mm2 phantom images acquired with and without the use of rectangular FOV and ZOOM pulse is shown in Fig. 3. As shown, geometric distortion can be reduced significantly with ZOOM-RSEPI. This method also reduces the ‘jagged’ appearance of the spinal cord as shown in the b = 0 s/mm2

images (Fig. 4). Fig. 5 compares a ZOOM-EPI and ZOOM-RSEPI scan of the orbits. The eyes, the optic nerve, and the ocular muscles show reduced distortion with ZOOM-RSEPI.

Discussion: This work shows that RS-EPI in combination with the ZOOM pulse in order to spatially select a region of interest may be useful for diffusion imaging of regions with large off-resonance effects. While the rectangular FOV used in this work (30cm x 10cm) reduced distortion by 30% (compared to a full FOV acquisition), RS-EPI further reduced the distortion by 33%. A disadvantage of RS-EPI is the reduced SNR efficiency compared with EPI. However the resulting RS-EPI DTI data shown in Fig. 4 shows high SNR 3T images acquired in a reasonable scan time for DTI, and the jagged appearance that often hampers the quality of EPI DW images is reduced significantly. The orbital scan in Fig. 5 more accurately depicts the shape of the optical nerve, thus may be a useful method for DTI or fiber-tracking of the optical nerve for the early diagnosis of pathology such as multiple sclerosis. References: [1] Kiefer C. ESMRMB 1999;302 [2] Saritas E. MRM 2008;60:468. [3] Mansfield P. Phys. E: Sci. Instrum. 1988 21:275. [4] Symms M. ISMRM 2000;160. [5] Wheeler-Kingshott, MRM 2002 47:24 [6] Porter D. ISMRM 2004;442. [7] Holdsworth S. ISMRM 2009:6247. Acknowledgements: This work was supported in part by the NIH (1R01 EB008706, 1R01 EB008706S1, 5R01 EB002711, 1R01 EB006526, 1R21 EB006860), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, Oak Foundation, and the Swedish Research Council (K2007-53P-20322-01-4).

Figure 1: The zoom pulse. Following a 90º slice-selective pulse, a 180º pulse is applied obliquely at an angle θ. The resulting exciting parallelogram is the desired rectangular volume [3].

Figure 2: Reduction of distortion as one moves from (a) full-FOV EPI to (b) a rectangular FOV with EPI (zoom-EPI), and (c) a rectangular FOV with RS-EPI (ZOOM-RSEPI). For the parameters used in this work, this 'distortion meter' accompanying the trajectories is drawn to scale.

Figure 5: Orbital isoDWI images (b = 600 s/mm2) acquired using ZOOM-EPI (60 diffusion directions) and ZOOM-RSEPI (8 diffusion directions, 7 blinds), both in a scan time of 3:12min.

Figure 3: Single-shot EPI and single-shot RS-EPI images (b = 0s/mm2) acquired on a phantom using using: (Left column) a full FOV of 26 cm and matrix size = 180 x 180; (Right column) a rectangular FOV = 26 x 7.8 cm and matrix size = 180 x 54 (square pixels).

Figure 4: Comparison between the b = 0 s/mm2 images of a thoracic spine using full FOV EPI (30 x 30 cm, matrix size = 200 x 200), ZOOM-EPI and ZOOM-RSEPI (30 x 10 cm, matrix size = 200 x 60 (square pixels)). For ZOOM-RSEPI, the isotropic DWI (isoDWI, b = 500 s/mm2), fractional anisotropy (FA), and 1st eigenvector (colormap) are also shown. Note that there is less ‘disc bulging’ into the spinal canal and less blurring on the ZOOM-RSEPI scans than on the ZOOM-EPI scans.

Figure 3: Comparison between the ss-EPI DWI and ss-RS-EPI DWI 1min sequence acquired at 3T on a pediatric patient under suspended respiration. Imaging parameters were: FOV = 28cm, Δz = 5mm, matrix-size = 128x128, TR = 2s, two b = 500s/mm2 (A/P direction), 7 blinds of width 32 (RS-EPI), and 7 NEX (EPI).

Diffusion-Weighted Imaging of the Abdomen with Readout-Segmented (RS)-EPI

S. J. Holdsworth1, S. Skare1, S. S. Vasanawala1, and R. Bammer1 1Radiology, Stanford University, Palo Alto, CA, United States

Introduction: Diffusion-weighted imaging (DWI) in the abdomen has proven useful for various pathologies, including liver lesion characterization [1-4] and simple vessel suppression, diagnosis of diffuse renal disease [5-8], and detection of metastatic spread to lymph nodes [9,10]. However, image distortions arising from the use of EPI has shown to be problematic. We have recently applied DW ‘Short-Axis Propeller’ (SAP)-EPI to the abdomen on adults to reduce geometric distortions via its faster k-space traversal [11]. In this work we explore the use of another short-axis readout technique, Readout-Segmented (RS)-EPI [12], for imaging the abdomen. As shown in Figure 1, the use of several adjacent segments in RS-EPI results in reduced distortion compared with EPI.

Materials & Methods: Breath-hold single-shot (ss)-EPI and ss-RS-EPI diffusion-weighted images were acquired on an adult volunteer using a 3T whole-body GE DVMR750 system using an 8-channel cardiac-array coil. Both sequences used a matrix size of 192 x 192, FOV = 34cm, TE = minimum (RS-EPI: 56 ms, EPI: 72 ms), partial Fourier imaging (24 overscans), slthck/gap = 8 mm/1.5mm, TR = 2s, one b = 500 s/mm2 (S/I direction), in a scan time of 30sec. Seven blinds of size 64 x 192 (freq.×phase) were used for RS-EPI, and 7 NEX were used for EPI to keep the scan time equivalent. By using RS-EPI over EPI, the distortion was reduced by 50% (due to the bandwidth increase in the phase-encode direction). Both sequences were then also acquired on a 6-month old pediatric patient under general aesthesia, after obtaining IRB approval and consent from the patient's parent. Imaging parameters (as different from above) were as follows: matrix size of 128 x 128, FOV = 28cm, slthck/gap = 5 mm/0mm, b = 500 s/mm2 (A/P direction, applied twice), 7 blinds of size 32 x 128 (RS-EPI), and a total scan time of 1 min. In this case, the distortion reduction was 45%. The reconstruction of the RS-EPI data was performed as in Ref. [13], with one exception: the triangular window used for phase correction [14] was increased to the full k-space radius in order to reduce phase errors (and address the larger extent of motion that occurs in body imaging).

Results: A comparison between the b = 0 s/mm2 and isotropic b = 500 s/mm2 EPI and RS-EPI images of the abdomen for the volunteer and patient is shown in Figs. 2 and 3. At an equivalent matrix size and scan time, RS-EPI appears sharper and less distorted, at the expense of a lower SNR. Discussion & Conclusion: While EPI-based DWI of the abdomen has proven useful for the diagnosis of various pathologies, image distortions arising from off-resonance effects (especially in the presence of bowel gas) and large FOVs can significantly hamper the image quality. This work shows that RS-EPI can be useful for DWI of the abdomen by reducing geometric distortion and blurring (as shown in Figs. 2-3). Disadvantages of RS-EPI are the increased scan time compared with EPI – which is tied to the extra number of blinds required to cover k-space – as well as the increased risk of phase-artifacts that can occur between blinds. Further experiments will explore these effects under free-breathing and respiratory triggering. References: [1] Namimoto T, Radiology 1997;204:739. [2] Kim T, AJR Am J Roentgenol 1999;173:393. [3] Ichikawa T, Abdom Imaging 1999;24:456. [4] Taouli B, Radiology 2003;226:71. [5] Ries M, JMRI 2001;14:42. [6] Chan JH, Clin Imaging 2001;25:110. [7] Namimoto T, JMRI 1999;9:832. [8] Fukuda Y, JMRI 2000;11:156. [9] Takahara T, Radiat Med 2004;22:275. [10] Koh D, AJR Am J Roentgenol 2007;188:1622. [11] Skare S, ESMRMB 2009:49. [12] Porter D. ISMRM 2004;442. [13] Holdsworth S, MRM 2009:62 Early view. [14] Pipe J. MRM 1999;42(5):963. Acknowledgements: This work was supported in part by the NIH (1R01EB008706, 1R01EB008706S1, 5R01EB002711, 1R01EB006526, 1R21EB006860), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, Oak Foundation, and the Swedish Research Council (K2007-53P-20322-01-4).

Figure 1: K-space traversal of RS-EPI [12]. K-space is acquired with a series of adjacent EPI segments or ‘blinds’. Note that each blind is accompanied by an extra central segment (or navigator blind) in order to perform phase correction on the DW blinds.

Figure 2: Comparison between ss-EPI and ss-RS-EPI DWI 30sec breath-hold images on a volunteer acquired at 3T. Imaging parameters were: FOV = 34cm, Δz = 8mm, matrix-size = 192 x 192, TR = 2s, one b = 500s/mm2 (S/I direction), TEmin = 72ms/56ms (EPI/RS-EPI), 7 blinds of width 64 (RS-EPI), and 7 NEX (EPI).

Clinical Application of Readout-Segmented (RS)-EPI for Diffusion-Weighted Imaging in Pediatric Brain

S. J. Holdsworth1, K. Yeom1, S. Skare1, P. D. Barnes1, and R. Bammer1 1Radiology, Stanford University, Palo Alto, CA, United States

Introduction: Readout-segmented (RS)-EPI [1] has been suggested as an alternative approach to EPI for high resolution diffusion-weighted imaging (DWI) with reduced distortions. Here we implemented GRAPPA-accelerated RS-EPI DWI on 35 pediatric patients at 3T. We compared these images with standard accelerated (ASSET) EPI DWI used routinely for clinical studies at our pediatric hospital. Methods: RS-EPI and EPI images were acquired on 35 pediatric patients using a 3T whole-body system (GE DVMR750) and an 8-channel head coil. The following parameters were used: FOV=20cm, slthck=4mm, TR=3s, one b=0 and three diffusion directions with b=1000 s/mm2 (xyz encoding). RS-EPI used a twice-refocused diffusion preparation with a matrix size = 1922, 7 segments (width=64, overlap factor=57%), acceleration factor R=3, NEX=3, and a scan time of 4:12min. GRAPPA and ghost calibration were performed on the multi-shot data, thus no separate calibration scan was acquired. Data were reconstructed as described elsewhere [2]. The routine ASSET-accelerated EPI sequence used for comparison: matrix size=1282, R=2, one b=0 and three diffusion directions with b=1000 s/mm2 (xyz encoding), and a scan time of 50s. A pediatric neuroradiologist evaluated the DW images, scoring them in terms of resolution, distortion level, SNR, lesion conspicuity, and diagnostic confidence as follows: 1 – non-diagnostic, 2 – poor, 3 – acceptable, 4 – standard, 5 – above average, 6 – good, 7 – outstanding. First the images were scored independently, followed by a reevaluation of the RS-EPI images with the datasets viewed together. Finally, an overall preference was selected. Results: Fig. 1 shows the average scores calculated across 35 patients for EPI, RS-EPI, and EPI vs RS-EPI. The RS-EPI dataset was preferred overall in all except for two patients due to the presence of phase artifacts on RS-EPI arising from pulsatile brain motion. In 12 patients, the EPI scans suffered from mild-to-severe ‘worm-like’ artifacts also arising from brain motion (though not accounted for when considering the final preference). RS-EPI identified a lesion not identified by EPI in one patient (small subdural empyema, Fig. 2); more accurately defined the extent and structure of lesions, such as a cystic encephalomalacia (Fig. 3a) and a clival chordoma (Fig. 3b); had improved additional lesion localization in one patient (Leigh's disease, Fig. 4); and correctly identified a false positive lesion seen on EPI on another patient (Moya Moya disease, Fig. 5). RS-EPI also demonstrated exquisite anatomic detail at the cortical-subcortical levels, brainstem, temporal and inferior frontal lobes, skull base, orbits, naso-ethmoid, and the cranial nerves – all of which were more difficult to assess on EPI. Overall, the RS-EPI had significantly improved diagnostic confidence. Discussion & Conclusion: Averaged over 34 patients, RS-EPI out-performed the product ASSET EPI sequence (Fig. 1). RS-EPI was chosen as the overall preference for all but two patients due to the presence of phase artifacts on DWI. Note that these artifacts were later removed by increasing the triangular window used for phase correction to the full k-space radius (data not shown). In conclusion, RS-EPI may be a useful alternative to EPI for DWI for evaluating lesions such as hypoxic-ischemic brain injury, diffuse axonal injury, tumors, dermoid/epidermoid, and skull base/orbital pathology. While some of the imaging parameters of the two sequences were not identical, this study shows the importance of both resolution and decreased distortions in the clinics, which can be accomplished by a combination of parallel imaging and alternative k-space trajectories such as RS-EPI. Aside from SNR, increasing the number of averages for EPI (to match the scan time of the RS-EPI) is not expected to change the outcome of this study as it is primarily the resolution and distortion improvements that led to increased lesion conspicuity and diagnostic confidence.

References: [1] Porter D. ISMRM 2008;3262. [2] Holdsworth S. MRM 2009:62 (early view). Acknowledgements: This work was supported in part by the NIH (1R01 EB008706, 1R01 EB008706S1, 5R01 EB002711, 1R01 EB006526, 1R21 EB006860), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, Oak Foundation, and the Swedish Research Council (K2007-53P-20322-01-4). Special thanks to Serman Lim, Alfred Barikdar, Allan White, Young Chang, Harold Estrada, Liz Ellison, and Abbie Bird and for their assistance with the patient studies.

Fig 1. Comparison between the routine ASSET-accelerated EPI sequence and our implementation of RS-EPI in terms of 5 categories averaged over 35 patients.

5835 3D SAP-EPI motion-corrected fast susceptibility weighted imaging

S. J. Holdsworth1, S. Skare1, K. Marty1, M. Straka1, and R. Bammer1

1Lucas MRS/I Center, Stanford University, Stanford, CA, United States

Introduction: Susceptibility-weighted imaging (SWI) has been utilized as a useful contrast mechanism in MRI that accentuates the paramagnetic properties of blood products (1,2). With the use of both magnitude and phase images, SWI can provide improved conspicuity of venous blood vessels and other sources of susceptibility effects (2). Typically, the SWI acquisition uses a high-resolution, three-dimensional gradient echo (GRE) sequence. However, the GRE acquisition used for SWI suffers from a long scan time (~5 mins at 3T), which decreases patient through-put and increases the chances of motion artifacts. A 3D GRE-EPI trajectory has been proposed as a faster alternative. However, unless the data are acquired with several interleaves, the images may suffer from considerable blurring and geometric distortion artifacts. The problem with using multiple interleaves is that, like standard GRE, it makes 3D GRE-EPI vulnerable to motion. Here, a 3D short-axis readout propeller (SAP)-EPI trajectory (3) is suggested as an alternative approach to 3D GRE and 3D GRE-EPI. SAP-EPI can achieve higher resolution than EPI with significantly reduced distortions (4). As a result, fewer interleaves can be used (GRAPPA-acceleration factor R ≤ 4), making the use of parallel imaging (PI) applicable. With PI, each interleave can be acquired with the full image FOV, making one ‘blade’ consistent (that is, inter-blade motion is negligible), while the acquisition of one ‘brick’ can be performed with full brain coverage in a few seconds. The speed of 3D SAP-EPI makes the risk of intra-brick motion (ghosting) small – leaving only the inter-brick 3D motion to be corrected (3). Here we show human 3D SAP-EPI SWI images, as well as demonstrate initial motion-corrected SWI SAP-EPI human data from controlled motion experiments. 3D SAP-EPI is also compared with interleaved 3D EPI as well as with standard 3D GRE.

Methods: The 3D SAP-EPI k-space trajectory is shown in Fig. 1. Experiments were conducted on a healthy volunteer using a 3T whole-body GE Excite system and an eight-channel head coil. The following scan parameters were used for the SAP-EPI and interleaved EPI sequence: matrix size = 256 x 256, TR/TE/FA = 55ms/20ms/20º, FOV = 24 x 24 x 12.8cm3, 64 z-partitions, slthk = 2 mm. The SAP-EPI sequence used 8 blades of width 64, R = NEX = 4, a brick frame rate of 3.5 s, and a scan time of 1:48 min. The EPI sequence used 32 interleaves for an equivalent scan time. Two 3D SAP-EPI datasets were acquired, the second with a through-plane rotation of ~10º. Blade data were mixed, such that every second blade was chosen from the rotated dataset. The R bricks per brick angle originating were 3D motion corrected (in the image domain). All bricks together were then motion corrected prior to gridding (in k-space). A high resolution flow-compensated GRE sequence was acquired for comparison (matrix size = 512 x 256, rectangular FOV = 0.75, TR/TE/FA = 37ms/20ms/20º, z-

partitions = 32, slthk = 2mm, scan time = 5mins). All data were processed by generating a phase mask using a 2D Hanning window. The phase mask was multiplied by the magnitude image 5 times to produce the final SWI image.

Results: A comparison between the original magnitude images acquired with 3D GRE, interleaved EPI, and SAP-EPI is shown in Fig. 2. Although the resolution and SNR is highest for the GRE scans, both the interleaved EPI and SAP-EPI scans demonstrate darker vessels in a number of regions. In addition, interleaved EPI and SAP-EPI have a considerably reduced scan time and a better extent of brain coverage (64 partitions in 1:52mins for interleaved EPI and SAP-EPI, versus 32 partitions in 5mins for GRE). Although the scan time of the interleaved EPI scan is equivalent to the SAP-EPI and the vessels are slightly more conspicuous, it has reduced SNR and suffers from ghosting artifacts – even for a cooperative volunteer. Motion artifacts are problematic for both GRE and EPI, as even small patient motion could result in an unusable image. Fig. 3 shows a side-by-side comparison of GRE and SAP-EPI images. While small vessels are more easily depicted in the GRE image, SAP-EPI renders thicker and more prominent larger vessels – probably due to the additional T2*-dephasing that occurs during the EPI readout. Also depicted are motion corrupted SAP-EPI SWI data from the mixed-blade dataset which have been corrected for motion. This example demonstrates an additional advantage of SAP-EPI over GRE and interleaved EPI.

Discussion: Perhaps one of the greatest hindrances to the adoption of SWI in the clinics is the long scan time associated with standard GRE. However, with parallel imaging, the scan time of GRE can be reduced by up to a factor of 4 (8-channel head coil) – although this can result in a significant SNR penalty. EPI can be used to significantly speed up the acquisition, but with an SNR which makes it more compatible with PI. However, PI-enhanced EPI still suffers from distortion artifacts. On the other hand, multi-shot EPI used without PI (R > 4), like standard GRE can suffer from severe ghosting in the presence of motion. SAP-EPI helps to alleviate some of these problems. The ‘short-axis’ blades with a smaller echo-spacing (compared to EPI) result in reduced distortion (roughly proportional to the width of the blade). As a result, fewer interleaves can be used – which enable the use of PI (here R = 4) to give a consistent motion-free blade (that is, a blade acquired at full FOV) in a reduced overall scan time compared with GRE. In addition, any motion that does occur between blades can be corrected for via 3D rigid-body correction. In the event that the brick frame rate (of 3.5 s in this case) results in inter-brick motion, this brick could be re-acquired (3).

Summary: Here we have presented SWI images acquired with an efficient propeller-based EPI readout method, which has an inherent ability to allow motion correction. While 3D SAP-EPI still suffers from some geometric distortion, its significantly shorter scan time and relatively high SNR suggest that 3D SAP-EPI may be a useful alternative to GRE for use in susceptibility-weighted imaging, particularly in uncooperative patients. References: [1] Reichenbach JR et al. Radiology 1997;204:272-77. [2] Hacke EM et al. MRM 2004;52:612-18. [3] Holdsworth SJ et al. ISMRM 2008:1352. [4] Skare S et al. MRM 2006;55:1298-1307. [5] Nordell A et al. ISMRM 2007:1833. [6] Griswold MA et al. MRM 2002;47:1202-1210. [7] Qu P et al. JMR 2005;174(1):60-67. [8] Skare S et al. MRM 2007;57:881–890. Acknowledgements: This work was supported in part by the NIH (2R01EB002711, 1R01EB008706, 1R21EB006860), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, Oak Foundation, and the Swedish Research Council (K2007-53P-20322-01-4). We would also like to thank Bronwen Holdsworth for her continuous help.

Fig. 2: 3D GRE, 3D interleaved EPI (32 shots), and 3D SAP-EPI (R = NEX = 4, 8 blades) original magnitude images.

Fig. 3: (A) 3D GRE, (B) 3D SAP-EPI SWI (top row) and SWI minIP images (bottom row). Also included in (B) are motionless, motion-corrupted, and 3D motion corrected SAP-EPI images.

Fig. 1: 3D SAP-EPI k-space traversal (3). One blade is acquired for every z-partition – resulting in one ‘brick’, which is then rotated. Referenceless Nyquist-ghost calibration parameters (5) are estimated on the middle slice in hybrid-space to correct for each brick, followed by a 1D FFT along kz. GRAPPA weights (6,7) are estimated on each brick (8).

6397 T1-weighted 3D SAP-EPI for use in pediatric imaging without general anesthesia

S. J. Holdsworth1, S. Skare1, K. Yeom1, and R. Bammer1

1Radiology, Stanford University, Palo Alto, CA, United States

Introduction: 3D Short-Axis readout Propeller EPI (SAP-EPI) was recently introduced as an alternative to the 3D T1-w Spoiled Gradient Echo (SPGR) technique commonly used for routine clinical studies [1]. In the presence of motion, the data consistency for encoding in 3D-SPGR is violated and gives rise to ghosting artifacts. In 3D SAP-EPI, the acquisition of ‘bricks’ (each consisting of an EPI blade that goes through the center of k-space) gives full brain coverage with a frame rate of ~3s (Fig. 1). Since each brick can be acquired at full FOV, the option of performing 3D motion and distortion correction between bricks is available. 3D SAP-EPI can have particular impact on pediatric imaging, since gross patient motion is difficult to avoid, and as a consequence, many patients are sedated or anesthetized. Whilst motion-compensated methods are available for T2w/FLAIR/DWI, a T1w method is not currently available and would be tremendously useful. In this abstract, we demonstrate the utility of 3D SAP-EPI applied to a moving pediatric patient.

Methods: The 3D SAP-EPI k-space trajectory is shown in Fig. 1. Images were acquired on a 1.5T GE Excite (Waukesha, WI, USA: 50mT/m, 150mT/m/s) and an 8-channel head coil. First of all, to verify the utility of the sequence controlled motion experiments were performed on a healthy adult volunteer. 3D SAP-EPI data were acquired with the following scan parameters: FOV = 25 cm3; a matrix size of 192 x 192 x 128; a voxel size of 1.3 x 1.3 x 2.0 mm3, 8 blades of size 48(kRO) x 192(kPE) x 128(kPEz), a GRAPPA-acceleration factor R = 3; NEX = 3; full Fourier; TR/TE/FA = 55ms/17ms/60º; a brick frame rate of 7 s. The scan time was 2:48mins (one would expect a ~3mins for a conventional 3D fast SPGR of a similar scan prescription). The volunteer was asked to move in the through- and in-plane direction and the scan was then repeated. Blades from the first and second dataset were then mixed. After obtaining IRB approval and consent from the patient’s parents, 3D SAP-EPI were acquired on a 6yr old male with an optic glioma. Imaging parameters were: FOV = 24 x 24 x 12.8 cm3; a matrix size of 192 x 192 x 64; and a voxel size of 1.3 x 1.3 x 2 mm3. Four blades of size 64 x 192 x 64 were acquired with a 180º sweep (thus the edges of k-space were slightly undersampled); a brick frame rate of 3.5s; and a total scan time of 2:07mins. Three repetitions of each blade angle were made, in order to increase the chance of acquiring a brick without inter-brick

motion. The brick with the best GRAPPA fit and Nyquist ghost parameters was used in the final reconstruction. For the post-processing stage, the blades underwent referenceless Nyquist-ghost correction [2], and GRAPPA weights [3-5] estimation and application on a per brick basis. 3D motion and distortion correction was then applied using the combination of all blades for estimating the ΔB0 field [6], followed by gridding of the blades together [7].

Results: Data obtained from the mixed-blade dataset is shown in Fig. 2. The 3D motion- and distortion-corrected image shown in Fig. 2c shows the successful correction of the motion-corrupted data in Fig. 2b. Patient data are shown in Fig. 3. The top row shows the routine T1-w fast SPGR image corrupted by motion. The rows below this show motion corrupted 3D SAP-EPI data which also have been corrected for motion, as well as combined motion and distortion correction. As indicated by the white arrow, a double image is evident in the posterior region of the motion corrected image, due to residual distortion. A marked improvement can be observed in this area for the combined 3D distortion and motion corrected images.

Discussion & Conclusion: In our experience, approximately 20% of pediatric patients must either be rescanned or sedated, due to severely motion corrupted images. 3D SAP-EPI has yielded images with high grey-white matter contrast and data can be acquired in a similar scan time than fast 3D SPGR. Together with its motion correction capability, 3D SAP-EPI could be a useful alternative to fast 2D and 3D SPGR routinely used for pediatric brain imaging. Fig. 3 is an example of a successfully corrected dataset acquired on a 6yr old moving patient. By collecting several bricks per blade angle, one can discard the corrupted bricks in the event of substantial intra-volume motion – and 3D motion correction can then be performed using the remaining bricks. While the brick frame rate of 3.5s cannot rule out intra-volume motion, the use of 4 blades and 3 repetitions of the acquisition enabled two of the bricks that were corrupted by inter-brick motion to be discarded. To increase the brick frame rate, future work would be to implement GRAPPA in the z-direction also, or to use a multi-slab approach. Deciding which bricks to discard in a non-supervised manner could be investigated with the use of k-space entropy or by the GRAPPA fit error. Here, the use of thin SAP-EPI blades combined with parallel imaging has allowed reduced distortions. Any residual distortion can be partly corrected for, using 3D distortion correction with the combination of all blades/bricks, without the penalty of extra calibration time. Future work would be to acquire images at higher field strengths to test the distortion correction method, and to put forward a good method for automatic brick elimination based on motion. References: [1] Holdsworth SJ et al. ISMRM 2008:1352. [2] Nordell A et al. ISMRM 2007:1833. [3] Griswold MA et al. MRM 2002;47:1202-1210. [4] Qu P et al. JMR 2005;174(1):60-67. [5] Skare S et al. MRM 2007;57:881–890. [6] Skare S et al. ISMRM 2008:417. [7] Jackson JI. IEEE Trans Med Imag 1991;10:473-478. Acknowledgements: This work was supported in part by the NIH (2R01EB002711, 1R01EB008706, 1R21EB006860), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, and the Swedish Research Council (K2007-53P-20322-01-4). We would like to thank Bronwen Holdsworth, Tom Brosnan, Allan White, Serman Lim, Michael Beers, Alfred Barikdar, Young Chang, and Liz Ellison for their assistance.

Figure 2. Human brain scans from a controlled motion 3D SAP-EPI experiment.

Figure 3. Human brain scans acquired with fast 3D SPGR (top row) and 3D SAP-EPI (remaining rows). Parameters were: a matrix size of 192 x 192, blade width = 64, 4 blades selected from 3 repetitions, R = NEX = 3, TR/TE = 56 ms/17ms, a FOV = 24 x 24 x 12.8 cm3, 64 partitions, a voxel size of 1.3 x 1.3 x 2 mm, and scan time = 2:07mins.

Figure 1. Traversal of k-space in 3D SAP-EPI [1]. Bricks are swept by 180º in the x-y plane.

6761 On the application of phase correction and use of k-space entropy in partial Fourier diffusion-weighted EPI

S. J. Holdsworth1, S. Skare1, and R. Bammer1

1Lucas MRS/I Center, Stanford University, Stanford, CA, United States

Introduction: It is well-known that diffusion-weighted (DW) imaging is very sensitive to the effects of brain motion, even in single-shot (ss)-EPI [1-4]. While the extent of rigid body motion can be minimized through patient compliance and by securing the patient’s head, pulsatile brain motion is ubiquitous and can be significant. Pulsatile brain motion that occurs during the application of the DW gradients can result in the dispersion of k-space, corresponding to signal dropout and shading in the image domain. Severe brain motion may yield a k-space completely corrupted by brain motion [4]. Typically, partial Fourier (PF) encoding in the phase-encoding direction is used to reduce the echo time in DW-ssEPI. Here, the number of ‘overscans’ is used to denote how many extra lines of k-space are acquired past the k-space center. If k-space is dispersed in the case of pulsatile brain motion, the number of overscans acquired may not be enough to encode some of the dispersed signal and considerable information may be lost. In addition, the lack of phase information provided by the small central strip of k-space used for PF reconstruction may result in artifacts in the final image. This abstract shows that phase correction applied prior to partial Fourier reconstruction in ss-EPI is helpful for recovering signal lost in cases where k-space is corrupted by brain motion.

Using the same k-space from several repetitions of a DW-ssEPI scheme, we explore the use of k-space entropy [5] as a metric to identify k-space corrupted by non-linear brain motion; the use of peripheral cardiac gating and non-gating; phase correction applied before both homodyne and POCS reconstruction; as well as the number of overscans that should be used to avoid significant artifacts due to pulsatile brain motion.

Materials & Methods: A healthy volunteer was scanned on a 3T whole-body GE EXCITE system (Waukesha, WI, USA, 40 mT/m, SLR = 150 mT/m/s) with an 8-channel head coil. Data were acquired by repeating an EPI diffusion scheme 150 times along the S/I direction (the direction most sensitive to pulsatile motion [6]). This scheme was repeated both with and without peripheral cardiac gating. A target resolution of 128 x 128 was used, a TR = 3 s (or 3 RR intervals and minimum trigger delay for the gated acquisition), R = 3, b = 1000 s/mm2, and 21

slices with a thickness of 5mm. Full Fourier data were acquired – and this data was used to test various overscans. The entropy of k-space was used to determine the correlation between entropy and the extent of non-linear motion due to brain pulsation. Corrupted k-space identified by the entropy measure was then reconstructed using the following number of overscans: 8, 16, and 32. Each dataset were phase corrected using a triangular windowing approach [7] modified for partial Fourier data (Fig. 1). The phase correction approach corrects for any low spatially varying linear and non-linear motion with the use of a low resolution phase-map extracted from the center strip of k-space [7]. This approach was applied before both POCS [9] and homodyne [10] reconstruction. The images were compared with the same data reconstructed without phase correction.

Results: Fig. 2 shows a plot of the k-space entropy for 150 DW-EPI repetitions calculated from one slice acquired at the base of the brain. As shown, non-linear motion causes a substantial dispersion of k-space data – which is paralleled with an increase in the entropy of k-space, and correspondingly large signal voids in the center of the image. While peripherally-gated DW-ssEPI sequences are robust against pulsatile brain motion, non-gated sequences yield corrupted k-space with 15% prevalence for slices located at the base of the brain (where pulsatile motion is greatest). Fig. 3 shows slices with high- and low- k-space entropy (taken from the highest and lowest peak in Fig. 2, respectively). Both datasets are reconstructed with POCS and homodyne (using 8 overscans), as well as reconstructed without (top row) and with (bottom row) phase correction. While there is little difference in image quality between the two types of PF reconstruction methods in the low k-space entropy case, the dataset with high k-space entropy yields significant artifacts in the image domain. For the latter, both homodyne and POCS yield a large signal void in the brain stem, with additional ‘worm-like’ artifacts for the homodyne reconstruction. For both reconstruction techniques, it is clear that performing the phase correction approach before Partial-Fourier reconstruction recovers significant signal in the brain stem for both PF methods, and has fewer worm-like artifacts for the homodyne reconstruction. Important to note is the utility of using a larger number of overscans for avoiding brain motion artifacts [4], as shown in Fig. 4. Here, the same dataset is used, except k-space is trimmed to 8, 16, and 32 overscans, respectively, prior to PF reconstruction. In the case of severe non-linear motion, the increasing benefit of more overscans is evident. In addition, even in the case of 16 overscans, phase correction prior to homodyne reconstruction recovers signal in the brain stem. However, as the number of overscans approaches 32, the benefit of performing phase correction before PF is not clear.

Discussion: This work demonstrates k-space entropy as a robust metric to identify data corrupted by motion. Out of 150 repetitions of a diffusion scheme, ~15% of slices in the base of the brain (b = 1000 s/mm2, S/I direction) revealed elevated k-space entropy which closely correlated with the extent of signal dropout and image artifacts in the image domain. The entropy metric tended to be deterministic – either low in the case of no motion, or considerably elevated (see Fig. 2). Perhaps the most important message is the following: to help to avoid artifacts due to brain motion, it is useful to perform phase correction on PF data before PF reconstruction. It was shown that POCS out-performs homodyne reconstruction for data corrupted by non-linear motion. Both methods help to recover lost signal, however POCS results in fewer worm-like artifacts. For both methods, consistent with [4], a larger overscan factor will yield a more robust estimation of the image phase and fewer motion-related image artifacts. Used in conjunction with phase correction prior to PF reconstruction, we recommend using a minimum number of overscans of 16 to help avoid these image artifacts. Whilst the cases shown in the figures are the most extreme cases of

non-linear motion we saw in our experiments, in some cases motion may be so severe (particularly when there is significant motion in the through-plane direction) that k-space may have to be reacquired. References: [1] Norris DG. JMRI 2001;13:486–495. [2] Wedeen VJ. MRM 1994;32:116-120. [3] Butts K. MRM 1996;35:763-770. [4] Storey P. MRM;57(3):614-619. [5] Shannon CE. Weaver W. Uni. Illinois Press; 1963. [6] Wirestam R. JMRI 1996;6(2):348-355. [7] Pipe J. MRM 2002;47(1):42-52. [8] Holdsworth SJ. ISMRM 2008;4. [9] Liang ZP. Rev MRM 1992;4:67-185. [10] Noll DC. IEEE Trans. Med. Imag. 1991;10(2):154. Acknowledgements: This work was supported in part by the NIH (2R01EB002711, 1R01EB008706, 1R21EB006860), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, and the Swedish Research Council (K2007-53P-20322-01-4).

Figure 2: Plot showing the entropy of k-space calculated for 150 DW-ssEPI acquired in the S/I diffusion-encoding direction (b = 1000 s/mm2, black = gated; blue = not gated). The red line shows the threshold above which k-space is significantly dispersed by non-linear motion (high k-space entropy), causing large signal dropouts in the image domain. The threshold (red line) was determined by using the mean of the entropy over the 150 repetitions + one standard deviation, and indicates the line above which these corrupted blinds have severe signal dropouts and shading in the image domain.

Figure 3: DW-EPI datasets with a) low k-space entropy, and b) high k-space entropy. A matrix in-plane resolution of 128 x 128 was used, slthck = 5mm, b = 1000 s/mm2 (S/I direction). Both datasets were acquired with PF in the p/e-direction, using 8 overscans and both homodyne and POCS reconstruction. The data were also reconstructed both without (top row) and with (bottom row) phase correction. The long red arrows indicate the ‘worm-like’ artifacts prevalent in homodyne-reconstructed datasets corrupted by brain motion, as well as the severe signal dropouts in the brainstem in both PF methods. The small arrows indicate areas of significant improvement in the image quality due to the phase correction.

Figure 4: DW-EPI (b = 1000 s/mm2, S/I direction) datasets acquired at an in-plane resolution of 128 x 128 showing: A) Low k-space entropy for reference (full Fourier data). B) Severely motion corrupted data reconstructed with various overscans both without phase correction (top row), as well as with phase correction performed prior to homodyne reconstruction. The red arrows indicate areas with significantly improved image quality.

Figure 1: Triangular phase correction process [7] applied to the partial Fourier diffusion-weighted ssEPI data. Note that this process is similar to [8], however is faster with the use of zerofilling (rather than POCS).

6427 Diffusion-weighted imaging of the spine with readout-segmented (RS)-EPI

S. J. Holdsworth1, R. Bammer1, and S. Skare1

1Lucas MRS/I Center, Stanford University, Stanford, CA, United States

Introduction: The development of diffusion-weighted imaging (DWI) of the spine has been hindered by the large off-resonance effects problematic for single-shot EPI. Overcoming these restrictions would open up applications ranging from the diagnosis of spinal cord infarction, vertebral body fractures, lymphoma, trauma, and many other disorders. Navigated interleaved EPI has been shown to overcome this distortion problem both in the brain [1] and in the spine [2]. However, interleaved EPI may lead to undersampling effects in k-space leading to ghosting [3]. Readout-segmented (RS)-EPI has recently been shown to be a promising pulse sequence for high-resolution DWI of the human brain, with significantly reduced distortions [4-6]. RS-EPI uses several ‘blinds’ (each coupled with a central blind navigator) which are adjacent in the readout direction. The shorter echo-spacing – or, in other words, the increased pseudo bandwidth along the phase encoding direction – reduces both geometric distortions and image blurring. Since each blind itself is consistent (that is, acquired at full FOV), this trajectory also avoids ghosting in the presence of motion that occurs between shots in interleaved EPI. The objective of this study was to compare DW images acquired with RS-EPI and EPI. Here we produce images with significantly reduced distortions compared with EPI.

Materials & Methods: Diffusion-weighted images were acquired on three volunteers on a 3T whole-body GE Excite system using a four-channel spine coil. One volunteer presented with an asymptomatic hemangioma in the vertebrae. Single-shot (ss)-EPI and ss-RS-EPI images were acquired in the thoracic spine as well as cervical spine region. Parallel imaging was not used due to the coil geometry. Thus, the phase encoding direction was applied in the A/P direction and an anterior graphical saturation pulse was applied to avoid wrapping (due to phase aliasing and motion artifacts from the heart). Both methods used a matrix size of 192x192, TE = minimum (RS-EPI: 61 ms, EPI: 84ms), 32 overscans, slthck = 4 mm, TR = 3s. RS-EPI used 7 blinds of size 32x192 (freq.×phase), and EPI used 7 NEX to keep the scan time equivalent. Images of the thoracic spine were acquired on two volunteers, consisting of 3 b = 0 s/mm2 and 15 isotropically distributed DW directions with b = 500 s/mm2, a rectangular FOV = 40 x 20 cm, and a scan time of 6:18mins. For the second volunteer, a b = 0 s/mm2 image was acquired with a negative phase encoding gradient, and – with the use of the b = 0 s/mm2 image from the positive phase encoding gradient – this data was used to perform distortion correction [7]. The cervical spine scan consisted of one b = 0 s/mm2 and seven b = 500 s/mm2 diffusion directions at a FOV = 30 x 15 cm, and a scan time of 2:27mins. For all scans, the theoretical reduction in distortion with RS-EPI is 57%. The ghost calibration parameters [8] were calculated from the center blind of the center slice of the b=0 volume and were applied to all b = 0 and b = 500 s/mm2

volumes. This was followed by ramp sampling correction, and phase correction using triangular windowing [9,10]. The partial Fourier data were reconstructed with POCS [11,12], prior to gridding [13] and sum-of-squares over coils. FSE images were also acquired for geometric comparison. Note that for all data, gradient warp correction was not used.

Results: A comparison between the b = 0 s/mm2 and isotropic b = 500 s/mm2 EPI and RS-EPI images of the spine is shown in Figure 1. The RS-EPI trajectory significantly reduces the “zig-zag” appearance of the spinal cord compared with EPI (cf. FSE image, left panel). Incidentally, hemangioma in the vertebrae (white arrows) is more clearly delineated with RS-EPI. Likewise, the isotropic RS-EPI-DW images of the cervical spinal cord in Figure 2 have reduced distortions compared with EPI, particularly at tissue-air interfaces. Fig. 3 shows distortion corrected ss-RS-EPI data. As indicated by the red line drawn on the FSE for geometric reference, further improvement in the distortion properties can be observed.

Discussion: EPI-based DWI of the spine has traditionally been difficult because of off-

resonance effects and large FOVs. This work shows that RS-EPI can be useful for imaging the spine, with considerably reduced geometric distortions (Figs. 1-3). This method can be used to acquire high resolution DW images in a clinically reasonable scan time. Compared with EPI, the scan time increase is 7-fold. However, compared with PROPELLER FSE – a sequence which may be another useful candidate for spine DWI – the reduction in scan time is significant. Another advantage of RS-EPI is that the target resolution is independent from geometric distortion – it is only dependent upon the blind width and FOV. If further reduction in distortion is warranted, one may decrease the blind width (at the expense of more blinds and a longer scan time), and/or perform distortion correction (Fig. 3) with the use of an image acquired with a negative phase-encoding gradient. Future work could be to replace the spectral spatial pulse used here with selective excitation [14-16] to avoid the imperfect saturation pulse; and to investigate the use of inversion recovery methods such as STIR, SPIR, and SPAIR [17] to achieve better fat saturation. References: [1] Butts K. MRM 1996;35:763-770. [2] Bammer R. JMRI 2002;15:364-373. [3] Atkinson MRM 2000;44:101-109. [4] Porter D. ISMRM 2004;442. [5] Porter D. ISMRM 2008;3262. [6] Holdsworth SJ. ISMRM 2008;757. [7] Andersson JL. Neuroimage 2003;20(2):870-888. [8] Nordell A. ISMRM 2007:1833. [9] Pipe J. MRM 1999;42(5):963-969. [10] Holdsworth SJ. ISMRM 2008;4. [11] Haacke JMR 1991;92:126-145. [12] Liang Rev MRM 1992;4:67-185. [13] Jackson IEEE TMI 1991;10:473-478. [14] Mansfield J. Phys E: Sci Instrum 1988(21):275-280. [15] Rieseberg S MRM 2002;47(6):1186-1193. [16] Saritas E. MRM 2008;60:468-473. [17] Mürtz Eur Radiol 2007;17:3031–3037. Acknowledgements: This work was supported in part by the NIH (2R01EB002711, 1R01EB008706, 1R21EB006860), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, Oak Foundation, and the Swedish Research Council (K2007-53P-20322-01-4). We would also like to thank Greg Zaharchuk for his useful advice.

Figure 2: EPI and RS-EPI isotropic DWI (7 directions with b = 500 s/mm2) and an FSE for geometric reference. As in Fig. 1, the scan time for the sequences is equivalent (2:27mins). Imaging parameters were: matrix size 192 x 192, FOV = 30 x 15 cm, slthck = 4 mm, TR = 3 s. The echo spacing was 316μs for RS-EPI and 728μs for EPI.

Figure 3: Images (b = 0s/mm2) on a second volunteer acquired as in Fig. 1, showing a comparison between ss-EPI and ss-RS-EPI. On the far right the ss-RS-EPI image has been distortion corrected with the use of a b = 0 image acquired with a negative phase-encoding gradient.

Figure 1: ss-EPI and ss-RS-EPI iso-DWI (15 diffusion directions with b = 500 s/mm2) and an FSE for geometric reference. The scan time for the sequences is equivalent (EPI: NEX = 7; RS-EPI: 7 blinds of width 32). Imaging parameters were: matrix size = 192 x 192, FOV = 40 x 20 cm, slthk = 4 mm, TR = 3s, scan time = 6:18mins.

6479 Reducing distortion in EPI using partial Fourier encoding in the kx-direction

S. J. Holdsworth1, R. Bammer1, and S. Skare1

1Lucas MRS/I Center, Stanford University, Stanford, CA, United States

Introduction: It is often incorrectly believed that geometric distortion in echo-planar imaging (EPI) is related to the time of reading out the entire EPI train – rather than the time between two consecutive echoes in the EPI train, the latter which is the reciprocal of the pseudo bandwidth along ky. Local displacements (in [m]) of an object in the phase-encoding direction arise according to [1]:

0( ) ( )

2pe ro pe

d r B r T FOVγπ

= Δ (1)

where ΔB0(r) represents a field inhomogeneity, FOVpe is the phase-encoding FOV, and Tro = Nro * Δtro is the readout time for one k-space line (or echo spacing), and Nro is the number of samples in the readout direction. From Eq. 1, one can reduce geometric distortion by reducing FOVpe and/or by reducing Tro. The former can be achieved by accelerating the traversal of k-space with parallel imaging [2-4], whilst the latter can be achieved by reducing the readout width Nro. To shorten the EPI readout and TE, the acquisition is often used with partial Fourier (PF) imaging in the ky-direction. Particularly with higher field strength, the shorter readout train decreases blurring; while the smaller achievable TE increases SNR (offset by less data acquired per readout), increases the # slices/TR, and can decrease T2-shine-through in diffusion-weighted imaging for high matrix sizes. In this abstract, PF-encoding in EPI is performed instead in the kx-direction and compared with images acquired with PF in the ky-direction. As shown in Fig. 1, the echo spacing between two consecutive echoes is reduced (Fig. 1b) – resulting in reduced geometrical distortion while keeping the SNR approximately equivalent. This approach can reduce geometric distortion by ~20% compared with EPI images acquired with PF in ky.

Materials & Methods: Images were acquired using the two approaches shown in Fig. 1, where method A represents PF-encoding in ky, and method B represents PF-encoding in kx. GRAPPA-accelerated T2-weighted images were acquired on a phantom and on a healthy volunteer on a

3T whole-body GE EXCITE system (Waukesha, WI, USA; G = 40 mT/m, SLR = 150 mT/m/s) using an eight-channel head coil. Images were acquired using method A with Noy = 18 and the alternative method B with Nox (or ‘overscans in kx’) equivalent to 18 pixels. Images were acquired for both methods with a matrix size of 128 x 128 and 256 x 256 and with a TE and Tro reported in Table 1. Other parameters were: a GRAPPA-acceleration factor R = 3; NEX = 3; a 4 mm slice thickness; FOV = 24 cm; TR = 4s, and a scan time of 16s. For SNR measurements, human brain images were acquired for each of the methods. Here, three repetitions and 24 slices were acquired using the same imaging parameters above, but with the same echo time (TE = 34ms for a matrix size of 128 x 128, and TE = 68ms for a matrix size of 256 x 256). For the post-processing stage, the ghost calibration [5] and GRAPPA weights [2-3] were calculated for each volume, followed by ramp sampling correction, homodyne reconstruction [6], and sum-of-squares over coils.

Results: Phantom data comparing the two alternatives is shown in Fig. 2. Zooming into the gridded region one can observe reduced distortion and blurring in B. There is also reduced distortion as indicated by the curvature of the black region. Brain data comparing the two methods are shown in Fig. 3. The distortion reduction achievable in B is most noticeable in the eyes, brain stem, and temporal lobes – as indicated by the white arrows. Although the TE is longer for method B, this may be preferred for some applications requiring T2- or T2*-weighting (such as fMRI). Measurements from human brain data revealed no significant difference in SNR between the two methods.

Discussion: A number of MR applications that require the use of fast imaging rely on EPI for its robustness to motion and short scan time. Perhaps the most predominant problem with EPI is that it can suffer from severe geometric distortion. Here we propose a relatively simple method to reduce distortion by performing PF encoding in the kx-direction, instead of in the ky-direction. Since geometric distortion is proportional to the readout width Nro, for an equivalent scan time, geometric distortion can be reduced by ~20% compared to images acquired with PF-encoding in ky. It would seem from Fig. 1 that a larger reduction should be achieved. However, the relation between Nro and Tro is not linear – due to differences in the amount of ramp times versus the plateau time [1]. Despite this, the reduction in distortion is noticeable in both the phantom and human data shown in Figs. 2 and 3. One disadvantage of this method is that the minimum achievable TE is longer (refer Table 1). However, in situations requiring T2- or T2*-weighting – where TE > 34ms for a 128 x 128 matrix size, and TE > 68ms for a 256 x 256 matrix size (Nox = 18) – the SNR will be approximately equivalent for the two methods, as long as Nox = Noy. According to our SNR measurements calculated on images acquired with the same TE, the SNR is indeed approximately the same for both methods – despite that, due to ramp sampling, method B collects more sample points per ky-line.

References: [1] Skare S. MRM 2006;55:1298–1307. [2] Griswold M. MRM 2002;47:1202-1210. [3] Qu P. JMR 2005;174(1):60-67. [4] Bammer R. MRM 2001;46(3):548-554. [5] Nordell A. ISMRM 2007:1833. [6] Noll DC. IEEE Trans. Med. Imag. 1991;10(2):154. Acknowledgements: This work was supported in part by the NIH (2R01EB002711, 1R01EB008706, 1R21EB006860), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, Oak Foundation, and the Swedish Research Council (K2007-53P-20322-01-4). We would like to thank Bronwen Holdsworth, Heiko Schmiedeskamp, and Murat Aksoy for their help.

Method TE/Tro 128 x 128 256 x 256

A 17ms/688μs 20ms/916μs B 34ms/564μs 68ms/712μs

Table 1: Minimum echo time (TE) and echo spacing (Tro) used for the two methods proposed in Fig. 1.

Figure 3. EPI images of a healthy volunteer acquired with PF-encoding in (A) ky, (TE = 20ms) and (B) kx (TE = 68ms). Imaging parameters were: a matrix size of 256 x 256, FOV=24cm, TR=4s, R=NEX=3, scan time = 16s.

Figure 1. EPI trajectory with partial Fourier encoding in (A) the ky-direction, and (B) the kx-direction. In (B) the echo spacing (Tro; shown by the red-dashed lines) between consecutive echoes is reduced. Noy and Nox represent the ‘number of overscans’ in the ky- and kx-direction, respectively.

Figure 2. Phantom data acquired at a matrix size of 256 x 256 (R=3) with PF-encoding in (A) ky (Tro = 916μs), and (B) the kx (Tro = 916μs). The red line indicates the extent of distortion reduction by using B.

Figure 4: RS-EPI diffusion-weighted navigator-corrected datasets (b = 1000 s/mm2, S/I direction) acquired (a) with and (b) without gating at a target resolution of 288 x 288. The datasets are reconstructed with different overlapping factors as shown.

Practical Considerations for GRAPPA-accelerated Readout-Segmented EPI in Diffusion-Weighted Imaging

S. J. Holdsworth1, S. Skare1, R. D. Newbould1, A. Nordell2, and R. Bammer1 1Department of Radiology, Stanford University, Palo Alto, CA, United States, 2Hospital Physics, Karolinska University Hospital, Stockholm, Sweden

Introduction: Readout mosaic segmentation (RS-EPI) has been suggested as an alternative approach to EPI for high resolution diffusion-weighted imaging (DWI)

with minimal geometric distortions (1). The RS-EPI trajectory must be coupled with the use of a second navigator echo to correct for shifts in k-space that occur during the application of the diffusion-encoding gradients. Larger shifts which displace the signal outside the k-space sampling range can cause dramatic signal loss. This effect can be minimized with the use of overlapping blinds, however this comes at the expense of scan time. In this abstract, peripherally cardiac gated and non-gated RS-EPI-DW images are acquired with the use of parallel imaging. To achieve a smaller effective TE, the blinds are acquired with Partial Fourier imaging. The methods used to phase correct and reconstruct the resulting data are described. The datasets are reconstructed with various overlapping factors to assess whether physiological motion significantly degrades the image quality. It is assessed whether the RS-EPI scan time can be reduced through the use of non-gated acquisitions with minimally overlapping blinds using a typical set of scan parameters we are using for high resolution DW acquisitions. Materials & Methods: The RS-EPI spin echo-based (twice-refocused) diffusion pulse sequence timing diagram is shown in Fig. 1. For each TR, an imaging echo (or ‘blind’) and its accompanying navigator echo are acquired. Each navigator echo is used only to sample the central blind of k-space. The imaging echo fills k-space with separate (adjacent or overlapping) blinds until the target resolution is reached. Depending upon the number of blinds chosen, B; the blind width, W; and the target resolution N (in the readout-direction) – the amount the blinds may overlap, dW, is described by the overlapping factor, OF. In the case of parallel imaging, only the central blind is acquired, using a GRAPPA-acceleration factor of R = NEX. This blind can be used for referenceless Nyquist ghost parameter estimation (2) and GRAPPA (3-4) calibration, values which are applied to all other (b = 0 and DW blinds). A summary of the steps used to reconstruct the partial Fourier GRAPPA-accelerated RS-EPI data is shown in Fig. 2a. For the navigator (phase) correction, each navigator is windowed in k-space by a triangular function used for PROPELLER DWI (5,6) prior to Fourier transformation (FFT). This removes all low-frequency spatially varying phase in image space for each blind (6). There are three apparent differences between the phase correction of PROPELLER and that of RS-EPI (see Fig. 2b). Firstly, RS-EPI is not self-navigated, therefore the phase of a blind is removed from the phase of the accompanying windowed navigator (rather than from the phase of a windowed version of the blind itself). Secondly, to preserve the distance of the blind relative to the k-space center for off-centered blinds, they cannot be individually reconstructed with partial Fourier reconstruction (this step is instead performed after gridding). Rather, the

navigator undergoes partial Fourier (POCS) reconstruction (7,8), and the high-spatial frequency blind edges are discarded, to a size equivalent to that of the imaging blind. This provides a phase map that can be used for correction. Thirdly, because the navigator phase is inverted due to the 180º pulse, the phase correction step is a multiplication rather than a division. All scans were performed on a 3T whole-body GE EXCITE system (Milwaukee, WI, USA; G = 40 mT/m, SLR = 150 mT/m/s) using an eight-channel head coil. Datasets were acquired on a healthy volunteer. To provide a dataset with which to test various overlapping factors, GRAPPA-accelerated RS-EPI images were acquired with and without peripheral cardiac gating at in-plane target resolutions of 288 x 288 using B = 33 blinds of width 64 (OF = 86%). The acquisitions consisted of one b = 0 s/mm2 and one b = 1000 s/mm2 applied in the S/I direction. Three repetitions of the non-gated experiment were made. Other imaging parameters were as follows: R (=NEX) = 3; TE = minimum (68 ms); number of overscans (NO) = 18; TR = 3 RR intervals (gated), TR = 3 s (non-gated acquisitions); and FOV = 24 cm. All RS-EPI datasets were reconstructed with the use of the navigator correction outlined in Fig. 2b. For both acquisitions, the 33 acquired blinds were reconstructed with varying OFs. Results: Fig. 3 shows non-gated DW-RS-EPI datasets (B = 33, OF = 86%) reconstructed without and with navigator correction. As shown, navigator correction corrects for the majority of phase shifts/ghosting artifacts that occur between blinds, resulting in considerably improved SNR. Fig. 4 shows navigator-corrected gated and non-gated datasets reconstructed with various blind

overlapping factors. As shown, ignoring the loss of SNR with decreasing overlapping factor, even adjacent (OF = 0 %) blinds are robust to artifacts due to physiological motion. Discussion: In this abstract, the navigator-corrected non-gated DW-RS-EPI acquisitions rendered images with comparable quality compared with gated acquisitions. However, in the case of severe brain motion, this may not rule out the possibility of complete signal dropout of the central blind. A practical way to reduce this risk would be to increase the number of overscans and acquire one-two extra center blinds. Ignoring these signal voids, there seems to be considerable flexibility in the choice of overlapping factor. This work shows that RS-EPI acquisitions can be used without cardiac gating and with adjacent blinds. However, if k-space shifts due to involuntary patient motion are of concern then it may be sensible to use OF > 0%. Scan time permitting, a higher overlapping factor can also be selected if a higher SNR is desired. It is shown here that patient handling can be simplified with the use of non-gated acquisitions, enabling the acquisition of high resolution DW images with minimal distortion in a clinically relevant scan time. The criteria for minimally overlapping blinds (reduced scan time) may make this sampling strategy a useful alternative to other methods used for navigated DW imaging. References: 1) Porter ISMRM 2004;442. 2) Nordell ISMRM 2007:1833. 3) Griswold MRM 2002;47:1202-1210. 4) Qu JMR 2005;174(1):60-67. 5) Pipe MRM 1999;42(5):963-969. 6) Pipe MRM 2002;47(1):42-52. 7) Haacke JMR 1991;92:126-145. 8) Liang Rev MRM 1992;4:67-185. 9) Jackson IEEE TMI 1991;10:473-478. Acknowledgements: This work was supported in part by the NIH (2R01EB002711, 1R21EB006860), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas

Foundation, Oak Foundation, and the Swedish Research Council (K2007-53P-20322-01-4).

Figure 1: (left) Pulse sequence timing diagram for the RS-EPI, twice-refocused spin echo-based diffusion sequence. The RF pulses (spectral-spatial 90º and refocusing 180º); the diffusion gradients GD; and the imaging and navigator echo are shown. (right) Resulting k-space, filled with an odd number of separate blinds, B, (indicated by green, grey, and black) of a given blind width, W, and overlapping factor, OF = dW/W. A fully sampled central blind (interleaved black, red, and blue trajectories) is used to get the ghost calibration parameters and GRAPPA weights, which are applied to all other blinds.

Figure 3: RS-EPI DWI non-gated datasets (b=1000 s/mm2, S/I direction) acquired with N = 288, R =NEX=3, NO = 18,W=64, OF=36%, FOV = 24 cm, slthck = 5 mm, TR = 3s and ascan time = 2:10 min (incl. b=0). (left) without, and (right) with phase correction.

Figure 2: (a) Summary of the reconstruction steps applied to the partial Fourier RS-EPI b = 0 and diffusion-weighted data. A fully-sampled central blind provides a central segment for FOV/2-ghost correction and GRAPPA calibration. Individual interleaves of each blind are now complex-averaged to form a single blind. A 2D FFT is applied to each blind, and gridding (9) of the partial Fourier data is performed to combine all blinds in k-space. POCS reconstruction is performed for each coil to fill in the remaining extent of k-space. After an inverse FFT, the final image is produced by combining images from all coils via performing the sum of squares. (b) Triangular phase correction process applied to each partial Fourier diffusion-weighted blind in RS-EPI.

(b)

(a)

3D SAP-EPI for Self-Navigated T1w Spoiled Gradient Echo Imaging

S. J. Holdsworth1, S. Skare1, A. Nordell2, R. D. Newbould1, and R. Bammer1 1Department of Radiology, Stanford University, Palo Alto, CA, United States, 2Hospital Physics, Karolinska University Hospital, Stockholm, Sweden

Introduction: 3D T1-w Spoiled Gradient Echo (SPGR) imaging is commonly used in the clinical care as well as for research due to its high gray-white matter contrast and isotropic resolution. While the short TR makes the total scan time reasonable (~3-10 mins), certain patients have difficulties in remaining still during the scan, which leads to image ghosting and the need for reacquiring the data. Recently, an IR-prepared 2D PROPELLER T1-w sequence has been proposed (1), which is able to correct for in-plane motion. However in 3D, this poses difficulties because of the limited T1 relaxation time following the IR-prepared pulse. It would therefore be of great advantage to acquire k-space in an efficient fashion, using a sampling scheme that can detect and correct for the full 3D rigid body motion of the patient semi-continuously during the scan. As motion induced ghosting for 2D/3D Cartesian imaging occurs due to phase inconsistencies and shifts between adjacent lines in k-space, a design criterion to avoid this is to acquire k-space such that an image volume with full image FOV can be formed in a very short time frame during which the risk of motion is negligible.

Short-axis readout propeller EPI (SAP-EPI) (2) has been suggested as an alternative approach to EPI to achieve higher resolution without the penalty of increasing distortions. In the SAP-EPI scheme individual EPI ‘blades’ are rotated through a central strip in k-space, which similar to PROPELLER allows for 2D motion correction between the blades. To achieve the above goal for 3D imaging, a 3D GRE version of the SAP-EPI sequence is implemented here, by acquiring 3D ‘bricks’. We will show that the acquisition of one brick can be performed with full brain coverage in a couple of seconds, making the risk of intra-brick motion (ghosting) small and leaving only the inter-brick 3D motion to be corrected. We demonstrate motion and distortion-corrected phantom data from controlled motion experiments. Initial human images are presented with good T1-w gray/white matter contrast, acquired with three averages in a sub-minute scan time. Materials & Methods: The 3D SAP-EPI pulse sequence diagram and resulting k-space trajectory is shown in Fig. 1. A 90º spectral-spatial pulse was used for water-only excitation, followed by partition-encoding in the z-direction, a 3-shot SAP-EPI partial Fourier readout in ky, and finally crushers applied in all directions. For the following excitations, the shot index and brick angle in the xy-plane was altered. After a 1D FFT along kz, referenceless Nyquist-ghost correction (3) was applied to each brick independently. For each brick, GRAPPA weights (4,5) were estimated on all interleaves and applied to each shot (6) to recover the brick sampling speed and allow for image based 3D motion correction between the shots. The data are then reconstructed with POCS (7,8) in the ky-direction to fill in the remaining required extent of k-space. At this stage in the reconstruction, the data is FFT’d to the image domain for realignment and motion correction. First, the R bricks per brick angle originating from each shot are 3D motion corrected and averaged. Second, all bricks together are simultaneously motion and distortion corrected using a new technique based on ideas by Andersson et al. (9,10). This algorithm uses the combination of all blades for estimating the ΔB0 field, correcting for motion and distortion on all blades without the acquisition of any extra data. Following this correction, image data is 2D-FFT’d back to k-space for gridding (11). Experiments were conducted on a 1.5T whole-body MRI unit (GE Excite, G = 50mT/m, SLR = 150 mT/m/s) and an eight-channel head coil. The following scan parameters were used on a cylindrical phantom: a target resolution of 192x192, seven partial Fourier-encoded blades of width 48, overscans = 24, a GRAPPA-acceleration factor R = NEX=3, TR/TE = 43 ms/9 ms, FOV = 25.6 x 25.6 x 25.6 cm, and 64 z-partitions resulting in a slice thickness of 4 mm, a brick frame rate of 2.7 s, and a scan time of 57 s. Two phantom 3D SAP-EPI datasets were acquired, the second with an in-plane rotation of ~10º. Blade data were mixed such that every second blade was chosen from the rotated dataset. For human studies, the same scan parameters were used as in the phantom study. Results: A phantom image obtained from a mixed blade dataset is shown in Fig. 2. Without correction, distortions and motion (depicted by the white arrow and curly braces, respectively) are evident in the uncorrected image. These artifacts are largely corrected for with the application of the motion and distortion correction technique discussed above. Fig. 3 shows preliminary human data, depicting a subset of 64 partitions (4 mm thick) acquired in a scan time of 19 s per NEX.

Discussion & Conclusion: Here we have presented an efficient propeller-based readout method that does not require the acquisition of FSE readouts, and enables the fast acquisition of T1w-SPGR images. Its inherent ability to allow motion- and geometric- distortion correction (Fig. 2) without the acquisition of any extra data makes 3D SAP-EPI a promising alternative sampling strategy to standard 3D T1w SPGR – a technique that often suffers from ghosting artifacts due to motion. In the event that the brick frame rate (of 2.7 s in this case) results in motion between shots, this brick could be re-acquired. Initial experiments on a human volunteer (Fig. 3) yielded images with high grey/white matter contrast. For this work we plan to acquire and correct for controlled/step wise and continuous motion on volunteers and compare with conventional 3D T1w SPGR. In the case of under-sampled blades, we will estimate the GRAPPA weights using a continuous GRAPPA-kernel without the need for external calibration data (12,13). Using the scan parameters above, this would result in a total scan time of ~19 s (64 partitions, 7 blades, TR = 43 ms, brick frame rate = 2.7 s). For future work, we aim to perform fMRI with the acquisition of full TE blades. With the short scan time, immunity to ghosting and inherent ability to correct for motion and geometric distortions made possible through the use of 3D SAP-EPI, this sequence may be a useful alternative sampling strategy for high resolution 3D SPGR imaging. References: 1) Takei N et al. ISMRM 2007:1728. 2) Skare S. et al. MRM 2006;55:1298-1307. 3) Nordell A et al. ISMRM 2007:1833. 4) Griswold MA. et al. MRM 2002;47:1202-1210. 5) Qu P. et al. JMR 2005;174(1):60-67. 6) Skare S. MRM 2007;57:881–890. 7) Haacke EM et al. JMR 1991;92:126-145. 8) Liang ZP et al. Rev MRM 1992;4:67-185. 9) Andersson JL. Neuroimage 2003;20(2):870-888. 10) Skare S. MRM 2005;54(1):169-181. 11) Jackson JI. IEEE Trans Med Imag 1991;10:473-478. 12) Skare S. et al ISMRM 2006;1734. 13) Skare S. et al. ISMRM 2006; 1743. Acknowledgements: This work was supported in part by the NIH (2R01EB002711, 1R21EB006860), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, Oak Foundation, and the Swedish Research Council (K2007-53P-20322-01-4).

Figure 1. 3D SAP-EPI pulse sequence timing diagram and corresponding traversal of k-space.

Figure 3: Human brain scans acquired with 3D SAP-EPI. Parameters were: a target resolution of 192 x 192, blade width of 48, 7 blades, R = NEX = 3, TR/TE = 43 ms/9ms, a FOV = 25.6 x 25.6 x 25.6 cm, and 64 partitions resulting in a voxel size of 4 mm.

Figure 2. (left) Phantom image using mixed blade data from two 3D SAP-EPI acquisitions, one with the phantom rotated by ~10º. Every second blade (out of a total of seven blades) is chosen from the rotated dataset. (right) Same dataset after motion and distortion correction.

Comparison of Short-Readout Trajectories for Diffusion-Weighted Imaging

S. J. Holdsworth1, S. Skare1, R. D. Newbould1, A. Nordell2, and R. Bammer1 1Department of Radiology, Stanford University, Palo Alto, CA, United States, 2Hospital Physics, Karolinska University Hospital, Stockholm, Sweden

Introduction: “Short-Axis readout Propeller EPI” (SAP-EPI) (1), its dual-blade variant (dual-blade SAP-EPI) (2), and Readout-Segmented EPI (RS-EPI) (3) have been proposed as variants of EPI for high-resolution diffusion-weighted (DW) imaging. These “short-readout” (sr)-EPI readouts use a faster traversal of k-space and thus minimize artifacts from off-resonant spins and T2

* decay resulting in significantly reduced distortions compared to single-shot EPI, particularly when used in combination with GRAPPA (1). There are a few intricacies of sr-EPI sampling strategies that may affect the scan efficiency and overall image quality. In addition to the requirement (or not) of an extra navigator, or the use of dual-readouts, the scan efficiency will also be dependant upon the diffusion preparation time. Thus, the purpose of this abstract is to assess these schemes with regard to diffusion preparation/acquisition ratio, normalized scan time, and image quality for a typical set of scan

parameters we are using for high resolution GRAPPA (4-5)-accelerated DWI. Materials & Methods: The three k-space trajectories and corresponding pulse sequence diagrams are shown in Fig. 1a and b, respectively. RS-EPI segments k-space into individual EPI ‘blinds’ along the readout direction, and requires an additional navigator blind (for phase correction of the DW blinds) acquired with the use of an additional refocusing pulse. SAP-EPI rotates individual ‘blades’ through the center of k-space, and does not require an extra navigator. For the dual-blade SAP-EPI method, a second 180° pulse is used to acquire a second blade, with the aim to achieve a shorter scan time. Striving for similar effective TE’s between the two blades, the first and second half-Fourier blades are acquired inwards and outwards respectively from the k-space center. Experiments were conducted on a 1.5T whole-body MRI unit (GE Excite, G = 50mT/m, SLR = 150 mT/m/s) and an eight-channel head coil. To implement the RS-EPI sequence, our existing dual-blade SAP-EPI readout was modified such that the second echo served as a navigator, and with the imaging echoes acquired in an adjacent fashion. T2w (b = 0) and DW datasets were acquired on human volunteers using all proposed sr-EPI variants using the following diffusion preparation schemes: 1) Twice-refocusing with standard x,y,z diffusion encoding (or DTI), and 2) Stejskal-Tanner diffusion preparation with tetrahedral encoding (which minimizes the TE for a given b-value). A typical set of scan parameters that we have been using for high-resolution GRAPPA-accelerated DW sr-EPI imaging were used: a blade width of 64, a fixed target resolution of 288 x 288, a GRAPPA-acceleration factor R = 3, Partial Fourier encoding with 18

overscans, a slice thickness of 5 mm, TR = 3 s, a FOV = 26 cm, and a b-value of 1000 s/mm2. RS-EPI used 5 blinds, SAP-EPI used 6 blades, and dual-blade SAP-EPI 3 orthogonal blades. Three repetitions of each sequence were conducted, each of which were phase corrected using a triangular windowing approach (6). The SNR efficiency as a function of SNR/sqrt(sequence time x blades) was obtained by taking the relative standard deviation over the mean of the three repeated b = 0 scans. The SNR was calculated as 1/mean(noise maps). A new distortion correction method based on the Reversed Gradient Polarity method (7,8) was applied to the SAP-EPI acquisitions. With this method, the ΔB0 field was estimated on (and applied to) the SAP-EPI blades, without the need for collecting additional data. Results: The minimum TEs achieved for both sequences are shown in Table 1. T2w images and noise maps with the corresponding SNR values for each sr-EPI diffusion preparation scheme are in Fig. 2. While the SAP-EPI and dual-blade SAP-EPI images presented have been corrected for distortion, the noise maps are calculated from the SAP-EPI variants without correction. Fig. 3 shows sr-EPI isotropic DW images from the dataset acquired with twice-refocusing. Discussion & Conclusion: As given by the SNR values and noise maps in Fig. 2, dual-blade SAP-EPI is shown to

be less effective than originally anticipated, despite the acquisition of an extra imaging blade per TR. Given our choice of parameters and hardware, the longer TE’s (and late ending of the second blade) of dual-blade SAP-EPI, combined with the reduced number of slices that can be acquired per TR seems to result in a disadvantage with respect to SNR and T2 blurring. However, the properties of the second echo may need to be investigated further due to possible phase inconsistencies of the 180º pulse. Comparing RS-EPI and SAP-EPI, a slightly higher SNR is achieved for RS-EPI in the twice-refocused approach with x, y, z

diffusion encoding (Fig. 2a). This may be explained by the requirement for fewer blinds/blades to fill k-space in RS-EPI, despite that more slices/TR can be acquired for SAP-EPI. The reverse is true, however, with the use of the Stejskal-Tanner diffusion preparation with tetrahedral encoding (Fig. 2b). The reason for this difference may partly be attributed to blurring due to the non-Cartesian nature of SAP-EPI, but more likely to its increased acquisition/sequence time ratio. With regard to overall image quality, it can be observed in Figs. 2 and 3 that residual distortion in SAP-EPI results in blurring, which can limit the effective resolution. On the contrary, the unidirectional distortions in

RS-EPI allow the image resolution to be increased further, while the effective resolution is only limited by T2 decay and scan time. In summary, the short-axis EPI variants SAP-EPI and RS-EPI should be selected depending upon the scan parameters and diffusion preparation used. Further work will include simulations to disentangle distortions, RF effects and T2-decay. While the effect of eddy currents is already minimized with the use of sr-EPI readouts, for any residual eddy currents we anticipate the use of the Stejskal-Tanner method in combination with eddy current correction. References: 1) Skare S. MRM 2006;55:1298-1307. 2) S Skare, ISMRM Arizona, 2007 3) Porter D et al. ISMRM 2004;442. 4) Griswold MA. et al. MRM 2002;47:1202-1210. 5) Qu P. et al. JMR 2005;174(1):60-67. 6) Pipe JG. MRM 1999;42(5):963-969. 7) Andersson JL. Neuroimage 2003;20(2):870-888. 8) Skare S. MRM 2005;54(1):169-181. 9) Haacke EM et al. JMR 1991;92:126-145. 10) Liang ZP et al. Rev MRM 1992;4:67-185. Acknowledgements: This work was supported in part by the NIH (2R01EB002711, 1R21EB006860), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, the Oak Foundation, and the Swedish Research Council (K2007-53P-20322-01-4).

Figure 3. Isotropic sr-EPI DWI images (b =1000 s/mm2, twice-refocusing, tetrahedral encoding) acquired at a target resolution of 288 x 288.

Diffusion preparation & encoding

Minimum TE RS-EPI & SAP-EPI

dSAP-EPI

(TE1/TE2) Twice refocused,

x,y,z encoding 70 ms 108/119

ms Single refocused,

tetrahedral encoding 43 ms 76/92 ms

Table 1. Minimum echo times for the three sr-EPI variants for the diffusion preparation module used in the text.

Figure 1. (a) RS-EPI, SAP-EPI, and dual SAP-EPI k-space trajectories. For all trajectories, the partial

Fourier data are reconstructed with POCS (9-10) to fill in the remaining required extent of k-space. (b) sr-EPI pulse sequence diagrams following diffusion preparation module.

Figure 2. (a) One b = 0 image selected from each sr-EPI dataset acquired using a twice refocused diffusion preparation and x,y,z encoding (b = 1000 s/mm2) and corresponding noise maps below. The numbers displayed for each image are the normalized SNR values. For the SAP-EPI variants, the images displayed have been corrected for distortion. (b) As above, acquired instead using a Stejskal-Tanner diffusion preparation and tetrahedral encoding.

GRAPPA-accelerated Readout-Segmented EPI for High Resolution Diffusion Imaging

S. J. Holdsworth1, S. Skare1, R. D. Newbould1, A. Nordell2, and R. Bammer1 1Department of Radiology, Stanford University, Palo Alto, CA, United States, 2Hospital Physics, Karolinska University Hospital, Stockholm, Sweden

Introduction: Readout-segmented (RS)-EPI (1) has been suggested as an alternative approach to EPI for high resolution diffusion-weighted imaging (DWI). In RS-EPI scheme, segments of k-space are acquired along the readout direction. This reduces geometric distortions due to the decrease in echo spacing. Here we demonstrate that a combination of the RS-EPI k-space trajectory and parallel imaging results in high resolution T2-weighted and diffusion-weighted images with minimal geometric distortions. Clinical RS-EPI DWI images delineate tumors near the auditory canals, nasal cavity, and the brain stem - areas traditionally difficult for EPI-based trajectories to image with high quality. DTI images are also acquired and compared with GRAPPA-accelerated EPI. The short scan times made possible through the use RS-EPI may make it a useful alternative sampling strategy for high resolution diffusion imaging.

Materials & Methods: Fig. 1 shows the k-space trajectory for RS-EPI. For each repetition, each (partial-Fourier encoded) segment or ‘blind’ may be acquired with several interleaves, each accompanied by an extra navigator for phase correction. Depending upon the number of blinds chosen, the blind width, W; and the target resolution in the readout-direction – the amount the blinds may overlap, dW, is described by the overlapping factor, OF. In the case of parallel imaging, only the central blind is acquired with GRAPPA -acceleration factor R = NEX. This blind can be used for referenceless ghost parameter estimation (2) and GRAPPA (3-4) calibration, values which are applied to all other (b = 0 and DW blinds). The RS-EPI sequence was developed for a 3T whole-body GE EXCITE system (Milwaukee, WI, USA). An 8-channel head coil and a high-performance gradient system (40 mT/m, SLR = 150 mT/m/s) was used. Patient studies were IRB approved and volunteers signed consent forms. For volunteer studies, axial, sagittal, and coronal RS-EPI b = 0 and b = 1000 s/mm2 images were acquired at a target resolution of 288 x 288. Imaging

parameters were: FOV = 24 cm; a slice thickness = 5 mm; TR/TE = 3 s/68 ms; R = 3; NEX = R; 9 blinds of width 64 (OF = 50%); isotropic tetrahedral encoding with b = 1000 s/mm2, resulting in a scan time of 6:48 min for each of the three scan planes. For patient studies, a RS-EPI-DW acquisition was performed in a patient with a brain stem cavernoma and with a stroke in the brain stem. The dataset used a 192 x 192 in-plane target resolution; a GRAPPA-acceleration factor R = NEX = 2; five blinds of width 64 (OF = 40%); a FOV = 24cm; slice thickness = 4 mm; partial-Fourier encoding with NO = 18; TR/TEmin = 3s/67ms; and a total scan time of 2 mins. The DWI images were acquired using a b = 0 s/mm2 complemented by three b = 1000 s/mm2 images (x, y, and z direction), resulting in a scan time of 2 min. For comparison, a standard single-shot (ss)EPI DW image was acquired with an in-plane target resolution of 128 x 128. To compare the performance of GRAPPA-accelerated EPI with RS-EPI, diffusion-tensor images (DTI) were acquired on a volunteer with an equivalent scan time. Both datasets used an in-plane target resolution of 288 x 288, a FOV = 24 cm, slice thickness of 5 mm, and R = NEX = 3. For the RS-EPI dataset, 7 blinds were acquired with a blind width of 64

(OF = 35%). For the EPI dataset, 7 repetitions of the diffusion scheme were implemented. Diffusion weighting with a b = 1000 s/mm2 was carried out along 15 isotropically distributed directions, complemented by three b = 0 s/mm2 images. With a TR of 3 s for both datasets, the total scan time was 19 minutes. Isotropic DWI, fractional anisotropy maps; and directionally encoded color maps are presented. An FSE sequence acquired at the same target resolution was also acquired for geometric reference. Results: In Fig. 2, RS-EPI b = 0 s/mm2 and isotropically weighted b = 1000 s/mm² images acquired at an in-plane target resolution of 0.8 mm2 (matrix size 288 x 288) present with little blurring and distortion. DW images of the cavernoma patient in Fig. 3 show that while the standard 128 x 128 ssEPI b = 0 s/mm2 and isotropically weighted b = 1000 s/mm² images (Fig. 3a) suffer from substantial distortion and blurring, the RS-EPI images (Fig. 3b) clearly delineate the brain stem cavernoma. The improvement in geometric distortion properties is particularly noticeable regions around the nasal cavity, and areas adjacent to the hemorrhagic lesions. Fig. 4 shows an isotropic RS-EPI-DW dataset depicting a dataset of a patient suffering from a stroke in the brain stem. Fig. 5 shows two slices from each of the GRAPPA-accelerated EPI and RS-EPI DTI datasets acquired with an in-plane target resolution of 288 x 288 with the same scan time (19 min). While the additional repetitions of the EPI dataset yield images with high SNR, considerable geometric distortion remain at the level of the eyes, nasal cavities, auditory canals, and the occipital and frontal lobe. Summary: It is demonstrated that the combination of parallel imaging and the RS-EPI k-space trajectory gives resulting in images with reduced geometric distortions and exquisite spatial resolution at 3T. This method allows the clear delineation of structures and pathology in the lower parts of the brain, areas traditionally difficult for EPI to acquire with reliable image quality. References:1) Porter D et al. ISMRM 2004;442. 2) Nordell A et al. ISMRM 2007:1833. 3) Griswold MA. et al. MRM 2002;47:1202-1210. 4) Qu P. et al. JMR 2005;174(1):60-67. Acknowledgements: This work was supported in part by the NIH (2R01EB002711, 1R21EB006860), the Center of Advanced MR Technology at Stanford (P41RR09784), the Lucas Foundation, the Oak Foundation, and the Swedish Research Council (K2007-53P-20322-01-4). The authors are grateful to Anne Sawyer and Sandra Rodriguez for providing assistance with the patient studies. I would like to thank Bronwen Holdsworth for her inexhaustible help with proofreading.

Fig. 1: k-space trajectories for the RS-EPI sequence. K-space is filled with an odd number of separate blinds, B, (indicated by green, grey, and black) of a given blind width, W, and overlapping factor, OF = dW/W.

Fig. 2: RS-EPI (left) b = 0 and (right) b=1000 s/mm2 (isotropic tetrahedral encoding) coronal images. Imaging parameters were: FOV=26 cm, slice thickness = 5 mm, N = 288, R = NEX = 3, 9 blinds, W=64, OF=50%, TR/TE = 3s/62ms, scan time = 6:48 min.

Fig. 4: RS-EPI isotropic DWI dataset (x,y,z direction, b= 1000 s/mm2) acquired with 5 blinds, an in-plane target resolution =192x192, W = 64, slthck = 5mm, R (= NEX)=2, 18 overscans, TR = 3s, and a total scan time = 2 min.

Fig. 3: T2w (b=0) and isotropic DW datasets (x,y,z direction, b=1000 s/mm2) from a brain stem cavernoma patient. (a) ssEPI acquired at a target resolution of 128 x 128. (b) RS-EPI image acquired with a target resolution of 192 x 192, R = NEX = 3, and 5 blinds (W = 64, OF = 40%). A FOV =24 cm, slthck = 4 mm, partial-Fourier encoding with 18 overscans, and a TR = 3 s were used, resulting in a scan time of 2 min (RS-EPI) and 0:15 s (ssEPI).

Fig. 5: GRAPPA-accelerated (a) EPI and (b) RS-EPI DTI datasets acquired on a healthy volunteer (three b = 0 s/mm2 and 15 directions with b = 1000 s/mm2). Imaging parameters were: R = NEX = 3, a target resolution of 288 x 288, partial Fourier encoding with NO = 18, FOV = 24 cm, slice thickness = 5mm, and a TR = 3s. b) used 7 blinds (W = 64,OF = 36%) and a) 7 repetitions of the DTI sequence to achieve an equivalent scan time (19 min). A 288 x 288 FSE image is shown for geometric reference.

Benchmarking SAP-EPI and PROPELLER for Diffusion Imaging

S. J. Holdsworth1, R. Bammer1, R. D. Newbould1, and S. Skare1 1Radiology, Stanford University, Palo Alto, CA, United States

Introduction: “Short-Axis readout Propeller EPI” (SAP-EPI) (1) has been proposed as a new variant for EPI-based PROPELLER (2). The short-axis readout uses a faster traversal of k-space and thus minimizes artifacts from off-resonant spins and T2

* decay. It has been shown that SAP-EPI is superior in image quality over its long-axis variant (1). Historically, DWI PROPELLER has been combined with FSE readouts because of FSE’s immunity to susceptibility distortions and eddy current effects. This is the only commercially available alternative to EPI for DWI, and has demonstrated increased geometrical and motion correction properties due to the RF refocusing pulses. Clinically, this has proven a great utility for the diagnostic work-up of lesions in the posterior fossa and brain stem, as well as in patients with surgical material or with hemorrhage. However, the requirement for large flip angle FSE trains in PROPELLER-FSE to combat violations of the CPMG condition as well as quite long scan times can pose difficulties in critically ill patients, and raise problems at higher magnetic field strengths where the specific absorption rate (SAR) issues and B1 inhomogeneities increase. In these situations, with the reduced distortions and minimum SAR of SAP-EPI in concert with the great motion insensitivity of the PROPELLER trajectory, SAP-EPI might pose an attractive alternative to FSE-based PROPELLER. Determining the strengths and weaknesses of both methods and comparing them to single-shot EPI (ssEPI) is therefore of great interest. The purpose of this work was to assess DWI PROPELLER-FSE and DWI SAP-EPI with regard to performance and image quality for a typical range of scan parameters used in clinical practice. Materials & Methods: Side-by-side comparisons of PROPELLER-FSE (T2w and DWI) provided by the vendor, ssEPI, as well as SAP-EPI accelerated by GRAPPA (R=3) (3) developed in-house were performed on a 3T whole-body MRI unit (GE Signa LX) using an eight-channel head coil and a high-performance gradient system (40mT/m, SLR=150mT/m/s). Here, PROPELLER-FSE determined the common minimum TR for a given number of slices across all three sequences under test because of the additional time for applying refocusing pulses. By using a fixed spatial resolution of 1.1×1.1×5mm, the following assessments were performed: 1) to determine the number of slices that can be interleaved for a given TR; 2) determine the minimum TE per blade width (SAP-EPI) or per echo train length (ETL) (PROPELLER-FSE); and 3) determine the SAR associated with each sequence. In addition, the level of geometric distortions in SAP-EPI was determined as a function of blade width (blade width range: 16, 32, and 64) and was compared against optimized FSE-PROPELLER (ETL range: 8, 16, and 24), as well as ssEPI. All experiments were performed in healthy young volunteers (28cm FOV, TR=4.8s) using peripherally gated DWI acquisitions to minimize confounding effects from brain pulsation artifacts. The SAP-EPI images were reconstructed with POCS (4) - since we found that preserving the phase resulted in markedly reduced artifacts compared with homodyne reconstruction used in previous work (2).

Results: For all parameter combinations investigated, SAP-EPI allows a smaller minimum TE, smaller minimum TR (and thus shorter scan time for a given number of slices), and lower average SAR for a given resolution (Table 1). Due to the considerable time occupied by refocusing pulses during the FSE readout and the longer readout (long axis) for each echo within a blade, the effective echo time increases substantially with increasing blade width (Fig. 1). This leads to marked increases in T2-weighting with increasing blade width (not shown). Conversely, the TE of SAP-EPI stays relatively constant with increasing blade width due to the half Fourier acquisition. Factors that determine TE in SAP-EPI are: half Fourier over-scan factor (typically 16-24),

length of each readout gradient lobe, and the slew rate. Example images of T2w SE ssEPI, T2w PROPELLER FSE, SAP-EPI (T2w, DWI) images are shown in Figure 2. While there are substantial geometric distortions and T2*-related blurring in the ssEPI scans there are no apparent

differences in geometric distortion between both PROPELLER methods that were acquired in the same scan time. With a minimum TR of 4.8s, the maximum number of slices achievable is 14 for PROPELLER and 36 for SAP-EPI. Although 2.5 times more slices were acquired with SAP-EPI, the average SAR is 0.67W/kg and 1.5W/kg for SAP-EPI and PROPELLER FSE, respectively. Despite the underlying EPI mechanism, a very promising aspect of SAP-EPI is its robustness against geometric distortions with increasing target resolution - affording resolutions unmatched thus far (768×768) (Fig. 3). By comparing these 768×768 SAP-EPI images with the 256×256 SAP-EPI (Fig. 2), we demonstrate that the distortions (in mm units) are kept constant.

Discussion & Conclusion: The results of this study demonstrate that SAP-EPI is a viable alternative to ssEPI and PROPELLER-FSE. The markedly faster traversal of k-space relative to ssEPI in combination with GRAPPA generates images with negligible geometric distortions within the same imaging time as PROPELLER-FSE. The substantial speed gain of SAP-EPI over PROPELLER-FSE affords larger brain coverage or even smaller blades (and thus further distortion reduction). The absence of refocusing pulses helps to diminish SAR considerably. This is not so much of an issue at 1.5T, but certainly at 3T and higher. B1 homogeneity also deteriorates at higher field

strength and thus the high flip angle regime required in PROPELLER-FSE cannot be maintained across the entire FOV. In this work, we have used POCS reconstruction of the half-Fourier blades as this preserves the image phase of each blade prior to Fourier transforming the blade images to k-space for the final regridding. This was found to yield substantial improvements in the image quality for SAP-EPI. With complex blade data in the image domain due to the POCS reconstruction, further investigation is needed on how we can modify our earlier proposed RGPM distortion correction techniques for SAP-EPI (5), which to date has solely operated on magnitude blade image data. With this issue solved, we anticipate further increase in the effective resolution and overall better geometrical faithfulness in the basal parts of the brain. Further work is also needed for highly accurate echo centering and motion correction schemes at high image resolutions. Moreover, it remains to be shown whether the robustness of SAP-EPI holds true in patients with surgical material (aneurism clips, coils) or hemorrhage. Most likely, both methods have complimentary advantages, and increased speed can be traded for more robustness against field inhomogeneities. Recently, TurboPROP (6) has been introduced - a GRASE variant of PROPELLER-FSE. A future study should focus on a comparison with this method since it combines the benefits of EPI’s fast readout and FSE’s robustness against distortions. In summary, SAP-EPI and PROPELLER FSE are both extremely robust methods far superior to ssEPI. Currently, it seems that PROPELLER-FSE has slight advantages when distortion reduction is required, whilst SAP-EPI excels at higher field when SAR becomes and issue or when higher speed is required.

References:1) Skare S. Magn Reson Med 2006;55:1298-1307. 2) Pipe JG. Magn Reson Med 1999;42(5):963-969. 3) Andersson JL et al. Neuroimage 2003;20(2):870-888. 4) Liang Z-P, Rev Magn Reson Med 1992;4:67-185. 5) Skare S. 2006; Seattle. ISMRM. p 857. 6) Pipe JG. Magn Reson Med 2006; 55(2):380-385. Acknowledgements: This work was supported in part by the NIH (1R01EB002711), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation, and Oak Foundation.

Figure 1: Echo Time vs. echo train length (ETL) for PROPELLER and blade width (SAP-EPI) for an equivalent resolution.

PROPELLER SAP-EPI (3 shots) ETL or blade width x 256

Minimum TR (ms)

Scan time (mins)

Ave SAR (W/kg)

Minimum TR (ms)

Scan time (mins)

Ave SAR (W/kg)

16 x 256 5800 4:44 1.7 1900 4:45 0.49 24 x 256 7900 4:21 1.9 1960 3:08 0.45 32 x 256 10500 4:23 1.9 2000 2:24 0.42

Table 1: Comparison between various parameters for PROPELLER and SAP-EPI for 20 slices, and a given ETL (PROPELLER) or blade width (SAP-EPI) at a fixed target resolution. This assumes a minimum diffusion preparation time of 50ms (b=1000s2/mm).

Figure 2: a) ssEPI T2w image: matrix size 256 x 256; (b-c) SAP-EPI and (d-e) PROPELLER T2w and DWI images (b=1000s2/mm) acquired at a resolution of 1.1x1.1x5mm, TR of 4.8s (scan time 5 mins), and 3 shots. For PROPELLER the ETL = 16, NEX=2, TEmin=101ms. For SAP-EPI the blade width = 32, andTEmin=75ms.

Figure 3: a) ssEPI T2w image (matrix size 256×256); b-c) 0.36mm x 0.36mm x 5mm SAP-EPI T2w and DWI images at 768×768 resolution using a blade size of 32×768, 3 shots, b=1000s/mm2.

(a) ssEPI: T2w (b) SAP-EPI: T2w (c) SAP-EPI: DWI

Comparison of FLASH and TPI Techniques for Sodium Imaging

S. J. Holdsworth1, S. E. Rose1, K. L. McMahon1, D. Maillet1, F. C. Damen2, G. J. Galloway1 1Centre for Magnetic Resonance, University of Queensland, Brisbane, Queensland, Australia, 2Center for MR Research, University of Illinois at Chicago, Chicago,

Illinois, United States Introduction Sodium (23Na) is the second most abundant MR-observable nucleus in living tissue. The application of sodium MRI in diagnostic radiology and clinical research has been limited for two main reasons. The first is due to the relatively low concentration of 23Na in vivo. In normal brain tissue, the intra- and extracellular concentrations of 23Na are approximately 12-14 and 140-160 mM respectively1. The second is due to the short spin-spin (T2) relaxation times of 23Na in vivo. This results from the strong interactions of the 23Na nuclear quadrupolar moment with its local environment2. Biological tissue, such as human brain tissue, shows a fast T2 component in the order of a few milliseconds, and a slow component of approximately 10-30ms. These short relaxation times, combined with the low sensitivity of 23Na make it a challenging nucleus to image with adequate signal-to-noise (SNR) and scan time for clinical use. Twisted projection imaging (TPI), an efficient method for sampling k-space has provided sodium images with high SNR in a fast imaging time3. We have implemented a TPI technique with a complete interactive user-interface for 23Na imaging. We compared phantom and in-vivo FLASH and TPI sodium images obtained with the same resolution and scan time. Materials and Methods Data acquisitions were performed on a 4.47T/40cm animal system (Bruker Biospec, ParaVision 3 beta test version) operating at a sodium frequency of 50.32 MHz, equipped with a single-tuned linear saddle coil. The gradient waveform equations for TPI were programmed so that the user maintains control over the field-of-view, nominal resolution, radial fraction p (% of the maximum k-space radius traversed by a radial line), and maximum gradient strength (Gmax). 23Na TPI data were reconstructed using a convolution gridding method with a Kaiser-Bessel window described by Jackson et al4. A 3D gradient echo sequence was modified to decrease the echo time by reducing the duration of the phase-encoding lobe, omitting the delay between the prephasing gradient lobe of the readout gradient, and by using partial echo acquisition (30%). Both TPI and FLASH acquisitions utilized a short (400us) 70° non-selective RF pulse and a TR of 30ms, a 3D isotropic nominal resolution of 4mm and field-of-view of 13cm. A 100mm x 100mm cylindrical phantom filled with 40mM NaCl and 10% by weight gelatine and four solid tubes of 6mm, 10mm, 16mm, 20mm diameter was used for resolution measurements. In-vivo experiments were performed on anesthetized newborn piglets. Results

(a) SNR= 4 (b) SNR= 8 (c) SNR=7 (d) SNR=16 (e) SNR=18 (f) SNR=13 Figure 1: Phantom (left) and in-vivo piglet (middle and right) 23Na images acquired with a FOV=13cm, 3D isotropic nominal resolution of 4mm, and a total scan time of 8 minutes, where (a),(c) FLASH: TR/TE=30ms/1.9ms, SW=25kHz, NEX=16 (b),(d) TPI: TR/TE=30ms/0.23ms, p=0.3, Gmax=3.7mT/m, NEX=16. TPI 23Na images acquired with the same readout and scan time are shown in the far right, where (e) p=0.4, Gmax= 3.7mT/m, NEX=12 (f) p=1.0, Gmax=1.6mT/m, NEX = 5. Images (c-d) and (e-f) were acquired from different piglets. Images obtained with p=0.4 at two different maximum gradient strengths gave an SNR of 18 (Gmax = 3.7mT/m) and 11 (Gmax = 7.2mT/m) as summarized with the SNR measurements from Fig. 1 in the table below. p Gmax Readout time NEX SNR SNR FLASH TPI (p=0.3) 0.4 3.7mT/m 7ms 12 18 Phantom 4 8 0.4 7.2mT/m 3.7ms 12 11 In-vivo 7 16 1.0 1.6mT/m 7ms 5 13 Table 1. Table 2. Table 1: SNR of phantom and in-vivo images obtained with FLASH and TPI techniques acquired at the same resolution (4mm) and scan time (8mins). Table 2: Summary of the TPI parameters used to acquire images with the same resolution and scan time as in Table 1, with the use of two different radial fractions and maximum gradient strengths. Discussion TPI 23Na images revealed over double the SNR compared with short-TE FLASH images acquired at equivalent resolution and FOV. Although short echo times are achievable with gradient echo schemes, this requires high bandwidths � resulting in images with poor SNR. Although decreasing the bandwidth at the expense of TE generally increases the SNR, the resulting loss of most of the short T2 component may complicate in-vivo concentration measurements. Although small radial fractions result in less sampling of central k-space, they facilitate the use of more averages for a given scan time, resulting in a higher SNR as shown in Table 2. However, the gain in SNR through the use of small radial fractions may be lost with poor selection of the maximum gradient strength. One disadvantage of TPI is that the inherently 3D isotropic nature of the scheme means that, unlike FLASH imaging, partial Fourier encoding is not easily achievable. References 1. K. R. Thulborn et al, Radiology 213:156 (1999) 2. Rooney, W.D., Springer, C.S., NMR in Biomedicine 4:209 (1991) 3. Boada et al, ,MRM 37:706 (1997) 4. Jackson et al, IEEE Transactions on Medical Imaging 10(3):473 (1991)

Proc. Intl. Soc. Mag. Reson. Med. 14 (2006) 3106