HistomorphometHistomorphometry ry
OrOr
How to get numbers out of How to get numbers out of slidesslides
Stephen GreenwaldStephen Greenwald
Pathology Group, Institute of Cell & Molecular Pathology Group, Institute of Cell & Molecular ScienceScience
Barts & The London School of Medicine & DentistryBarts & The London School of Medicine & Dentistry
OutlineOutline What is morphometry?What is morphometry? Why histomorphometry?Why histomorphometry? Measurement methodsMeasurement methods
““Manual”Manual” ComputerisedComputerised
Standard processes in computerised Standard processes in computerised histomorph.histomorph. Image captureImage capture EnhancementEnhancement ThresholdingThresholding MeasuringMeasuring
Micro CT of stented arteriesMicro CT of stented arteries
What is morphometry?What is morphometry?A body of methods for obtaining numerical A body of methods for obtaining numerical information about the shape and size of a information about the shape and size of a structure in terms of quantities such as:structure in terms of quantities such as:
volumevolume surface areasurface area relative amounts of each componentrelative amounts of each component orientation, interconnectionsorientation, interconnections distribution of substructuresdistribution of substructures etc.etc.
Why histomorphometry?Why histomorphometry?
When applied to biological tissue When applied to biological tissue examined microscopically it useful in examined microscopically it useful in correlating structure and function e.g.correlating structure and function e.g. Alveolar or gut villus surface areaAlveolar or gut villus surface area Arterial composition and elasticityArterial composition and elasticity Quantification ofQuantification of
Hyperplasia, dysplasia, hypertrophyHyperplasia, dysplasia, hypertrophy Immunohistochemical or flourescent markersImmunohistochemical or flourescent markers
Area or intensityArea or intensity
Major challengeMajor challenge
To extract information about large 3-To extract information about large 3-D structures from microscopic D structures from microscopic measurements on thin 2-D sectionsmeasurements on thin 2-D sections
To do this histomorphometry uses To do this histomorphometry uses the: the:
Delesse PrincipleDelesse Principle
Delesse PrincipleDelesse Principle
““In a rock composed of a number of In a rock composed of a number of minerals, the area occupied by any given minerals, the area occupied by any given mineral is proportional to the volume of mineral is proportional to the volume of the mineral in the rock”the mineral in the rock”
Repeated determinations of the Repeated determinations of the area area fraction fraction will yield an estimate of the will yield an estimate of the volume fractionvolume fraction..
The more determinations; the better the The more determinations; the better the estimate.estimate.
Delesse A. (1847) Procede mechanique pour determines la composition des roches. Comptes Rendus de l’Academie des Science (Paris) 25, 544)
How to estimate area How to estimate area fractionfraction
paper cutting and weighingpaper cutting and weighing planimetryplanimetry
PlanimetePlanimeterr
How to estimate area How to estimate area fractionfraction
paper cutting and weighingpaper cutting and weighing planimetryplanimetry dot countingdot counting
Dot countingDot counting
Nuclear area/cell area = number of dots in nuclei/number of dots in cellAbsolute area of a structure = number of dots in structure x area of dot square
How to estimate area How to estimate area fractionfraction
paper cutting and weighingpaper cutting and weighing planimetryplanimetry dot countingdot counting square countingsquare counting
Square countingSquare counting34 squares
7 squares
How to estimate area How to estimate area fractionfraction
paper cutting and weighingpaper cutting and weighing planimetryplanimetry dot countingdot counting square countingsquare counting pixel counting in a digital imagepixel counting in a digital image
semi- or fully automatic systemsemi- or fully automatic system
Mainprocessor
Mainprocessor
Computerised Computerised histomorphometryhistomorphometry
VideomemoryVideo
memory
ADCADC
LUTLUT
Imageprocessor
Imageprocessor
StorageStorage
ADCADC
LUTLUT
User.mouse,
light-pen
User.mouse,
light-pen
Stimulants
Microscope
TV camera
Pixel countingPixel counting
Pixel countingPixel counting
Recognising objects by Recognising objects by colourcolour
More difficult More difficult measurementsmeasurements
lengthlength seminiferous tubulesseminiferous tubules
surface areasurface area alveoli, gut villi etc.alveoli, gut villi etc.
counting discrete objectscounting discrete objects cells, nuclei, alveoli, elastic lamellae etc.cells, nuclei, alveoli, elastic lamellae etc.
Size distributionSize distribution cells, nuclei, tumours etc.cells, nuclei, tumours etc.
How to estimate lengthHow to estimate length(Buffon’s needle problem)(Buffon’s needle problem)
If you drop a If you drop a nail/needle on the nail/needle on the floor, what is the floor, what is the probability it will probability it will come to rest over a come to rest over a crack between the crack between the floor boards?floor boards?
Louis le Clerc, Compte de Buffon, (1707 -1788)French naturalist & polymath
Buffon needle problemBuffon needle problemThe probability (The probability (pp) of the ) of the needle (or nail) landing on a needle (or nail) landing on a join depends on the length of join depends on the length of the needle (the needle (ll), the width of the ), the width of the boards (boards (dd) and the angle it ) and the angle it makes with the direction of the makes with the direction of the boards (boards (). The angle ). The angle determines the projected (i.e. determines the projected (i.e. effective) length of the nail, effective) length of the nail, ((llprojproj))
dl
lproj
€
p =l proj
d where l proj is the average projected length
€
l proj =2l
πcosθ.d
0
π
2
∫ θ
=2l
π
€
∴ p =2l
πd
Inverse problem;Inverse problem;i.e. throw the grid at the i.e. throw the grid at the
nailsnails Imagine a contour Imagine a contour
of length of length LL composed of small composed of small elements, elements, ll
Now throw the Now throw the grid (spacing, grid (spacing, dd) at ) at the nails (i.e. the the nails (i.e. the small elements)small elements)
€
Probability (p) of an intersection is :
p =2l
πd
€
Number of "throws" is : L
l
€
Number of intersections N int is the number of
"throws" times the probability of an intersection
N int =L
l.
2l
πd
€
Rearranging the above expression,
we can calculate the total length (L)
L =πd.N int
2
Villus and crypt length Villus and crypt length measurementsmeasurements
How to measure surface How to measure surface areaarea
Measure absolute volume (Measure absolute volume (VV) of entire organ) of entire organ Archimedes, weight (knowing density)Archimedes, weight (knowing density)
Estimate tissue volume fraction from area fractionEstimate tissue volume fraction from area fraction calculate tissue volumecalculate tissue volume
Count intercepts (Count intercepts (NNintint) using grid of total length () using grid of total length (LL))
€
SA =2VN int
L
Pattern recognitionPattern recognition
normal v abnormal morphologynormal v abnormal morphology displasia, metaplasiadisplasia, metaplasia
counting poorly stained structurescounting poorly stained structures nuclei, nuclear organelles, leucocytesnuclei, nuclear organelles, leucocytes
Normal nucleus:Area = 10m2, perimeter =14m
Abnormal nucleus:Area = 10m2, perimeter =26m
Standard processesStandard processes Image captureImage capture EnhancementEnhancement
contrast/colourcontrast/colour background correctionbackground correction
Thresholding (identifying structures Thresholding (identifying structures of interest)of interest) colourcolour intensityintensity shapeshape
MeasurementMeasurement area, perimeter, countingarea, perimeter, counting
1.5MB1.5MB
10kB10kB
1kB1kB
Image enhancement:Image enhancement:shade correctionshade correction
Uneven background illumination
Image enhancement:Image enhancement:shade correctionshade correction
Original image with uneven illumination
Image enhancement:Image enhancement:shade correctionshade correction
Shade corrected image
Contrast enhancement:Contrast enhancement:
OriginalEnhanced
Thresholding by colourThresholding by colour
EnhancedThresholded
MeasurementMeasurementSection Field Area [sq micron] Elastin [%] Collagen [%] VSMC [%] E+C [%] V+E [%] V+C [%] Unthreshed [%] Total [%]
155-05-c2 1 22437.95 19.29 43.8 31.37 0 0 2.29 7.53 100.232 17619.23 22.46 39.39 29.52 0 0.47 0 8.3 1003 17424.26 21.83 37.6 32.66 0 0.31 1.56 8.71 99.975 16765.18 26.06 40.76 31.91 0.02 0 0.56 2.58 101.78
18561.655 22.41 40.3875 31.365 0.005 0.195 1.1025 6.78 100.495
152-05-d 1 21366.93 23.61 43.85 29.32 0 0 0.88 3.93 100.272 18108.37 19.64 55.43 35.24 0.87 2.37 8.99 1.62 101.983 18895.89 18.56 48.15 30.12 0 1.71 0 3.21 100.524 20573.07 20.61 60.18 26.84 0 1.27 6 -1.4 100.98
19736.065 20.605 51.9025 30.38 0.2175 1.3375 3.9675 1.84 100.9375
145-05-d 1 18244.94 16.79 52.13 24.36 0 1.07 0.62 8.8 100.392 20463.62 18.13 60.02 29.14 2.63 1.64 3.51 1.72 101.233 15651.55 15.13 62.22 27.6 1.91 0.97 2.56 1.81 101.334 20284.31 17.11 58.67 28.75 0.34 1.57 4.7 3.23 101.15
18661.105 16.79 58.26 27.4625 1.22 1.3125 2.8475 3.89 101.025
143-05-D 1 17682.66 20.24 54.25 24.5 1.99 0.07 0.01 4.16 101.082 16752.71 19.38 58.03 23.25 1.9 0.18 0.01 2.75 101.333 18252.77 18.52 61.73 19.23 0 0.37 2.3 3.38 100.994 16264.18 14.28 55.54 24.95 2.23 0.44 0 7.32 100.64
17238.08 18.105 57.3875 22.9825 1.53 0.265 0.58 4.4025 101.01
157-05-D 1 14207.13 17.18 66.19 12.97 2.19 0.56 0 6.57 100.722 17832.78 18.35 59.46 15.65 0 0.44 0.29 6.8 100.133 16970.9 17.73 56.9 23.37 0 0.49 5.44 5.03 99.714 15497.26 24.48 56.19 17.1 0.96 1.24 0.43 2.09 100.91
16127.0175 19.435 59.685 17.2725 0.7875 0.6825 1.54 5.1225 100.3675
The Effect of Stent Oversize The Effect of Stent Oversize Stiffness & Structure on Stiffness & Structure on
restenosisrestenosis In vivo radiographic measurement of In vivo radiographic measurement of
stent dimensions in pig carotid and stent dimensions in pig carotid and iliac arteriesiliac arteries
Development of a micro CT method Development of a micro CT method for stented vessel morphometry on for stented vessel morphometry on excised arteriesexcised arteries
Study aimsStudy aims
To quantify degree of restenosisTo quantify degree of restenosis Effect of stent oversize and stiffnessEffect of stent oversize and stiffness
To compare two stent typesTo compare two stent types SMART stent (a standard design)SMART stent (a standard design)
Major problem is restenosisMajor problem is restenosis
Compliant ended stent (a novel design). Compliant ended stent (a novel design). Developed by collaborators, J.E. Moore & Developed by collaborators, J.E. Moore & Colleagues at Texas A & MColleagues at Texas A & M
HypothesisHypothesis
By matching the compliance of the stent to that of the “native” artery, flow disturbances and bending stress at the stent/artery junction is reduced and hence restenosis is minimised
Stents used in the StudyStents used in the Study
SMART stent Compliant Ended Stent
Compliance Matching Compliance Matching StentStent
Rigid in the centre to Rigid in the centre to provide recoil provide recoil resistanceresistance
Parabolic and Parabolic and cantilevered strutscantilevered struts gradual change in gradual change in
compliancecompliance reduces stress reduces stress
concentration and concentration and bendingbending
Less disturbed flowLess disturbed flow
MethodsMethods
65 stents implanted in the iliac and 65 stents implanted in the iliac and carotid arteries of 17 Large White pigscarotid arteries of 17 Large White pigs
Lumen diameter determined before and Lumen diameter determined before and after implantation by angiographyafter implantation by angiography Follow-up angiography on days 3,7 and 28 Follow-up angiography on days 3,7 and 28 At day 28 the arteries were pressure At day 28 the arteries were pressure
perfused and removed for histology and CT perfused and removed for histology and CT scanning scanning
4
5
6
7
0 5 10 15 20 25 30 35
Position along stent [mm]
Lumen diameter [mm]
Vessel dimensions Vessel dimensions determined by automatic determined by automatic edge detecting algorithmedge detecting algorithm
Micro CT of excised Micro CT of excised vesselsvessels
Vessels pressure fixed in situ (10% formol saline)Vessels pressure fixed in situ (10% formol saline)
Excised and immersed in oil based contrast Excised and immersed in oil based contrast
mediummedium
Custom built Micro CT scanner (Dental Custom built Micro CT scanner (Dental
Biophysics QMUL)Biophysics QMUL)
Voxel size (30 x 30 x 30µm)Voxel size (30 x 30 x 30µm)
Images processed on custom software developed Images processed on custom software developed
under KS400 image analysis systemunder KS400 image analysis system
A trip through a stented A trip through a stented arteryartery
QuickTime™ and a decompressor
are needed to see this picture.
One of about 1200 slices cut One of about 1200 slices cut perpendicular to the long axis perpendicular to the long axis
of the vesselof the vessel
Image processingImage processing
Original slice Thresholded Media/Adventita only
Stent struts Circle fitted
Slice measurements (CE Slice measurements (CE Stent)Stent)
4
6
8
10
12
14
16
18
0 10 20 30 40
Lumen and stent area [mm2]
Distance [mm]
Lumen circularity
Distance [mm]
LumenStent
0.80
0.85
0.90
0.95
1.00
0 10 20 30 40
3D reconstruction3D reconstruction
And renderingAnd rendering
ConclusionsConclusions Histomorphometry is useful for counting and Histomorphometry is useful for counting and
measuring clearly defined structuresmeasuring clearly defined structures
Limited by a lack of “intelligent” softwareLimited by a lack of “intelligent” software Extremely difficult to better the human eye-brain Extremely difficult to better the human eye-brain
combination for pattern recognition/diagnosiscombination for pattern recognition/diagnosis
For histopathologists, may be valuable for For histopathologists, may be valuable for quantifying prognosisquantifying prognosis Measuring ratio or distribution of different tumour Measuring ratio or distribution of different tumour
markersmarkers
No immediate cause for alarm amongst No immediate cause for alarm amongst histopathologists…but watch this space.histopathologists…but watch this space.
