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NA-MICNational Alliance for Medical Image Computing
Analysis and Results of Brockton VA study:Controls vs Schizophrenics Personality Disorder
Martin Styner, Ipek Oguz, UNC
Jim Levitt, Martha Shenton, B&W, Brockton VA/Harvard`
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TOC
• NAMIC Data: SPD study
• Caudate shape analysis– Steps of Shape Pipeline (simplified)– Shape Analysis Results
• Global & Local
– Parcellation
• Corpus Callosum segmentation and subdivision
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Data SPD study
• Data through NAMIC
• Manual segmentations of the caudate (with existing subdivision)
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Shape Analysis Workflow
Caudate (Fusion) Segmentation
Preprocessing &Parameterization
SPHARM-PDM Shape
QCShape &Corresp.
Alignment& Scale
Feature Computatione.g. Subdivision or
Mean Shape Difference
QC of Features & Statistical Results
Statistical AnalysisOf Features
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Pre-processing
• Sample case• Segmentation after
pre-processing• Hole filling• 6 connect• Mean-curvature
smoothing• 0.5mm^3
resolution
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SPHARM Shape
• Spherical parameterization• Mirroring of right caudate• Alignment to first order ellipsoid• Alignment to template
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SPHARM Shape
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• Overlay of voxel segmentation (red) with SPHARM (blue)
• Average Error ~ 0.11mm
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SPHARM correspondence
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SPHARM Mean Caudate
Left Mean Right Mean
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• Cnt: Transparent blue, PSD: solid red, ICV scale• Difference between means
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Statistical Testing
• Global Shape Difference– No Scale: Left: p = 0.13, Right: p = 0.016– ICV Scale: Left: p = 0.46, Right: p = 0.062
• Local Significance (NoScale), Mean Diff, T2
lat medR RL L
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Caudate Subdivision
• Skeleton based Subdivision (11 parts)
• Fusion into 4 parts (ant/post head, body, tail)
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Caudate Subdivision
• Subdivision Automatic QC images
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Caudate Subdivision
L 0.08 0.13 0.12 0.07 0.04 0.06 0.05 0.01 0.10
R 0.14 0.18 0.03 0.20 0.06 0.01 0.02 0.06 0.01
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L 0.03 0.05 0.05 0.01
R 0.04 0.08 0.01 0.03
ICV ScaleOrig Scale same pattern all significant
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Caudate subdivision
• Good agreement with local shape analysis
L 0.03 0.05 0.05 0.01
R 0.04 0.08 0.01 0.03
lateral medial
R RL L
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Caudate analysis
• Prior work:– No diff. ant L and R, ICV + original– Diff. posterior region on R but not L
• UNC subdivision– All subparts different in original scale– Ant L and R different in ICV scale– Diff posterior region on L and R
• Explanation: – Variability cuts/intraventricular
foramen– Region of cut shows difference in R
in UNC subdivision– Small number of subjects
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Conclusion Caudate Study
• Shape shows local and global differences on R, but only local on L
• Subdivisions and local shape agree quite well
• Both local shape analysis and subdivision suggest main effect in caudate head and some effect in parts of the tail
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Corpus Callosum
• Methods & reliability• Results• How about other Brockton VA datasets?
• General Witelson Scheme
• Mostly manual• Can be automized
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CC segmentation
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• Automatic model based seg.
• Start from average
• Failure rate < 1% / 3%
• In case of failure, manual correction of parameters
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Stable also with Anomalies
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CC subdivision
• DTI fiber tracking based Corpus Callosum subdivision method– MICCAI 2005
Ant-frontal Post-frontal
Parietal Occ+temp
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Probabilistic Subdivision
• Not hard boundaries
• 5 training datasets: Average model
• Applicable on retrospective data
Average Probabilistic Model
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Example Pediatric Growth
• Regional Corpus Callosum growth in 4 pediatric cases age 2y to age 4y
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CC reliability
• 100% reproducible segmentation, subdivision• 1 subject, 5 sites with 2 scans within 24h• T1, T2, PD: 1.5 mm & 3mm slice• Single rater (where manual)• Interp. to 1mm3, registration to ACPC atlas
– 3 channel T1, T2, PD EMS for WM– T1 EMS for WM– Manual using T1 EMS– Manual model based (no parameter knowledge)– Pure manual (IRIS)
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EMS 3 Segmentation
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CC reliability• Model manual better than EMS1 manual
– Model manual performed after EMS1: bias
• Pure manual worst, only single case(better)• EMS3 shows best performance• Subdivision performs in the range of CC segmentation• Area measurements differ between methods
COV COV COV COV COVtotal ant front post front parietal occ-temp mean stdev
EMS3 2.72 3.10 4.12 2.47 2.53 511 14EMS1 3.61 5.37 5.20 2.49 2.63 534 19M EMS1 5.04 5.10 5.92 4.97 4.97 546 28M model 3.66 4.09 3.94 3.70 4.08 581 15M pure 5.66 - - - - 557 31M single 1.09
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CC Analysis in SPD data
• No p-vals below 0.4• No differences at all! • Is this negative finding expected? What
have others found in this population?• How about the other datasets in NAMIC-
VA:– Chronic schizophrenia (2 sets)– First episodes (2 sets)– We had findings before in other studies (autism,
fragile X)
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ITK InsightSNAP
• A level set semi- automatic segmentation tool
• Visualization tool• Postprocessing tool• 5 year history• Here: use for caudate
segmentation• Webpage with tools• Brief Demo of SNAP
– Bools & 3D cuts
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Caudate Segmentation
• Pediatric (2y & 4y) autism, fragile X, developmentally delayed and controls
• Show document and figures • Protocol online available:• http://www.psychiatry.unc.edu/autismresearch/mri/
roiprotocols.htm
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Other SNAP Projects
• Segmentation of lateral ventricles using probability maps from tissue segmentation– ICC > 0.99, time ~ 10 min per case
• Segmentation of mandible/maxilla for pre/post surgical evaluation from CB-CT
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The end (for now…)