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Morphometry BIRN - Overview - Scientific Achievements. Morphometry BIRN: Overview. Scientific Goal Methods Support multi-site structural MRI clinical studies or trials Multi-site MRI calibration, acquisition and analysis Integrate advanced image analysis and visualization tools Sites (9) - PowerPoint PPT Presentation
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All Hands Meeting 2005
Morphometry BIRN- Overview- Scientific Achievements
• Scientific Goal
• Methods• Support multi-site structural MRI clinical studies or trials• Multi-site MRI calibration, acquisition and analysis• Integrate advanced image analysis and visualization tools
• Sites (9) MGH, BWH, Duke, UCLA, UCSD, UCI, JHU, Wash U, MIT
Morphometry BIRN: Overview
human neuroanatomical data clinical datacorrelates
Diseases: Unipolar Depression, Alzheimer’s, Mild Cognitive Impairment
Multi-site MRI
Calibration
Integrate Analysis &
Visualization Tools
Data Management
Processing Workflows
Morphometry BIRN: Domain Areas
Application Caseshttp://nbirn.net/Publications/Brochures/index.htm
• fBIRN• Mouse BIRN• BIRN CC
HID
XNAT
DB
Workflows (LONI/Kepler)
Morphometry BIRN: manuscripts
• MacFall et al., Lobar distribution of lesion volumes in late-life depression (Neuropsychopharmacology, submitted)
• Fennema-Notestine et al., Quantitative evaluation of automatic skull stripping methods (Human Brain Mapping, 2005)
• Neu et al., The LONI debabeler: a mediator for neuroimaging software (NeuroImage, 2005)
• Chen et al., Fast correction for direction-dependent distortions in DTI (NeuroImage, in press)
• Jovicich et al., Reliability in multi-site structural MRI studies: unwarping effects (NeuroImage, in press)
• Bischoff-Grethe, A Technique for the Deidentification of Structural Brain MRI (NeuroImage, submitted)
• Farrell et al., Signal to noise ratio effects on fractional anisotropy reproducibility from DTI (to be submitted 2005)
Mouse – Morphometry BIRN paper
Technical development papers:
• Ali et al., Automated segmentation of neuroanatomical structures in multispectral mouse MRI (NeuroImage, 2005)
Clinical application papers:
• Han et al., Reliability of MRI-derived measurements of cerebral cortical thickness (NeuroImage, submitted)
• Fennema-Notestine et al., Multi-site clilnical structural neuroimaging data of legacy data (to be submitted 2005)
• Beg et al, Pattern classification of hippocampal shape analysis in a study of AD (to be submitted 2006)
• Marcus et al., The OASIS Project: a publicly available human brain imaging data resource (submitted)
Morphometry BIRN: manuscripts
• MacFall et al., Lobar distribution of lesion volumes in late-life depression (Neuropsychopharmacology, submitted)
• Fennema-Notestine et al., Quantitative evaluation of automatic skull stripping methods (Human Brain Mapping, 2005)
• Neu et al., The LONI debabeler: a mediator for neuroimaging software (NeuroImage, 2005)
• Chen et al., Fast correction for direction-dependent distortions in DTI (NeuroImage, in press)
• Jovicich et al., Reliability in multi-site structural MRI studies: unwarping effects (NeuroImage, in press)
• Bischoff-Grethe, A Technique for the Deidentification of Structural Brain MRI (NeuroImage, submitted)
• Farrell et al., Signal to noise ratio effects on fractional anisotropy reproducibility from DTI (to be submitted 2005)
Mouse – Morphometry BIRN paper
Technical development papers:
• Ali et al., Automated segmentation of neuroanatomical structures in multispectral mouse MRI (NeuroImage, 2005)
Clinical application papers:
• Han et al., Reliability of MRI-derived measurements of cerebral cortical thickness (NeuroImage, submitted)
• Fennema-Notestine et al., Multi-site clilnical structural neuroimaging data of legacy data (to be submitted 2005)
• Beg et al, Pattern classification of hippocampal shape analysis in a study of AD (to be submitted 2006)
• Marcus et al., The OASIS Project: a publicly available human brain imaging data resource (submitted)
Morphometry BIRN Calibration: Cortical thickness reproducibility across MRI system upgrade
Global Thickness variability: Group results (5 subjects)
Sonata-Sonata
Sonata-Avanto
Avanto-Avanto
Thickness variability maps: Group results (lh)
~ 6%
~ 3.5%
Morphometry BIRN: manuscripts
• MacFall et al., Lobar distribution of lesion volumes in late-life depression (Neuropsychopharmacology, submitted)
• Fennema-Notestine et al., Quantitative evaluation of automatic skull stripping methods (Human Brain Mapping, 2005)
• Neu et al., The LONI debabeler: a mediator for neuroimaging software (NeuroImage, 2005)
• Chen et al., Fast correction for direction-dependent distortions in DTI (NeuroImage, in press)
• Jovicich et al., Reliability in multi-site structural MRI studies: unwarping effects (NeuroImage, in press)
• Bischoff-Grethe, A Technique for the Deidentification of Structural Brain MRI (NeuroImage, submitted)
• Farrell et al., Signal to noise ratio effects on fractional anisotropy reproducibility from DTI (to be submitted 2005)
Mouse – Morphometry BIRN paper
Technical development papers:
• Ali et al., Automated segmentation of neuroanatomical structures in multispectral mouse MRI (NeuroImage, 2005)
Clinical application papers:
• Han et al., Reliability of MRI-derived measurements of cerebral cortical thickness (NeuroImage, submitted)
• Fennema-Notestine et al., Multi-site clilnical structural neuroimaging data of legacy data (to be submitted 2005)
• Beg et al, Pattern classification of hippocampal shape analysis in a study of AD (to be submitted 2006)
• Marcus et al., The OASIS Project: a publicly available human brain imaging data resource (submitted)
MGH Segmentation
De-identificationAnd upload
JHUShape Analysis
of Segmented Structures
BIRNVirtual
Data Grid
BWHVisualization
Scientific Goal: correctly classify patient status from
morphometric results
1
2
3
4
5
Teragrid
N=45
Data DonorSite (WashU)
Technical Goal: seamlessintegration of tools and
data flow during processing
Morphometry BIRN: Shape Analysis Pipeline Overview
21 control subjects18 Alzheimer subjects 6 semantic dementia subjects
Shape-derived metrics can be used to detect class-specific information
Morphometry BIRN: Shape Analysis Pipeline Results
Morphometry BIRN: manuscripts
• MacFall et al., Lobar distribution of lesion volumes in late-life depression (Neuropsychopharmacology, submitted)
• Fennema-Notestine et al., Quantitative evaluation of automatic skull stripping methods (Human Brain Mapping, 2005)
• Neu et al., The LONI debabeler: a mediator for neuroimaging software (NeuroImage, 2005)
• Chen et al., Fast correction for direction-dependent distortions in DTI (NeuroImage, in press)
• Jovicich et al., Reliability in multi-site structural MRI studies: unwarping effects (NeuroImage, in press)
• Bischoff-Grethe, A Technique for the Deidentification of Structural Brain MRI (NeuroImage, submitted)
• Farrell et al., Signal to noise ratio effects on fractional anisotropy reproducibility from DTI (to be submitted 2005)
Mouse – Morphometry BIRN paper
Technical development papers:
• Ali et al., Automated segmentation of neuroanatomical structures in multispectral mouse MRI (NeuroImage, 2005)
Clinical application papers:
• Han et al., Reliability of MRI-derived measurements of cerebral cortical thickness (NeuroImage, submitted)
• Fennema-Notestine et al., Multi-site clilnical structural neuroimaging data of legacy data (to be submitted 2005)
• Beg et al, Pattern classification of hippocampal shape analysis in a study of AD (to be submitted 2006)
• Marcus et al., The OASIS Project: a publicly available human brain imaging data resource (submitted)
BIRNVirtual Data
Grid
1
MGH Freesurfer
segmentations
2
BIRN CC PortalMulti-site data queries
and statisticsAccess to visualization and interpretation tools
0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0CVLT Discriminability Score
1000
2000
3000
4000
5000
6000
Le
ft H
ipp
oca
mp
al V
olu
me
BWH/MGH and UCSD Data
WebWeb
AD Project Data Flow
1) Retrospective data upload from UCSD and MGH sites
2) Semi-automated subcortical segmentation (MGH)
3) From any participating site: query, statistical analysiand
visualization of the data through the BIRN Portal
3
UCSDHuman Imaging
DB
Data Upload
MGHHuman Imaging
DB
3 3
UCSDN=125
BWH/MGHN=118
MGHArchives
UCSDArchives
Morphometry BIRN: Multi-site Alzheimer’s Disease Overview
UCSDMGH/BWH
WashU
Site
60 70 80 90
AGE
2000
3000
4000
5000
Lef
t-H
ipp
oca
mp
us
Hippocampal Volume Loss in Normal Aging
Morphometry BIRN: Multi-site Alzheimer’s Disease Results
Diagnostic classification
of multi-site healthy vs AD
• Linear and quadratic discriminant analysis applied
• Classification success rate on test data 90%.
Hippocampal volume loss in
normal aging from
multi-site healthy data
• Multi-site legacy data, if properly matched and calibrated, can be combined
Morphometry BIRN: manuscripts
• MacFall et al., Lobar distribution of lesion volumes in late-life depression (Neuropsychopharmacology, submitted)
• Fennema-Notestine et al., Quantitative evaluation of automatic skull stripping methods (Human Brain Mapping, 2005)
• Neu et al., The LONI debabeler: a mediator for neuroimaging software (NeuroImage, 2005)
• Chen et al., Fast correction for direction-dependent distortions in DTI (NeuroImage, in press)
• Jovicich et al., Reliability in multi-site structural MRI studies: unwarping effects (NeuroImage, in press)
• Bischoff-Grethe, A Technique for the Deidentification of Structural Brain MRI (NeuroImage, submitted)
• Farrell et al., Signal to noise ratio effects on fractional anisotropy reproducibility from DTI (to be submitted 2005)
Mouse – Morphometry BIRN paper
Technical development papers:
• Ali et al., Automated segmentation of neuroanatomical structures in multispectral mouse MRI (NeuroImage, 2005)
Clinical application papers:
• Han et al., Reliability of MRI-derived measurements of cerebral cortical thickness (NeuroImage, submitted)
• Fennema-Notestine et al., Multi-site clilnical structural neuroimaging data of legacy data (to be submitted 2005)
• Beg et al, Pattern classification of hippocampal shape analysis in a study of AD (to be submitted 2006)
• Marcus et al., The OASIS Project: a publicly available human brain imaging data resource (submitted)