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All Hands Meeting 2005 Morphometry BIRN - Overview - Scientific Achievements.

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Presentation on theme: "All Hands Meeting 2005 Morphometry BIRN - Overview - Scientific Achievements."— Presentation transcript:

1 All Hands Meeting 2005 Morphometry BIRN - Overview - Scientific Achievements

2 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 data correlates Diseases: Unipolar Depression, Alzheimer’s, Mild Cognitive Impairment

3 Multi-site MRI Calibration Integrate Analysis & Visualization Tools Data Management Processing Workflows Morphometry BIRN: Domain Areas Application Cases http://nbirn.net/Publications/Brochures/index.htm fBIRN Mouse BIRN BIRN CC HID XNAT DB Workflows (LONI/Kepler)

4 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)

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)

6 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%

7 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)

8 MGH Segmentation De-identification And upload JHU Shape Analysis of Segmented Structures BIRN Virtual Data Grid BWH Visualization Scientific Goal: correctly classify patient status from morphometric results 1 2 3 4 5 Teragrid N=45 Data Donor Site (WashU) Technical Goal: seamless integration of tools and data flow during processing Morphometry BIRN: Shape Analysis Pipeline Overview

9 21 control subjects 18 Alzheimer subjects 6 semantic dementia subjects Shape-derived metrics can be used to detect class-specific information Morphometry BIRN: Shape Analysis Pipeline Results

10 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)

11 BIRN Virtual Data Grid 1 MGH Freesurfer segmentations 2 BIRN CC Portal Multi-site data queries and statistics Access to visualization and interpretation tools Web 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 UCSD Human Imaging DB Data Upload MGH Human Imaging DB 3 3 UCSD N=125 BWH/MGH N=118 MGH Archives UCSD Archives Morphometry BIRN: Multi-site Alzheimer’s Disease Overview

12 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

13 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)

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