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Morphometry BIRN - Overview - Scientific Achievements

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)

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Morphometry BIRN - Overview - Scientific Achievements

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  1. Morphometry BIRN- Overview- Scientific Achievements

  2. 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) MGH, BWH, Duke, UCLA, UCSD, UCI, JHU, Wash U, MIT correlates human neuroanatomical data  clinical data Diseases:Unipolar Depression, Alzheimer’s, Mild Cognitive Impairment

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

  4. Morphometry BIRN:manuscripts Mouse – Morphometry BIRN paper • Ali et al., Automated segmentation of neuroanatomical structures in multispectral mouse MRI(NeuroImage, 2005) Technical development papers: • 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) • Han et al., Reliability of MRI-derived measurements of cerebral cortical thickness(NeuroImage, submitted) Clinical application papers: • Fennema-Notestine et al., Multi-site clilnical structural neuroimaging data of legacy data(to be submitted 2005) • MacFall et al., Lobar distribution of lesion volumes in late-life depression(Neuropsychopharmacology, submitted) • 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 Mouse – Morphometry BIRN paper • Ali et al., Automated segmentation of neuroanatomical structures in multispectral mouse MRI(NeuroImage, 2005) Technical development papers: • 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) • Han et al., Reliability of MRI-derived measurements of cerebral cortical thickness(NeuroImage, submitted) Clinical application papers: • Fennema-Notestine et al., Multi-site clilnical structural neuroimaging data of legacy data(to be submitted 2005) • MacFall et al., Lobar distribution of lesion volumes in late-life depression(Neuropsychopharmacology, submitted) • 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 Thickness variability maps: Group results (lh) Global Thickness variability: Group results (5 subjects) Sonata-Sonata ~ 6% Sonata-Avanto ~ 3.5% Avanto-Avanto

  7. Morphometry BIRN:manuscripts Mouse – Morphometry BIRN paper • Ali et al., Automated segmentation of neuroanatomical structures in multispectral mouse MRI(NeuroImage, 2005) Technical development papers: • 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) • Han et al., Reliability of MRI-derived measurements of cerebral cortical thickness(NeuroImage, submitted) Clinical application papers: • Fennema-Notestine et al., Multi-site clilnical structural neuroimaging data of legacy data(to be submitted 2005) • MacFall et al., Lobar distribution of lesion volumes in late-life depression(Neuropsychopharmacology, submitted) • 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. Morphometry BIRN: Shape Analysis Pipeline Overview 4 JHU Shape Analysis of Segmented Structures 3 MGH Segmentation 5 BWH Visualization Teragrid Technical Goal: seamless integration of tools and data flow during processing 1 BIRN Virtual Data Grid Data Donor Site (WashU) Scientific Goal: correctly classify patient status from morphometric results N=45 De-identification And upload 2

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

  10. Morphometry BIRN:manuscripts Mouse – Morphometry BIRN paper • Ali et al., Automated segmentation of neuroanatomical structures in multispectral mouse MRI(NeuroImage, 2005) Technical development papers: • 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) • Han et al., Reliability of MRI-derived measurements of cerebral cortical thickness(NeuroImage, submitted) Clinical application papers: • Fennema-Notestine et al., Multi-site clilnical structural neuroimaging data of legacy data(to be submitted 2005) • MacFall et al., Lobar distribution of lesion volumes in late-life depression(Neuropsychopharmacology, submitted) • 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. Morphometry BIRN: Multi-site Alzheimer’s Disease Overview Web BIRN CC Portal Multi-site data queries and statistics Access to visualization and interpretation tools MGH Freesurfer segmentations 2 3 BIRN Virtual Data Grid MGH Human Imaging DB UCSD Human Imaging DB 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 3 1 MGH Archives UCSD Archives Data Upload BWH/MGH N=118 UCSD N=125

  12. Hippocampal Volume Loss in Normal Aging 5000 A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A 4000 A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A Left-Hippocampus A A A A A A A A A A A A A A A A A A A A 3000 A A A A A A A A A A Site A A A 2000 UCSD MGH/BWH 60 70 80 90 WashU AGE Morphometry BIRN: Multi-site Alzheimer’s Disease Results Hippocampal volume loss in normal aging from multi-site healthy data Diagnostic classification of multi-site healthy vs AD • Multi-site legacy data, if properly matched • and calibrated, can be combined • Linear and quadratic discriminant analysis applied • Classification success rate on test data 90%.

  13. Morphometry BIRN:manuscripts Mouse – Morphometry BIRN paper • Ali et al., Automated segmentation of neuroanatomical structures in multispectral mouse MRI(NeuroImage, 2005) Technical development papers: • 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) • Han et al., Reliability of MRI-derived measurements of cerebral cortical thickness(NeuroImage, submitted) Clinical application papers: • Fennema-Notestine et al., Multi-site clilnical structural neuroimaging data of legacy data(to be submitted 2005) • MacFall et al., Lobar distribution of lesion volumes in late-life depression(Neuropsychopharmacology, submitted) • 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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