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)