Download - Ongoing BIRN-GCRC Collaborations

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Page 1: Ongoing BIRN-GCRC Collaborations

Ongoing BIRN-GCRC Collaborations

• Medical College Wisconsin (non BIRN site)– Functional MRI acquisition calibration

• University of Texas (non BIRN site)– Expand taxonomy for neuroimaging database

• BWH, Harvard Medical School– Enhance cardiac MRI analysis & visualization tools

• BWH & MGH, Harvard Medical School– Functional MRI cross-site calibration

Jorge Jovicich, Ph.D.Massachusetts General Hospital - Harvard Medical School

Page 2: Ongoing BIRN-GCRC Collaborations

Functional MRI acquisition calibration

• Sites– GCRC: MCW (P.I. Steven Rao)– BIRN: UCI, Stanford

• Collaboration goal– Apply FBIRN QA methods in a novel environment

• Value to GCRC– Experience using the QA methods to determine that

scanner quality is comparable with other sites

• Value to BIRN– Validate QA methods outside of FBIRN network– Receive feedback improve

GCRC:

• MCW

• UTSA

• BWH

• BWH/MGH

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Quality Assurance: stability of MRI Signal

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fBIRN recommendation

Typical brain

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BIRN Interactions with MCW

• MCW: new 3T GE MRI scanner• Interested in:

– Method for assessing fMRI signal stability– Comparison with fBIRN

• Doped-water phantom shipped for QA• Agar phantom being procured

GCRC:

• MCW

• UTSA

• BWH

• BWH/MGH

Sample Results

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• Sites– GCRC: UTSA (P.I. Peter Fox)– BIRN: UCI

• Background– Brainmap (www.brainmap.org) stores published neuroimaging results – Used for meta-analyses prior to experimental design– BIRN HID stores clinical info, fMRI metadata results, link to images

• Collaboration goal:– Enable [BrainMap + BIRN HID] queries for fMRI experimental results– Need common descriptors (taxonomy) for fMRI experiments

• Value to GCRCs– Improved experimental taxonomies (better BrainMap database)

– Improved experimental designs (meta-analysis [BrainMap + BIRN HID])

• Value to BIRN– Improved experimental taxonomies for a better HID design

– Improved query interface through integration with BrainMap

GCRC:

• MCW

• UTSA

• BWH

• BWH/MGH

Expanding taxonomy for neuroimaging databases

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• Integrating BIRN and BrainMap data descriptions– BIRN describes data from every subject– BrainMap describes only group results– Integration & expansion of Meta-data descriptions

GCRC:

• MCW

• UTSA

• BWH

• BWH/MGH

Expanding taxonomy for neuroimaging databases

Expansions to

include fBIRN

cognitive tasks

Brain Map

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• Sites– GCRC: BWH (P.I. Gail Adler)– BIRN: BWH

• Background– PET standard for cardiac perfusion– Perfusion MRI has potentials– Challenge quantification due to physiological motion. Automate.

• Collaboration goals

Extend and apply function BIRN tools for:

• Image registration algorithms (fully & semi-automated)

• Interactive time-series data management

• Value to GCRCs– Dissemination of improved tools (3D Slicer and Insight Toolkit)

– Training, expertise sharing, requirements definition future projects

• Value to BIRN– Extend and validate tools for non-brain imaging

– Expertise sharing

GCRC:

• MCW

• UTSA

• BWH

• BWH/MGH

Enhance cardiac perfusion MRI analysis & visualization tools

Page 8: Ongoing BIRN-GCRC Collaborations

GCRC:

• MCW

• UTSA

• BWH

• BWH/MGH

Cardiac perfusion MRI

time series

Original sequence

Correctedsequence

Page 9: Ongoing BIRN-GCRC Collaborations

GCRC:

• MCW

• UTSA

• BWH

• BWH/MGH

Need for data management & manual interaction (BIRN)

Interval Browser (3D Slicer) fBIRN visualization. In development

Extensions

Load, inspect , animate DICOM cardiac perfusion MRI datasets, key frame registrations

Future work• Investigate non-rigid registration

• Integrate perfusion processing in registration

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• Sites– GCRC: BWH (P.I. Reisa Sperling)– BIRN: BWH & MGH

• Background– Longitudinal fMRI for clinical trials– Challenge: optimize reproducibility

• Collaboration goalCombine expertise from mBIRN & fBIRN toquantify and improve test-retest reproducibility

• Value to GCRCs– Dissemination acquisition protocols & correction methods– Improved multi-site MRI clinical trials

• Value to BIRN– Test and improve calibration methods

GCRC:

• MCW

• UTSA

• BWH

• BWH/MGH

Functional MRI cross-site calibration

Page 11: Ongoing BIRN-GCRC Collaborations

Evolution of fMRI activation

Early vs. Late MCI

Early MCI (N=12) Late MCI (N=11)

GCRC:

• MCW

• UTSA

• BWH

• BWH/MGH

Value of longitudinal MRI studies

Goal: detect neuroimaging changes before behavioural changes

MCI: Mild Cognitive Impairment

Hippocampus

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Preliminary Test-Retest Assessments

MGH BWH

Retest

Activation in LH hippocampus

MGH – Siemens 3T

Activation in LH hippocampus

BWH – GE 3TTest

GCRC:

• MCW

• UTSA

• BWH

• BWH/MGH

LH: Left Hemisphere

Future work:

• Optimize reproducibility metrics

• Minimize variability in acquisition protocols

• Introduce fBIRN & mBIRN calibration methods

Statistical power estimationfrom measured reproducibility errors

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Acknowledgements

• For all the work: – Our GCRC collaborators and BIRN

• For these slides:– UCI: Jessica Turner– BWH: Wendy Plesniak, Steve Pieper,

Reisa Sperling– MGH: Doug Greve