2004 NIH Building on the BIRN Bruce Rosen, MD PhD Randy Gollub, MD PhD Steve Pieper, PhD Morphometry BIRN.

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Presentation transcript:

2004 NIH Building on the BIRN Bruce Rosen, MD PhD Randy Gollub, MD PhD Steve Pieper, PhD Morphometry BIRN

 What is the Morphometry BIRN? (B. Rosen)  Scientific Background and Significance (R. Gollub)  BIRN Advantages in Morphometry (S. Pieper) The BIRN Advantage OUTLINE: Morphometry BIRN

 Overall Goal: Develop capability to analyze and mine data acquired at multiple sites using processing and visualization tools developed at multiple sites Morphometry BIRN

 Overall Goal: Develop capability to analyze and mine data acquired at multiple sites using processing and visualization tools developed at multiple sites  Context: Human Brain MR Based Morphometry  Initial Application:Alzheimer’s, Depression, Ageing Brain  Participants: BWH, MGH, Duke, UC Los Angeles, UC San Diego, Johns Hopkins, UC Irvine, Washington University Morphometry BIRN

Human Data Protection Multi-site data acquisition Data Upload Integration and Application of Processing Tools Human Imaging Database Morphometry BIRN: Flowchart Simplified diagram of building blocks SRB

Human Data Protection Multi-site data acquisition Data Upload Integration and Application of Processing Tools Human Imaging Database Morphometry BIRN: Flowchart Simplified diagram of building blocks SRB

Raw dataDe-faced data De-facing: automated de-facing without brain removal Pipeline: image formats, BIRN ID generation, defacing, QA, upload Accomplishment: Developed a robust automated methods for bulk MRI de-identification and upload to database (diverse inputs, sharable outputs, common package) De-identification and Upload Pipeline* UCSD (fMRI): A. Bischoff, C.Notestine, B. Ozyurt, S. Morris, G.G. Brown MGH (NMR): B. Fischl BWH (SPL): S. Pieper UCI: D. Wei Duke: B. Boyd *See demo Morphometry BIRN: Reality

Human Data Protection Multi-site data acquisition Data Upload Integration and Application of Processing Tools Human Imaging Database Morphometry BIRN: Flowchart Simplified diagram of building blocks SRB

Multi-site Structural MRI Data Acquisition & Calibration Methods: common acquisition protocol, distortion correction, evaluation by scanning human phantoms multiple times at all sites MGH (NMR): J. Jovicich, A. Dale, D. Greve, E. Haley BWH (SPL): S. Pieper UCI: D. Keator UCSD (fMRI): G. Brown Duke University (NIRL): J. MacFall Corrected Uncorrected Image intensity variability on same subject scanned at 4 sites Morphometry BIRN: Reality Accomplishment: develop acquisition & calibration protocols that improve reproducibility, within- and across-sites

Human Data Protection Multi-site data acquisition Data Upload Integration and Application of Processing Tools Human Imaging Database Morphometry BIRN: Flowchart Simplified diagram of building blocks SRB

Shared Tools for Data Analysis : FreesurferMGH SlicerBWH LONI PipelineUCLA LDDMMJohns Hopkins Morphometry BIRN

Integration and Application of Processing Tools Various projects driving developments: Multi-site Imaging Research in Analysis of Depression*† Data from one site processed with tools of multiple sites Multi-site Morphometry in Analysis of Alzheimer’s Disease *† Data from multiple sites processed with tools of one site Semi-Automated Shape Analysis Project † Data from BIRN sites processed with tools of various sites * Demo at BIRN Toolbox’s session (12:00-3:00pm) † Poster available with more details Morphometry BIRN

Integration and Application of Processing Tools Projects driving developments: Multi-site Imaging Research in Analysis of Depression*† Data from one site processed with tools of multiple sites Multi-site Morphometry in Analysis of Alzheimer’s Disease *† Data from multiple sites processed with tools of one site Semi-Automated Shape Analysis Project † Data from BIRN sites processed with tools of various sites * Demo at BIRN Toolbox’s session (12:00-3:00pm) † Poster available with more details Morphometry BIRN: Reality

MIRIAD Project: Overview Duke Archives UCLA AIR Registration and Lobar Analysis BWH Intensity Normalization and EM Segmentation Duke Clinical Analysis BWH Probabilistic Atlas (one time transfer) UCSD Supercomputing Goal: analyze legacy data using automated lobar segmentation (UCLA) and cortical/subcortical segmentations (BWH)

MIRIAD Project: Accomplishments Segmentation Duke BIRN-MIRIAD Item (semi-automated)(fully-automated) # of tissue classes3 (Fig1)23 (Fig2) Time for 200 brains400 hours1 hour Time for 200 lobe &250 hours all lobes (Fig3) and 27 regional analysis regions included above Improved computational capabilities 1 2 3

Integration and Application of Processing Tools Projects driving developments: Multi-site Imaging Research in Analysis of Depression*† Data from one site processed with tools of multiple sites Multi-site Morphometry in Analysis of Alzheimer’s Disease *† Data from multiple sites processed with tools of one site Semi-Automated Shape Analysis Project † Data from BIRN sites processed with tools of various sites * Demo at BIRN Toolbox’s session (12:00-3:00pm) † Poster available with more details Morphometry BIRN: Reality

AD Project: Overview MGH Segmentation Multi-Site Data Acquisition De-identification and upload SRB UCSD BWH/MGH Multi-site Data Queries and Statistics HID Visualization and Scientific Search with 3DSlicer & Query Atlas

AD Project: Accomplishments Data sharing: Successfully tested Deidentification and Upload Pipeline (DUP) Integration of data Common database schemas for clinical and derived morphometry data at different sites Human Imaging Database (HID) Mediated queries that interrogate databases at two sites Integration of processing tools MGH subcortical segmentation completed on UCSD data Statistical tools through the BIRN Portal and HID Query Interface Data visualization and interpretation using 3DSlicer and Query Atlas

Integration and Application of Processing Tools Projects driving developments: Multi-site Imaging Research in Analysis of Depression*† Data from one site processed with tools of multiple sites Multi-site Morphometry in Analysis of Alzheimer’s Disease *† Data from multiple sites processed with tools of one site Semi-Automated Shape Analysis Project † Data from BIRN sites processed with tools of various sites * Demo at BIRN Toolbox’s session (12:00-3:00pm) † Poster available with more details Morphometry BIRN: Reality

SASHA Project: Overview MGH Segmentation Data Donor Sites De-identification And upload JHU Shape Analysis of Segmented Structures SRB BWH Visualization Goal: comparison and quantification of structures’ shape and volumetric differences across patient populations UCSD Supercomputing

SASHA Project: Accomplishments  Data: 46 hippocampus data sets (2070 comparisons)  Each LDDMM comparison takes about 3 to 8 hours Large Deformation Diffeomorphic Metric Mapping (LDDMM) using the TeraGrid Improved computational capabilities Single PCTeraGrid  1 comparison  ~431 days  60 comparisons simultaneously  ~7 days

Morphometry BIRN: Future  Calibration: Expand imaging modalities,correction methods, refine protocols  Analysis & Visualization: continue integration development, improve automaticity, support new imaging modalities  Computational Informatics: database interoperability, support genomics, support new image data, grid enable  Utilization: propagate widespread utilization of infrastructure, add new sites to testbed

Why are we here today? WE NEED FEEDBACK FROM YOU:  Which developments are useful for your projects?  Which developments are we missing?  How can we build better bridges to your projects?

Challenges  Technical Integration of disparate sources (data and software) Processing and handling of large datasets Federation of databases in compliance with HIPAA Quality control Audit and versioning requirements Accessing legacy data Project coordination and knowledge distillation  Sociological Encouraging collaboration Intellectual Property issues (data & software sharing) Authorship

Metrics for Success  Adopted for use by increasing numbers of experts  Sharing of tools and infrastructure with scientific community  Creation and maintenance of a valuable image archive that supports on-going research  Peer reviewed publications in scientific and technical journals  Presentations at national and international scientific meetings  Professional advancement of key personnel linked to success of project

AD Project: Accomplishments Successfully tested DUP to share data across sites following federal HIPAA guidelines Established common database schemas for clinical and derived morphometry data at different sites (HID) Enabled mediated queries that interrogate databases at two sites Successfully tested integration of tools for common analysis and data mining MGH Subcortical segmentation completed on UCSD data Univariate and bivariate statistical tools through the BIRN Portal and HID Query Interface Data visualization and intelligent scientific search based on anatomical labels using 3DSlicer and Query Atlas

MIRIAD Project: Accomplishments 50 depressed, 50 controls, imaged at baseline and 2 years Parietal lobe smaller in depressed (p < 0.02) In subjects responding to therapy: Temporal lobe smaller (p < 0.08) Frontal lobe was not smaller (p < 0.6)