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Morphometry BIRN: Imaging Calibration Analysis Tools Data Sharing.

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Presentation on theme: "Morphometry BIRN: Imaging Calibration Analysis Tools Data Sharing."— Presentation transcript:

1 Morphometry BIRN: Imaging Calibration Analysis Tools Data Sharing

2 Imaging Calibration Structural Data Calibration Effort 5 subject, 5 site, 2 session data  posted Cortical thickness paper  published Skull stripping paper  published De-identification paper  in press Two reproducibility manuscripts  in preparation

3 Imaging Calibration Diffusion Tensor Imaging Data Calibration Effort Single subject, 3 session, 45 scan  ~ posted 61 normal controls  ~ posted Single-site variability study  completed Multi-site variability study  ready to go “BIRN-approved” protocol  underway

4 DTI Calibration Study: DW Scheme QUESTION:  Which diffusion weighting scheme should you use and why? TAKE HOME POINT:  Use a scheme with many directions ( ~ 30) to get uniform precision and accuracy at all fiber orientations. BUT…Effect size is small (less than intra and inter scan variability) ENDPOINT:Paper submitted October 2006

5 Tools - Image Distortion Correction Gradient unwarping of structural data  workflow DTI eddy-current correction  code posted, sequences available for GE, Siemens Landmark LDDMM software  manuscript in review

6 Tools – Gradient Unwarping Portal Version

7 Tool – Databases Open source release Additional XNAT sites Simplified deployment (BIRN-CC, VMware) Integration with end user tools (ex. Slicer) Additional features (DICOM, web services, pipelines, compatibility with BIRN-CC infrastructure)

8 Duke NIRL Hosted MIRIAD Data http://nirlarc.duhs.duke.edu MIRIAD data in both XNAT and HID

9 Tools - FreeSurfer Subcortical segmentations, Integration with 3D-Slicer Automated filling of ventricles and basal ganglia, Improved skull-stripping and cutting plane definition, New parcellation (Desikan-Killiany), Surface-based General Linear Model analysis

10 Tools - BIRN Query Atlas in Slicer3 Re-Architecture of the QueryAtlas –Advanced Label Features Built-In –Real-Time Interaction with Labels –“Right Click” on Models and Images to Initiate Queries –Based on NA-MIC Software Engineering Methodology –Anatomy-Based Access to Web Resources Integrates with BIRN IT Efforts –Auto Convert and Load BIRN Data Leverages mBIRN Data Formats and Analysis (FreeSurfer) fBIRN is Building Functional QueryAtlas Integrated with mBIRN QueryAtlas

11 Tools - CATNAP GOAL:  To simplify and accelerate DTI & anatomical data processing HOW IT WORKS:  Coregistration with FSL FLIRT  Computes DTI gradient table  Computes diffusion tensor and DTI contrasts DETIALS:  Runs in MATLAB  Philips data only (so far) http://www.nbirn.net/downloads/

12 MBIRN Facilitations: Longitudinal Analysis UCI - a new Siemens 1.5T after a GE 1.5T: Replicate longitudinal analyses from Han, et al. 2006 Han X, Jovicich J, Salat D, van der Kouwe A, Quinn B, Czanner S, Busa E, Pacheco J, Albert M, Killiany R, Maguire P, Rosas D, Makris N, Dale A, Dickerson B, Fischl B. Reliability of MRI-derived measurements of human cerebral cortical thickness: the effects of field strength, scanner upgrade and manufacturer. Neuroimage. 2006 Aug 1;32(1):180-94. Epub 2006 May 2. Freesurfer reconstruction using Han’s longitudinal program Acquire Global mean thickness values and surface thickness measures for variability comparisons ?

13 BIRN-enabled Collaborations - VETSA Vietnam Era Twin Registry (VETSA) –mBIRN Acquisition MRI sequences (MGH/UCSD sites) –mBIRN Image Analysis Workflow QC of raw data FreeSurfer cerebral segmentation & QC FreeSurfer cortical surface reconstruction & parcellation & QC Databasing and statistics with clinical information –Heritability (twin method) statistics Implemented on cortical surface Modeling for ROIs in progress

14 Preliminary Findings of Cortical Heritability (VETSA) Right Hemisphere Left Hemisphere Regions in brighter color suggests a stronger genetic component.

15 The Future… IT SRB enabling of tools –Download pre-existing SRB data into applications –Applications run on the Apps Server with Portal Interface –Construct Federated Data Repository of Large Data Sets


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