Exploring multi-modal registration for improved longitudinal modeling of patient-specific 4D DTI data

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  Projects List

Key Investigators

• Utah: Anuja Sharma, Bo Wang, Guido Gerig
• UCLA: Andrei Irimia, Micah Chambers, Jack Van Horn

Objective

• Assess possible white matter atrophy in TBI patients by utilizing multi-modal longitudinal information and quantify changes in white matter properties of tracts along time.
• Perform multi-modal image registration and utilize the lesion segmentation framework previously developed by Wang et al. for identifying tracts of interest.
• Collaborate closely with the UCLA team on this project.

Approach, Plan

• Co-register patient-specific structural and DTI data, together with lesion segmentations. Registration is performed using Slicer in a longitudinal fashion to establish correspondence between the acute and chronic scans from a patient across multiple modalities.
• Utilize information from the lesion segmentations to guide the tractography.
• Assess white matter changes longitudinally in tracts close to the lesions sites.

Progress

References

• Bo Wang, Marcel Prastawa, Andrei Irimia, Micah C. Chambers, Neda Sadeghi, Paul M. Vespa, John D. Van Horn, Guido Gerig, Analyzing Imaging Biomarkers for Traumatic Brain Injury Using 4D Modeling of Longitudinal MRI, In IEEE ISBI 2013 .
• A. Sharma, P.T. Fletcher, J.H. Gilmore, M.L. Escolar, A. Gupta, M. Styner, G. Gerig. “Spatiotemporal Modeling of Discrete-Time Distribution-Valued Data Applied to DTI Tract Evolution in Infant Neurodevelopment,” In IEEE Proceedings of ISBI 2013.