Visualization and quantification of peri-contusional white matter bundles in traumatic brain injury using diffusion tensor imaging

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  Identification of peri-contusional areas in a subject with intra-cranial hemorrhage

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  Semi-automatic tissue classification and model rendering

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  Identification of peri-lesional white matter fiber bundles

Key Investigators

• UCLA: Andrei Irimia, Micah C. Chambers, Ron Kikinis, Paul M. Vespa, Jack Van Horn

Objective

The longitudinal fate of peri-contusional white matter (WM) is of appreciable clinical interest in neurotraumatology due to wide variability of outcome scenarios, ranging from tissue survival to atrophy to permanent tissue loss. The ability to predict WM fate in acute TBI patients would be extremely helpful from a clinical standpoint for the purpose of surgical planning and for the personalized formulation of rehabilitation treatments. This project is concerned with using 3D Slicer to visualize and quantify peri-contusional WM bundles extracted from TBI volumes acquired via DTI.

Approach, Plan

• we intend to perform an exploratory multimodal analysis of structural effects upon WM due to intracranial hemorrhage (ICH) in three selected clinical cases of progressive severity
• tissue classification will be performed following the established methods of Irimia et al., including multimodal segmentation followed by model rendering in 3D Slicer
• peri-lesional fiber bundles and the cortico-spinal tract will be reconstructed using DTI deterministic tractography using 3D Slicer
• tract streamline visualization will be performed to identify tracts within a 4 mm proximity to each lesion
• fiber deformation and bending around lesions will be characterized and quantified

Progress