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Multivariate analysis of thalamo-cortical connectivity loss in TBI

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7 Author(s)
Jeffrey Duda ; Penn Image Computing and Science Laboratory, University of Pennsylvania, USA ; Brian Avants ; Junghoon Kim ; Hui Zhang
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Diffusion tensor (DT) images quantify connectivity patterns in the brain while the T1 modality provides high-resolution images of tissue interfaces. Our objective is to use both modalities to build subject-specific, quantitative models of fiber connections in order to discover effects specific to a neural system. The health of this thalamo-cortical network is compromised by traumatic brain injury, and we hypothesize that these effects are due to a primary injury to the thalamus which results in subsequent compromise of radiating fibers. We first use a population-specific average T1 and DT template to label the thalamus and Brodmann areas (BA) 9,10 and 11 in each subject. We also build an expected connection model within this template space that is transferred to subject space in order to provide a prior restriction on probabilistic tracking performed in subject space. We evaluate the effect of traumatic brain injury on this prefrontal-thalamus network by quantifying, in 10 subjects and 8 controls, the mean diffusion and fractional anisotropy along fiber tracts, along with the mean diffusion within the thalamus and cortical regions. We contrast results gained by a template-based tract definition with those gained by performing analysis in the subject space. Both approaches reveal connectivity effects of TBI, specifically a region of reduced FA in the white matter connecting the thalamus to BA 10.

Published in:

Computer Vision and Pattern Recognition Workshops, 2008. CVPRW '08. IEEE Computer Society Conference on

Date of Conference:

23-28 June 2008