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Regionally Specific Atrophy Following Traumatic Brain Injury. DG MCLAREN , BB BENDLIN, and SC JOHNSON University of Wisconsin—Madison & GRECC, Madison VA Hospital. Background. Identifying longitudinal changes are essential in understanding plasticity and predicting future outcomes
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Regionally Specific Atrophy Following Traumatic Brain Injury DG MCLAREN, BB BENDLIN, and SC JOHNSON University of Wisconsin—Madison & GRECC, Madison VA Hospital
Background • Identifying longitudinal changes are essential in understanding plasticity and predicting future outcomes • Surface-based approaches have been used in functional and structural analyses
Using the Cortical Surface McLaren et al. 2007, Van Essen et al. 2005 & 2006
Background • Identifying longitudinal changes are essential in understanding plasticity and predicting future outcomes • Surface-based approaches have been used in functional and structural analyses • Can Surface-based approaches be used in longitudinal analyses?
Study Parameters • T1-weighted SPGRs were collected at ~79 days and ~409 days post injury • Standard Axial SPGR sequence with .9375x.9375x1.2mm voxel dimensions
Align Brains via Skull;Compute Flow Processing Steps 2 x Original T1 SIENA
P<.0001 N=30 N=36 Trivedi et al. 2006 Global Results Using SIENA
Bias Corrected T1(Brain Only) Normalize & Surface Analysis Processing Steps 2 x Original T1 Align Brains via Skull;Compute Flow SIENA
Surface Creation and Registration Van Essen 2005
Within Subject Surface Co-registration • Registration to PALS of the same surface produces identical results • Registration of an image to itself doesn’t produce the same results
Within Subject Surface Co-registration • T-statistic of time 2 minus time 1 scans P<.0001 corrected Percent Brain Volume Change: -.048
TBI Patient Cross-section (time 1) P<.0001 corrected 1028
TBI Patient Cross-section (time 2) P<.0001 corrected
TBI Patient Longitudinal P<.0001 corrected Percent Brain Volume Change: -.8276
Conclusions • Surface registration is stable • Normal Controls show little or no changes consistent with SIENA • Method is sensitive to changes over time (and errors in segmentation) • One of the first illustrations of longitudinal changes using the cortical surface
Future Directions • Improve segmentation to increase accuracy • More automated and stable procedure • Create study specific averages • Compare against SIENAr • Other patient populations
Acknowledgements • UW Institute of Aging • Collaborators on the project Trivedi MA, Ward MA, Hess TM, Gale SD, Dempsey RJ, Rowley HA • Funding Support: • NIH: T32 AG20013 • NIH: RO1 MH65723 • NIH: T32 GM007507 • Merit Review Grant from the Department of Veterans Affairs