1. Regionally Specific Atrophy Following Traumatic Brain Injury DG MCLAREN, BB BENDLIN, and SC JOHNSON University of Wisconsin—Madison & GRECC, Madison VA Hospital

2. Background Identifying longitudinal changes are essential in understanding plasticity and predicting future outcomes Surface-based approaches have been used in functional and structural analyses

3. Using the Cortical Surface McLaren et al. 2007, Van Essen et al. 2005 & 2006

4. 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?Can Surface-based approaches be used in longitudinal analyses?

5. 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

6. Processing Steps 2 x Original T1 Align Brains via Skull; Compute Flow SIENA

7. Global Results Using SIENA N=30N=36 P<.0001 Trivedi et al. 2006

8. Processing Steps 2 x Original T1 Align Brains via Skull; Compute Flow Bias Corrected T1 (Brain Only) Normalize & Surface Analysis SIENA

9. Surface Creation and Registration Van Essen 2005

10. 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

11. Within Subject Surface Co-registration T-statistic of time 2 minus time 1 scans Percent Brain Volume Change: -.048 P<.0001 corrected

12. Within Subject Surface Co-registration

13. TBI Patient Cross-section (time 1) 1028 P<.0001 corrected

14. TBI Patient Cross-section (time 2) P<.0001 corrected

15. TBI Patient Longitudinal Percent Brain Volume Change: -.8276 P<.0001 corrected

16. 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

17. Future Directions Improve segmentation to increase accuracy More automated and stable procedure Create study specific averages Compare against SIENAr Other patient populations

18. 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