Regionally Specific Atrophy Following Traumatic Brain Injury
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Transcript of Regionally Specific Atrophy Following Traumatic Brain Injury
Regionally Specific Atrophy Regionally Specific Atrophy Following Traumatic Brain InjuryFollowing 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 Can Surface-based approaches be used in longitudinal analyses?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
Processing Steps
2 x Original T1
Align Brains via Skull;Compute Flow
SIENA
Global Results Using SIENA
N=30 N=36
P<.0001
Trivedi et al. 2006
Processing Steps
2 x Original T1
Align Brains via Skull;Compute Flow
Bias Corrected T1(Brain Only)
Normalize & Surface AnalysisSIENA
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
Percent Brain Volume Change: -.048
P<.0001 corrected
Within Subject Surface Co-registration
TBI Patient Cross-section (time 1)
1028
P<.0001 corrected
TBI Patient Cross-section (time 2)
P<.0001 corrected
TBI Patient Longitudinal
Percent Brain Volume Change: -.8276
P<.0001 corrected
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