Journal
ACADEMIC RADIOLOGY
Volume 15, Issue 11, Pages 1360-1375Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.acra.2008.07.007
Keywords
Diffeomorphism; unbiased; traumatic brain injury; diffusion; morphometry
Funding
- NCI NIH HHS [T32 CA74781, T32 CA074781] Funding Source: Medline
- NICHD NIH HHS [R24 HD39621, R24 HD039621] Funding Source: Medline
- NIDA NIH HHS [L40 DA025520] Funding Source: Medline
- NINDS NIH HHS [P30 NS045839] Funding Source: Medline
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Rationale and Objectives. Diffusion tensor (DT) and T1 structural magnetic resonance images provide unique and complementary tools for quantifying the living brain. We leverage both modalities in a diffeomorphic normalization method that unifies analysis of clinical datasets in a consistent and inherently multivariate (MV) statistical framework. We use this technique to study MV effects of traumatic brain injury (TBI). Materials and Methods. We contrast T1 and DT image-based measurements in the thalamus and hippocampus of 12 TBI survivors and nine matched controls normalized to a combined DT and T1 template space. The normalization method uses maps that are topology-preserving and unbiased. Normalization is based on the full tensor of information at each voxel and simultaneously, the similarity between high-resolution features derived from T1 data. The technique is termed symmetric normalization for MV neuroanatomy (SyNMN). Voxel-wise MV statistics on the local volume and mean diffusion are assessed with Hotelling's T-2 test with correction for multiple comparisons. Results. TBI significantly (false discovery rate P < .05) reduces volume and increases mean diffusion at coincident locations in the mediodorsal thalamus and anterior hippocampus. Conclusions: SyNMN reveals evidence that TBI compromises the limbic system. This TBI morphometry study and an additional performance evaluation contrasting SyNMN with other methods suggest that the DT component may aid normalization quality.
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