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Anatomical shape differences in cortical structures in the brain can beassociated with various neuropsychiatric and neuro-developmental diseases ordisorders. Labeled Cortical Distance Map (LCDM), can be a powerful tool toquantize such morphometric differences. In this article, we investigate variousissues regarding the analysis of LCDM distances in relation to morphometry. Thelength of the LCDM distance vector provides the number of voxels (approximatelya multiple of volume (in mm^3)); median, mode, range, and variance of LCDMdistances are all suggestive of size, thickness, and shape differences. Howeverthese measures provide a crude summary based on LCDM distances which may conveymuch more information about the tissue in question. To utilize more of thisinformation, we pool (merge) the LCDM distances from subjects in the same groupor condition. The statistical methodology we employ require normality andwithin and between sample independence. We demonstrate that the violation ofthese assumptions have mild influence on the tests. We specify the types ofalternatives the parametric and nonparametric tests are more sensitive for. Wealso show that the pooled LCDM distances provide powerful results for groupdifferences in distribution, left-right morphometric asymmetry of the tissues,and variation of LCDM distances. As an illustrative example, we use gray matter(GM) tissue of ventral medial prefrontal cortices (VMPFCs) from subjects withmajor depressive disorder, subjects at high risk, and control subjects. We findsignificant evidence that VMPFCs of subjects with depressive disorders aredifferent in shape compared to those of normal subjects.

The Use of Labeled Cortical Distance Maps for Quantization and Analysis of Anatomical Morphometry of Brain Tissues