Collaborative Computational Anatomy: An MRI Morphometry Study of the Human Brain via Diffeomorphic Metric Mapping

摘要

This paper describes a large multi-institutional analysis of the shape and structure of the human hippocampus in the aging brain as measured via MRI. The study was conducted on a population of 101 controls >(n=57) with Clinical Dementia Rating (CDR) score 0 and subjects clinically diagnosed with Alzheimer’s Disease (AD, >28 with CDR 0.5 and 10 with CDR 1) >or semantic dementia (SD, >4 with CDR 0.5 and 2 with CDR 0) with imaging data collected at Washington University in St. Louis, hippocampal structure annotated at the Massachusetts General Hospital, and anatomical shapes embedded into a metric shape space using large deformation diffeomorphic mapping (LDDMM) at the Johns Hopkins University. A global classifier was constructed for discriminating cohorts of nondemented (>CDR 0) and demented (>CDR 0.5 or 1) subjects based on linear discriminant analysis of dimensions derived from metric distances between anatomical shapes demonstrating class conditional structure measured via LDDMM metric shape (p < .01). Localized analysis of >the control and AD subjects only on the coordinates of the population template demonstrates shape changes in the subiculum and the CA1 subfield in AD (p < .05). Such large scale collaborative analysis of anatomical shapes has the potential to enhance the understanding of neurodevelopmental and neuropsychiatric disorders.