4.7 Article

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

期刊

HUMAN BRAIN MAPPING
卷 30, 期 7, 页码 2132-2141

出版社

WILEY
DOI: 10.1002/hbm.20655

关键词

computational anatomy; shape; diffeomorphism

资金

  1. JHU [P41-RR015241]
  2. MGH [U24 RR021382]
  3. National Center for Research Resources (NIH) [P01-AG0568]
  4. WU [P01AG03991]
  5. NSF [DMS-0456253]
  6. National Center for Research Resources [P41-RR14075R01 RR16594-01A1]
  7. NCRR BIRN Morphometric Project [U24 RR021382, BIRN002]
  8. National Institute for Biomedical Imaging and Bioengineering [R01 EB001550]
  9. National Institute for Neurological Disorders and Stroke [R01 NS052585-01]
  10. Mental Illness and Neuroscience Discovery (MIND) Institute
  11. National Alliance for Medical Image Computing (NAMIC)
  12. National Institutes of Health (NIH Roadmap for Medical Research) [U54 EB005149]

向作者/读者索取更多资源

This article 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 subjects including nondemented control subjects (n = 57) and subjects clinically diagnosed with Alzheimer's Disease (AD, n = 38) or semantic dementia (n = 6) 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 metric mapping (LDDMM) at the Johns Hopkins University. A global classifier was constructed for discriminating cohorts of nondemented and demented subjects based on linear discriminant analysis of dimensions derived from metric distances between anatomical shapes, demonstrating class conditional structure differences measured via LDDMM metric shape (P < 0.01). 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 < 0.05). Such large scale collaborative analysis of anatomical shapes has the potential to enhance the understanding of neurodevelopmental and neuropsychiatric disorders. Hum Brain Mapp 30:2132-2141, 2009. (C) 2008 Wiley-Liss, Inc.

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