Multivariate statistical analysis of deformation momenta relating anatomical shape to neuropsychological measures

Authors:
Nikhil Singh;P. Thomas Fletcher;J. Samuel Preston;Linh Ha;Richard King;J. Stephen Marron;Michael Wiener;Sarang Joshi
Affiliations:
University of Utah, Salt Lake City, UT;University of Utah, Salt Lake City, UT;University of Utah, Salt Lake City, UT;University of Utah, Salt Lake City, UT;University of Utah, Salt Lake City, UT;University of North Carolina at Chapel Hill, Chapel Hill, NC;University of California, San Francisco, CA;University of Utah, Salt Lake City, UT
Venue:
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
Year:
2010

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Abstract

The purpose of this study is to characterize the neuroanatomical variations observed in neurological disorders such as dementia. We do a global statistical analysis of brain anatomy and identify the relevant shape deformation patterns that explain corresponding variations in clinical neuropsychological measures. The motivation is to model the inherent relation between anatomical shape and clinical measures and evaluate its statistical significance. We use Partial Least Squares for the multivariate statistical analysis of the deformation momenta under the Large Deformation Diffeomorphic framework. The statistical methodology extracts pertinent directions in the momenta space and the clinical response space in terms of latent variables. We report the results of this analysis on 313 subjects from the Mild Cognitive Impairment group in the Alzheimer's Disease Neuroimaging Initiative (ADNI).