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The Scientific World Journal
Volume 2014, Article ID 541802, 11 pages
http://dx.doi.org/10.1155/2014/541802
Research Article

Significance of Normalization on Anatomical MRI Measures in Predicting Alzheimer’s Disease

1Department of Electrical Engineering at the Florida International University, Miami, FL 33174, USA
2Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL 33140, USA
3Florida International University, 10555 West Flagler Street, EC 2672, Miami, FL 33174, USA

Received 30 August 2013; Accepted 1 October 2013; Published 6 January 2014

Academic Editors: D. J. Moore and F. Tempia

Copyright © 2014 Qi Zhou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This study establishes a new approach for combining neuroimaging and neuropsychological measures for an optimal decisional space to classify subjects with Alzheimer’s disease (AD). This approach relies on a multivariate feature selection method with different MRI normalization techniques. Subcortical volume, cortical thickness, and surface area measures are obtained using MRIs from 189 participants (129 normal controls and 60 AD patients). Statistically significant variables were selected for each combination model to construct a multidimensional space for classification. Different normalization approaches were explored to gauge the effect on classification performance using a support vector machine classifier. Results indicate that the Mini-mental state examination (MMSE) measure is most discriminative among single-measure models, while subcortical volume combined with MMSE is the most effective multivariate model for AD classification. The study demonstrates that subcortical volumes need not be normalized, whereas cortical thickness should be normalized either by intracranial volume or mean thickness, and surface area is a weak indicator of AD with and without normalization. On the significant brain regions, a nearly perfect symmetry is observed for subcortical volumes and cortical thickness, and a significant reduction in thickness is particularly seen in the temporal lobe, which is associated with brain deficits characterizing AD.