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

Authors

Qi Zhou, Department of Electrical and Computer Engineering, Florida International UniversityFollow
Mohammed Goryawala, Department of Electrical and Computer Engineering, Florida International UniversityFollow
Mercedes Cabrerizo, Department of Electrical and Computer Engineering, Florida International UniversityFollow
Waren Barker, Mount Sinai Medical Center
Ranjan Duara, Mounth Sinai Medical Center
Malek Adjouadi, Department of Electrical and Computer Engineering, Florida International UniversityFollow

Date of this Version

1-6-2014

Document Type

Article

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 theMini-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 ormean 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.

Comments

Originally published in The Scientific World Journal

Creative Commons License

This work is licensed under a Creative Commons Attribution 3.0 License.

Recommended Citation

Qi Zhou, Mohammed Goryawala, Mercedes Cabrerizo, Warren Barker, Ranjan Duara, and Malek Adjouadi, “Significance of Normalization on Anatomical MRI Measures in Predicting Alzheimer’s Disease,” The Scientific World Journal, vol. 2014, Article ID 541802, 11 pages, 2014. doi:10.1155/2014/541802