Combining anatomical biomarkers with neuropsychological data for multidimensional classification of Alzheimer’s disease Conference

cited authors

  • Zhou, Q; Goryawala, M; Cabrerizo, M; Wang, J; Barker, W; Duara, R; Adjouadi, M


  • This study combines MRI data with neuropsychological Mini-Mental State Examination (MMSE) as a decisional space for Alzheimer’s disease (AD). A new sorting/ranking method selects variables that make up the dimensions of an optimal decisional space. Specifically, 189 structural MRI scans with 60 AD patients and 129 cognitively normal controls (CN) obtained at Mount Sinai Medical Center were used for empirical evaluation. The results suggest that by using only the two volumetric measures, Right-Hippocampus and left inferior lateral ventricle, along with MMSE scores yielded an average accuracy of 92.3% (sensitivity: 82.8%; specificity: 96.7%). The study is consistent with the widely accepted notion of hippocampal atrophy and ventricular enlargement seen in AD patients. Moreover, the study through its inherent sorting and statistical ranking of the different variables provides a complete mapping of the significant subcortical brain regions which may act as important biomarkers in predicting AD.

publication date

  • January 1, 2013

start page

  • 255

end page

  • 261


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