Spatial Patterns of Brain Atrophy in MCI Patients, Identified via High-dimensional Pattern Classification, Predict Subsequent Cognitive Decline
Y. Fan, N. Batmanghelich, C. Clark, C. Davatzikos, Spatial Patterns of Brain Atrophy in MCI Patients, Identified via High-dimensional Pattern Classification, Predict Subsequent Cognitive Decline. NeuroImage, 39(4), pp 1731-43, 2008. PMID: 18053747 PMCID: PMC2861339 DOI: 10.1016/j.neuroimage.2007.10.031
Spatial patterns of brain atrophy in mild cognitive impairment (MCI) and Alzheimer's disease (AD) were measured via methods of computational neuroanatomy. These patterns were spatially complex and involved many brain regions. In addition to the hippocampus and the medial temporal lobe gray matter, a number of other regions displayed significant atrophy, including orbitofrontal and medial-prefrontal grey matter, cingulate (mainly posterior), insula, uncus, and temporal lobe white matter. Approximately 2/3 of the MCI group presented patterns of atrophy that overlapped with AD, whereas the remaining 1/3 overlapped with cognitively normal individuals, thereby indicating that some, but not all, MCI patients have significant and extensive brain atrophy in this cohort of MCI patients. Importantly, the group with AD-like patterns presented much higher rate of MMSE decline in follow-up visits; conversely, pattern classification provided relatively high classification accuracy (87%) of the individuals that presented relatively higher MMSE decline within a year from baseline. High-dimensional pattern classification, a nonlinear multivariate analysis, provided measures of structural abnormality that can potentially be useful for individual patient classification, as well as for predicting progression and examining multivariate relationships in group analyses.