Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline.
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.
Fan
Yong
Y
Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, School of Medicine, Philadelphia, PA 19104, USA.
Batmanghelich
Nematollah
N
Clark
Chris M
CM
Davatzikos
Christos
C
D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000544:Alzheimer Disease / Q000473:pathology / Q000523:psychology; D001284:Atrophy; D001921:Brain / Q000473:pathology; D003072:Cognition Disorders / Q000473:pathology* / Q000523:psychology*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D020244:Infarction, Middle Cerebral Artery / Q000473:pathology* / Q000523:psychology*; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009483:Neuropsychological Tests; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated / Q000379:methods*; D011379:Prognosis; D012372:ROC Curve