Amnestic MCI future clinical status prediction using baseline MRI features

Abstract

Amnestic mild cognitive impairment (aMCI) individuals are known to be at risk for progression to clinically probable Alzheimer's disease (AD). The objective of this work is to measure the accuracy of an automated classification technique based on clinical-quality, single time-point structural magnetic resonance imaging (MRI) scans for the retrospective prediction of future clinical status in aMCI. Thirty-one aMCI research subjects were followed with annual clinical reassessment after baseline MRI. Twenty subjects progressed to probable AD within an average 2.2 (1.4) years [mean age 76.6 (4.7) years, MMSE 27.1 (2.3)], while 11 remained non-demented on average 5.6 (2.6) years after baseline [mean age 73.3 (7.2) years, MMSE 28.2 (1.8)]. Leave-one-out classification was performed within a multidimensional MRI feature space built from intensity and local volume estimate data of a reference group of 75 probable AD and 75 age-matched control subjects. Prediction using aMCI data reached 81% accuracy, 70% sensitivity and 100% specificity. This automated and objective method has potential in helping predict future clinical status in aMCI.