MR image texture analysis applied to the diagnosis and tracking of Alzheimer's disease.

Abstract

We assess the value of magnetic resonance (MR) image texture in Alzheimer's disease (AD) both as a diagnostic marker and as a measure of progression. T1-weighted MR scans were acquired from 40 normal controls and 24 AD patients. These were split into a training set (20 controls, 10 AD) and a test set (20 controls, 14 AD). In addition, five control subjects and five AD patients were scanned repeatedly over several years. On each scan a texture feature vector was evaluated over the brain; this consisted of 260 measures derived from the spatial gray-level dependence method. A stepwise discriminant analysis was applied to the training set, to obtain a linear discriminant function. In the test set, this function yielded significantly different values for the control and AD groups (p < 10(-4)) with only small group overlap; a classification rate of 91% was obtained. For the repeatedly scanned control subjects, the median increment in the discriminant function between successive scans of 0.12 was not significantly different from zero (p > 0.05); for the repeatedly scanned AD patients the corresponding median increment of 1.4 was significantly different from zero (p < 0.05). MR image texture may be a useful aid in the diagnosis and tracking of Alzheimer's disease.