Improved prediction of Alzheimer's disease with longitudinal white matter/gray matter contrast changes

Abstract

Brain morphometry measures derived from magnetic resonance imaging (MRI) are important biomarkers for Alzheimer's disease (AD). The objective of the present study was to test whether we could improve morphometry-based detection and prediction of disease state by use of white matter/gray matter (WM/GM) signal intensity contrast obtained from conventional MRI scans. We hypothesized that including WM/GM contrast change along with measures of atrophy in the entorhinal cortex and the hippocampi would yield better classification of AD patients, and more accurate prediction of early disease progression. T1 -weighted MRI scans from two sessions approximately 2 years apart from 78 participants with AD (Clinical Dementia Rating (CDR) = 0.5-2) and 71 age-matched controls were used to calculate annual change rates. Results showed that WM/GM contrast decay was larger in AD compared with controls in the medial temporal lobes. For the discrimination between AD and controls, entorhinal WM/GM contrast decay contributed significantly when included together with decrease in entorhinal cortical thickness and hippocampal volume, and increased the area under the curve to 0.79 compared with 0.75 when using the two morphometric variables only. Independent effects of WM/GM contrast decay and improved classification were also observed for the CDR-based subgroups, including participants converting from either a non-AD status to very mild AD, or from very mild to mild AD. Thus, WM/GM contrast decay increased diagnostic accuracy beyond what was obtained by well-validated morphometric measures alone. The findings suggest that signal intensity properties constitute a sensitive biomarker for cerebral degeneration in AD.

Keywords: MRI T1-weighted signal intensity; cerebral cortex; cortical thickness; disease prediction; entorhinal; hippocampus; tissue contrast.

Figure 1

Spatial clusters from surface‐based General Linear Models testing degree of annual change in WM/GM contrast and cortical thickness (A), and the effects of group (AD versus controls, B). A: WM/GM contrast (upper row, green) and cortical thickness (bottom row, orange) change for AD and controls, respectively. All clusters indicate a significant annual decay, except the WM/GM cluster in the controls marked with an asterisk, which showed an significant increase. B: WM/GM contrast (upper row, green) and cortical thickness (bottom row, orange). All clusters indicate areas of larger annual decay in AD than controls. Inf, inferior view; Sup, superior view; Con, controls. P < 0.05, corrected for multiple comparisons.

Figure 2

Receiver operating characteristics curves of classification with and without WM/GM contrast change. A: Controls versus AD; B: Controls versus CDR = 0.5 stable; C: Controls versus converted (CDR = 0 ‐‐> 1 and CDR = 0.5 ‐‐> CDR 1). ECT, entorhinal cortical thickness; HV, hippocampal volume; E‐WM/GM, entorhinal WM/GM contrast.

Figure 3

Area under the curve (AUC) estimates at each vertex derived from vertex‐wise logistic regression. Inf, inferior view; Sup, superior view; Thickness, Cortical thickness change; Volume, Hippocampal volume change; Contrast, WM/GM contrast change; LH, left hemisphere; RH = right hemisphere. Please note that the current thresholding was set to highlight differences, thus possibly making relatively small differences seem more pronounced, and that no rigorous statistical testing of differences has been done.