Predicting white-matter hyperintensity progression and cognitive decline in patients with cerebral small-vessel disease: a magnetic resonance-based habitat analysis.

Background: White-matter hyperintensity (WMH) is the key magnetic resonance imaging (MRI) marker of cerebral small-vessel disease (CSVD). This study aimed to investigate whether habitat analysis based on physiologic MRI parameters can predict the progression of WMH and cognitive decline in CSVD. Methods: Diffusion- and perfusion-weighted imaging data were obtained from 69 patients with CSVD at baseline and at 1-year of follow-up. The white-matter region was classified into constant WMH, growing WMH, shrinking WMH, and normal-appearing white matter (NAWM) according to the T2-fluid-attenuated inversion recovery (FLAIR) sequences images at the baseline and follow-up. We employed k-means clustering on a voxel-wise basis to delineate WMH habitats, integrating multiple diffusion metrics and cerebral blood flow (CBF) values derived from perfusion data. The WMH at the baseline and the predicted WMH from the habitat analysis were used as regions of avoidance (ROAs). The decreased rate of global efficiency for the whole brain structural connectivity was calculated after removal of the ROA. The association between the decreased rate of global efficiency and Montreal Cognitive Assessment (MoCA) and mini-mental state examination (MMSE) scores was evaluated using Pearson correlation coefficients. Results: We found that the physiologic MRI habitats with lower fractional anisotropy and CBF values and higher mean diffusivity, axial diffusivity, and radial diffusivity values overlapped considerably with the new WMH (growing WMH of baseline) after a 1-year follow-up; the accuracy of distinguishing growing WMH from NAWM was 88.9%±12.7% at baseline. Similar results were also found for the prediction of shrinking WMH. Moreover, after the removal of the predicted WMH, a decreased rate of global efficiency had a significantly negative correlation with the MoCA and MMSE scores at follow-up. Conclusions: This study revealed that a habitat analysis combining perfusion with diffusion parameters could predict the progression of WMH and related cognitive decline in patients with CSVD.