Progression of MRI markers in cerebral small vessel disease: Sample size considerations for clinical trials

Abstract

Detecting treatment efficacy using cognitive change in trials of cerebral small vessel disease (SVD) has been challenging, making the use of surrogate markers such as magnetic resonance imaging (MRI) attractive. We determined the sensitivity of MRI to change in SVD and used this information to calculate sample size estimates for a clinical trial. Data from the prospective SCANS (St George’s Cognition and Neuroimaging in Stroke) study of patients with symptomatic lacunar stroke and confluent leukoaraiosis was used (n = 121). Ninety-nine subjects returned at one or more time points. Multimodal MRI and neuropsychologic testing was performed annually over 3 years. We evaluated the change in brain volume, T2 white matter hyperintensity (WMH) volume, lacunes, and white matter damage on diffusion tensor imaging (DTI). Over 3 years, change was detectable in all MRI markers but not in cognitive measures. WMH volume and DTI parameters were most sensitive to change and therefore had the smallest sample size estimates. MRI markers, particularly WMH volume and DTI parameters, are more sensitive to SVD progression over short time periods than cognition. These markers could significantly reduce the size of trials to screen treatments for efficacy in SVD, although further validation from longitudinal and intervention studies is required.

Figure 1.

Plots showing individual trajectories in magnetic resonance imaging (MRI) markers showing a decrease in mean diffusivity (MD) normalized peak height (MD NPH), a decrease in brain volume and an increase in white matter hyperintensity volume (WMH) over the 3-year follow-up period. Time points are shown on the x axis. The average slope is shown in red with credibility intervals. There is only a minimal change in slope when missing data are accounted for in simultaneous models (shown in blue). MAR, missing at random.