Experimental Design and Sample Size Considerations in Longitudinal MRI Based Biomarker Detection for Multiple Sclerosis

Several modeling approaches have been developed to quantify differences in multiple sclerosis (MS) lesion evolution on magnetic resonance imaging (MRI) to identify the effect of treatment on disease progression. These studies have limited clinical applicability due to onerous scan frequency and lengthy study duration. Efficient methods are needed to reduce the required sample size, study duration, and sampling frequency in longitudinal MRI studies. We develop a data-driven approach to identify parameters of study design for evaluation of longitudinal MRI biomarkers of MS lesion evolution. Our design strategies are considerably shorter than those described in previous studies, thus having the potential to lower costs of clinical trials. From a dataset of 36 MS patients with at least 6 monthly MRIs, we extracted new lesions and performed principal component analysis to estimate a biomarker that recapitulated lesion recovery. We tested the effect of MS disease modifying therapy on the lesion evolution index in 3 experimental designs and calculated sample sizes needed to appropriately power studies. Our proposed methods can be used to calculate required sample size and scan frequency in observational studies of MS disease progression as well as in designing clinical trials to find effects of treatment on MS lesion evolution.