Modelling new enhancing MRI lesion counts in multiple sclerosis

Magnetic resonance imaging (MRI) has been established as the most relevant paraclinical toot for diagnosing and monitoring multiple sclerosis (MS). In this context counting the number of new enhancing lesions on monthly MRI s cans is widely used as a surrogate marker of MS activity when evaluating th e effect of treatments. In this study, we investigated whether parametric m odels based on mixed Poisson distributions (the Negative Binomial (NB) and the Poisson-Inverse Gaussian (P-IG) distributions) were able to provide ade quate fitting of new enhancing lesion counts in MS. We found that the NB mo del gave good approximations in relapsing-remitting and secondary progressi ve MS patients not selected for baseline MRI activity, whereas the P-IG dis tribution modelled better new enhancing lesion counts in relapsing-remittin g MS patients selected for baseline activity. This study shows that paramet ric modelling for MS new enhancing lesion counts is feasible. This approach should provide more targeted tools for the design and the analysis of MRI monitored clinical trials in MS.