Brain structural magnetic resonance imaging (sMRI) is a tool that uses a magnetic field to produce images of the brain. Patients with multiple sclerosis (MS) have lesions in their brains which are visible on sMRI. MS lesions formation is a complex process involving inflammation, tissue damage, and tissue repair — all of which are visible on sMRI and potentially modifiable by pharmacological therapy. We introduce a PCA regression modeling framework for relating voxel-level (or three-dimensional pixel-level), longitudinal, multi-sequence sMRI intensities within MS lesions to clinical information and therapeutic interventions. To do so, we first characterize the post-lesion incidence repair process on longitudinal, multi-sequence sMRI as voxel-level intensity profiles. We then perform PCA on the intensity profiles to develop a voxel-level biomarker for identifying slow and persistent, long-term inten sity changes within lesion voxels. We then relate the biomarker to the clinical information in a mixed model framework. Treatment with disease-modifying therapies and steroids are both associated with return of a voxel to an intensity value closer to that of normal-appearing tissue.