Researchers developed normative brain modeling using 62,444 healthy brain scans to create individualized reference standards for detecting atrophy in multiple sclerosis patients. Applied to 953 longitudinal scans from 362 MS patients over 12 years, the model identified critical brain volume deviations 2.7 times more frequently than in controls, with 25% showing thalamic atrophy. Patients with more widespread deviations, particularly in thalamus, hippocampus, and putamen regions, exhibited significantly higher disability scores both cross-sectionally and longitudinally. This normative modeling approach represents a meaningful advance beyond traditional group-level comparisons by enabling precision medicine assessment of individual brain health. The methodology could transform MS monitoring by providing personalized atrophy profiles that predict disability progression, moving away from one-size-fits-all diagnostic approaches. However, this preprint awaits peer review, and the findings require validation in independent patient cohorts before clinical implementation. While the large training dataset and longitudinal design strengthen the results, the practical utility depends on accessibility of advanced MRI processing and whether intervention strategies can effectively target the identified at-risk brain regions.