Normative Modelling of Brain Volume for Diagnostic and Prognostic Stratification in Multiple Sclerosis
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Background
Brain atrophy is a hallmark of multiple sclerosis (MS). For clinical translatability and individual-level predictions, brain atrophy needs to be put into context of the broader population, using reference or normative models.
Methods
Reference models of MRI-derived brain volumes were established from a large healthy control (HC) multi-cohort dataset (N=63 115, 51% females). The reference models were applied to two independent MS cohorts (N=362, T 1 w-scans=953, follow-up time up to 12 years) to assess deviations from the reference, defined as Z-values. We assessed the overlap of deviation profiles and their stability over time using individual-level transitions towards or out of significant reference deviation states (|Z|>1·96). A negative binomial model was used for case-control comparisons of the number of extreme deviations. Linear models were used to assess differences in Z-score deviations between MS and propensity-matched HCs, and associations with clinical scores at baseline and over time. The utilized normative BrainReference models, scripts and usage instructions are freely available.
Findings
We identified a temporally stable, brain morphometric phenotype of MS. The right and left thalami most consistently showed significantly lower-than-reference volumes in MS (25% and 26% overlap across the sample). The number of such extreme smaller-than-reference values was 2·70 in MS compared to HC (4·51 versus 1·67). Additional deviations indicated stronger disability (Expanded Disability Status Scale: β=0·22, 95% CI 0·12 to 0·32), Paced Auditory Serial Addition Test score (β=-0·27, 95% CI −0·52 to −0·02), and Fatigue Severity Score (β=0·29, 95% CI 0·05 to 0·53) at baseline, and over time with EDSS (β=0·07, 95% CI 0·02 to 0·13). We additionally provide detailed maps of reference-deviations and their associations with clinical assessments.
Interpretation
We present a heterogenous brain phenotype of MS which is associated with clinical manifestations, and particularly implicating the thalamus. The findings offer potential to aid diagnosis and prognosis of MS.
Funding
Norwegian MS-union, Research Council of Norway (#223273; #324252); the South-Eastern Norway Regional Health Authority (#2022080); and the European Union’s Horizon2020 Research and Innovation Programme (#847776, #802998).
Research in context
Evidence before this study
Reference values and normative models have yet to be widely applied to neuroimaging assessments of neurological disorders such as multiple sclerosis (MS). We conducted a literature search in PubMed and Embase (Jan 1, 2000–September 12, 2025) using the terms “MRI” AND “multiple sclerosis”, with and without the keywords “normative model*” and “atrophy”, without language restrictions. While normative models have been applied in psychiatric and developmental disorders, few studies have addressed their use in neurological conditions. Additionally, it remains unclear whether there is a brain phenotype unique to MS, which might help diagnosis and patient stratification.
Added value of this study
We provide regionally detailed brain morphometry maps derived from a heterogeneous MS cohort spanning wide ranges of age, sex, clinical phenotype, disease duration, disability, and scanner characteristics. By leveraging normative modelling, our approach enables individualised brain phenotyping of MS in relation to a population based normative sample.
The analyses reveal heterogeneity in affected brain regions across the cohort, and yet consistent patterns of smaller brain volumes, particularly in the thalamus and frontal cortical regions, which are linked to disability, cognitive impairment, and fatigue. Robustness across scanners, centres, and longitudinal follow-up supports the stability and generalisability of these findings to real-world MS populations.
Implications of all the available evidence
Normative modelling offers an individualised, sensitive, and interpretable approach to quantifying brain structure in MS by providing individual-specific reference values, supporting earlier detection of neurodegeneration than possible with standard radiological assessments and improved patient stratification. A consistent pattern of thalamic and fronto-parietal deviations defines a distinct morphometric profile of MS, with potential utility for early and personalised diagnosis and disease monitoring in clinical practice and clinical trials.
