The use of routinely collected structural neuroimaging to identify cognitive impairment in multiple sclerosis.

Overview

1. Melbourne School of Psychological Sciences, The University of Melbourne,Redmond Barry Building, Parkville, VIC 3010 Australia
2. Neuroimmunology Centre, Department of Neurology, The Royal Melbourne Hospital,635 Elizabeth Street, Melbourne, VIC 3000 Australia
3. Clinical Outcomes Research (CORe) Unit, Department of Medicine (RMH), The University of Melbourne,635 Elizabeth Street, Melbourne, VIC 3000 Australia
4. Centre of Excellence for Cellular Immunotherapy and Clinical Haematology, Peter MacCallum Cancer Centre and Royal Melbourne Hospital,305 Grattan Street, Melbourne, VIC 3000 Australia
5. School of Psychology, Deakin University,Victoria, Australia

Abstract

Background: Cognitive impairment is common in multiple sclerosis (MS), yet comprehensive cognitive assessment is not universally accessible, and patients need to be triaged for referral. Given the links between brain atrophy and cognition, this study investigated whether routinely collected neuroimaging markers could identify MS patients at risk of cognitive impairment.

Methods: Data were retrospectively analysed from adult MS patients assessed in a specialist cognitive neuroimmunology clinic, who had undergone MRI within 12 months prior to cognitive testing. Normalised brain volume (NBV), normalised grey matter volume (NGMV), normalised white matter volume (NWMV), and corpus callosum index (CCI) were measured using the Siemens MorphoBox automated software. GLMs were estimated to investigate group differences in brain volume metrics between cognitively impaired and non-impaired patients. ROC curves were estimated to investigate screening performance for neuroimaging metrics (Youden’s J). Results are expressed as parameter estimates with 95% bootstrapped confidence intervals (CI).

Results: 120 patients were included (35% cognitively impaired). Cognitively impaired patients had lower NBV (b = − 2.06, 95% CI [− 3.35, − 0.81]) and NWMV (b = − 1.65, 95% CI [− 2.60, − 0.77]). NWMV (area under the curve [AUC] = 0.67, 95% CI [0.57, 0.76]) and CCI (AUC = 0.62, 95% CI [0.51, 0.72]) classified impairment, although sensitivity was low (< 0.70). No clear associations or sufficient classification performance were observed for NGMV. Diagnostic performance improved when neuroimaging markers were statistically combined with relevant demographic information.

Conclusion: The present study did not find strong evidence supporting routinely collected neuroimaging as standalone cognitive screening tools. Classification performance improved when combined with demographic factors, but remained below thresholds for clinical utility. These findings highlight a gap between group-level associations reported in the literature and their translation to individual-level clinical application.

Supplementary Information: The online version contains supplementary material available at 10.1186/s12883-026-05085-z.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Data

Datasets cited

• osf:5bng6, at OSF; found in “Data availability”

Data availability

De-identified data and complete analysis may be accessed from the following online data depository: 10.17605/OSF.IO/5BNG6.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 6 authors, 5 keywords, 13 MeSH terms, 35 references.

Cite

This paper

Jardine, R. E., Kuznetsova, V., D’Aprano, F., Kalinicik, T., Roberts, S., & Malpas, C. B. (2026). The use of routinely collected structural neuroimaging to identify cognitive impairment in multiple sclerosis. BMC neurology, 26(1), 544. https://doi.org/10.1186/s12883-026-05085-z

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