Abstract Background and aims Digital twins in health (DTHs) are virtual representations of individual patients. They integrate biological data to simulate their personal biology and predict health trajectories. In various fields of medicine, DTHs have been developed for modeling (cardiovascular) anatomy and function, amongst others. The application and level of maturity of DTHs in neurology, and stroke in particular, is unclear. We systematically reviewed the literature to provide an overview of DTHs in neurology and their level of clinical readiness. Methods A PubMed search was performed including papers published up to September 2025 using predefined search terms related to digital twins, computational models, and neurological disorders. Included studies reported DTH-related concepts or models applied to neurological organ systems or diseases; studies without DTH relevance or neurological application were excluded. Methodological quality was assessed using the TRIPOD checklist for prediction models, JBI Critical Appraisal Checklist for narrative reviews, and the STARD checklist for studies evaluating the accuracy of computational models. Results We identified 89 articles, of which nine underwent methodological quality assessment. The included studies described conceptual models or early-stage DTH implementations applied to diagnosis, treatment planning, disease modeling, or disease prediction. Reported applications included device-choice support for the treatment of ischemic stroke, brain tumor diagnosis, and early detection of Alzheimer’s disease. Conclusions Several DTHs have been proposed in neurology and stroke, but none are ready for clinical implementation. Digital twin-related approaches have been proposed for exploratory applications, including device-choice support for treatment of ischemic stroke. Conflict of interest Thom Brouwer: nothing to disclose, Lina Belhadj: nothing to disclose , Charles Majoie: nothing to disclose , Henk Marquering: nothing to disclose
Brouwer et al. (2026) studied this question.