The Brain-Age Gap in Pediatric Dystonia: Neuroanatomical Deviations Inform Deep Brain Stimulation Outcomes.
Authors
Affiliations (11)
Affiliations (11)
- Neurosciences and Mental Health, SickKids Research Institute, Toronto, Ontario, Canada.
- Division of Neurosurgery, The Hospital for Sick Children, Toronto, Ontario, Canada.
- Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.
- Division of Neurology, The Hospital for Sick Children, Toronto, Ontario, Canada.
- Department of Neurosurgery and Spine Surgery, University Hospital of Essen, Essen, Germany.
- Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg-Essen, Essen, Germany.
- Division of Neurology, Centre Hospitalier Universitaire Sainte-Justine, Montreal, Quebec, Canada.
- Division of Neurosurgery, Centre Hospitalier Universitaire Sainte-Justine, Montreal, Quebec, Canada.
- Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada.
- Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, UHN, Toronto, Ontario, Canada.
- Division of Neurology, University of Toronto, Toronto, Ontario, Canada.
Abstract
Dystonia in children is a heterogeneous condition with variable response to deep brain stimulation (DBS). Brain-age gap, a machine learning-derived metric of structural deviation from norm, may capture signatures that differentiate underlying biotypes and predict outcomes. A brain age model was trained on several thousand normative developmental trajectories (nā=ā2623). Brain-age gap (the difference between predicted and chronological age) was computed from pre-DBS T1-weighted magnetic resonance imaging in 37 children with dystonia and compared to matched healthy controls. Associations with etiology, Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS) and Pediatric Quality-of-Life (PedsQL) scores were examined. Children with dystonia showed a greater brain-age gap (structural deviation) compared to controls (Pā<ā0.001). Greater gap was linked to worse baseline motor scores and poorer 1-year quality-of-life improvement. Patterns differed by etiology, with distinct regional deviations in genetic and acquired dystonia. Brain-age modeling reveals biologically distinct subtypes of pediatric dystonia and may offer a biomarker for stratification and outcome prediction. Ā© 2026 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.