Your browser doesn't support javascript.
loading
Prediction of dementia using diffusion tensor MRI measures: the OPTIMAL collaboration.
Egle, Marco; Hilal, Saima; Tuladhar, A M; Pirpamer, Lukas; Hofer, Edith; Duering, Marco; Wason, James; Morris, Robin G; Dichgans, Martin; Schmidt, Reinhold; Tozer, Daniel; Chen, Christopher; de Leeuw, Frank-Erik; Markus, Hugh S.
Afiliación
  • Egle M; Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
  • Hilal S; Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lim School of Medicine, National University of Singapore, Singapore.
  • Tuladhar AM; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System of Singapore, Singapore.
  • Pirpamer L; Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Nijmegen, The Netherlands.
  • Hofer E; Department of Neurology, Medical University Graz, Graz, Austria.
  • Duering M; Department of Neurology, Medical University Graz, Graz, Austria.
  • Wason J; Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria.
  • Morris RG; Institute for Stroke and Dementia Research, University Hospital, Ludwig Maximilian University Munich, Munich, Germany.
  • Dichgans M; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
  • Schmidt R; MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge Institute of Public Health, Cambridge, UK.
  • Tozer D; Population Health Sciences Institute, Newcastle University, Baddiley-Clark Building, Newcastle upon Tyne, UK.
  • Chen C; Department of Psychology (R.G.M), King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK.
  • de Leeuw FE; Institute for Stroke and Dementia Research, University Hospital, Ludwig Maximilian University Munich, Munich, Germany.
  • Markus HS; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
J Neurol Neurosurg Psychiatry ; 93(1): 14-23, 2022 01.
Article en En | MEDLINE | ID: mdl-34509999
OBJECTIVES: It has been suggested that diffusion tensor imaging (DTI) measures sensitive to white matter (WM) damage may predict future dementia risk not only in cerebral small vessel disease (SVD), but also in mild cognitive impairment. To determine whether DTI measures were associated with cognition cross-sectionally and predicted future dementia risk across the full range of SVD severity, we established the International OPtimising mulTImodal MRI markers for use as surrogate markers in trials of Vascular Cognitive Impairment due to cerebrAl small vesseL disease collaboration which included six cohorts. METHODS: Among the six cohorts, prospective data with dementia incidences were available for three cohorts. The associations between six different DTI measures and cognition or dementia conversion were tested. The additional contribution to prediction of other MRI markers of SVD was also determined. RESULTS: The DTI measure mean diffusivity (MD) median correlated with cognition in all cohorts, demonstrating the contribution of WM damage to cognition. Adding MD median significantly improved the model fit compared to the clinical risk model alone and further increased in all single-centre SVD cohorts when adding conventional MRI measures. Baseline MD median predicted dementia conversion. In a study with severe SVD (SCANS) change in MD median also predicted dementia conversion. The area under the curve was best when employing a multimodal MRI model using both DTI measures and other MRI measures. CONCLUSIONS: Our results support a central role for WM alterations in dementia pathogenesis in all cohorts. DTI measures such as MD median may be a useful clinical risk predictor. The contribution of other MRI markers varied according to disease severity.
Asunto(s)
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Demencia / Imagen de Difusión Tensora Tipo de estudio: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Neurol Neurosurg Psychiatry Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Demencia / Imagen de Difusión Tensora Tipo de estudio: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Neurol Neurosurg Psychiatry Año: 2022 Tipo del documento: Article