Multimodal PET-MRI profiling predicts dementia with Lewy bodies in isolated REM sleep behaviour disorder.
Multimodal PET-MRI profiling predicts dementia with Lewy bodies in isolated REM sleep behaviour disorder.
Where did the research take place?
The study site has not been established. Author addresses may differ from where the research occurred.
DK · Author affiliation · country only
Department of Nuclear Medicine, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, Aarhus N, J220, 8200, Aarhus, Denmark. andreasbaun@clin.au.dk.Location evidence
Barcelona, ES · Author affiliation
Neurology Service, Department of Neurology, Hospital Clínic de Barcelona, 08036, Barcelona, Spain. airanzo@clinic.cat.Location evidence
Centro, ES · Author affiliation
Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic, IDIBAPS, Universitat de Barcelona, Barcelona, Catalonia, Spain. airanzo@clinic.cat.Location evidence
Aalborg, DK · Author affiliation
Department of Neurology, Aalborg University Hospital, Aalborg, Denmark.Location evidence
Manchester, GB · Author affiliation
Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK.Location evidence
Newcastle upon Tyne, GB · Author affiliation
Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK.Location evidence
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Original abstract
Despite isolated REM sleep behaviour disorder (iRBD) reliably identifying individuals at high risk of developing Parkinson's disease (PD) or dementia with Lewy bodies (DLB), with more than 90% converting, the neurobiological markers of the conversion phenotype are not fully understood. Most previous studies have found univariate imaging biomarkers of phenoconversion, and most of these lack specificity for PD and DLB. Using a well-characterised iRBD cohort (N=21), receiving multiple PET and MRI scans, we aimed to assess if the inter-modality relationship can specifically predict conversion to PD or DLB. The patients received [18F]-DOPA, [11C]-Donepezil and [11C](R)-PK11195 PET and structural MRI scans to derive grey matter (GM) volume along with dynamic susceptibility contrast MRI to extract measures of microcirculatory dysregulation. We used a multimodal adaptation of the scaled sub-profile model to identify patterns of multimodal covariance across the PET and MRI scans. We identified a multimodal network characterised by high neuroinflammation, cholinergic dysfunction, GM atrophy and microcirculatory dysfunction with the covariance pattern converging in the medial occipito-parietal cortex (OPC). The combined pathology from the OPC and striatal [18F]-DOPA uptake was able to specifically predict conversion into DLB (sub-distribution hazard ratio=38.68, 95% confidence interval: 7.545-198.3), and this survived correction for age and disease duration. These findings demonstrate the feasibility of integrating multiple modalities in risk assessment and suggest that posterior cortical pathology, along with striatal dopaminergic impairment, could hold predictive value for phenotype-specific conversion of iRBD patients, and that multiple pathological processes converge in this brain region.