Thais Minett1,2, Li Su3,4, Elijah Mak3, Guy Williams5, Michael Firbank6, Rachael A Lawson6, Alison J Yarnall6, Gordon W Duncan7, Adrian M Owen8,9, Tien K Khoo10, David J Brooks6,11,12, James B Rowe13,14,15, Roger A Barker16, David Burn17, John T O'Brien3. 1. Department of Radiology, University of Cambridge, Cambridge, UK. thaisminett@hotmail.com. 2. Cambridge Institute of Public Health, University of Cambridge, Forvie Site, Cambridge Biomedical Campus, Cambridge, CB2 0SR, UK. thaisminett@hotmail.com. 3. Department of Psychiatry, University of Cambridge, Cambridge, UK. 4. China-UK Centre for Cognition and Ageing Research, Southwest University, Chongqing, China. 5. Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK. 6. Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK. 7. Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK. 8. Brain and Mind Institute, University of Western Ontario, London, Canada. 9. Department of Psychology, University of Western Ontario, London, Canada. 10. School of Medicine, University of Wollongong, Wollongong, NSW, Australia. 11. Division of Neuroscience, Imperial College London, London, UK. 12. Institute of Clinical Medicine, Aarhus University, Aarhus, Denmark. 13. Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK. 14. Medical Research Council, Cognition and Brain Sciences Unit, Cambridge, UK. 15. Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK. 16. John van Geest Centre for Brain Repair, University of Cambridge, Cambridge, UK. 17. Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK.
Abstract
OBJECTIVE: To investigate whether white matter microstructural changes can be used as a predictor of worsening of motor features or cognitive decline in patients with Parkinson's disease and verify whether white matter microstructural longitudinal changes differ between patients with Parkinson's disease with normal cognition and those with mild cognitive impairment. METHODS: We enrolled 120 newly diagnosed patients with early stage Parkinson's disease (27 with mild cognitive impairment and 93 with normal cognition) along with 48 controls. Participants were part of the incidence of cognitive impairment in cohorts with longitudinal evaluation in Parkinson's disease study and were assessed at baseline and 18 months later with cognitive, motor tests and diffusion tensor imaging. The relationships between fractional anisotropy and mean diffusivity with disease status, cognitive and motor function were investigated. RESULTS: At baseline, patients with early stage Parkinson's disease had significantly higher widespread mean diffusivity relative to controls, regardless of cognitive status. In patients with Parkinson's disease/mild cognitive impairment, higher mean diffusivity was significantly correlated with lower attention and executive function scores. At follow-up frontal mean diffusivity increased significantly when comparing patients with Parkinson's disease/mild cognitive impairment with those with normal cognition. Baseline mean diffusivity was a significant predictor of worsening of motor features in Parkinson's disease. CONCLUSIONS: Mean diffusivity represents an important correlate of cognitive function and predictor of motor impairment in Parkinson's disease: DTI is potentially a useful tool in stratification of patients into clinical trials and to monitor the impact of treatment on motor function.
OBJECTIVE: To investigate whether white matter microstructural changes can be used as a predictor of worsening of motor features or cognitive decline in patients with Parkinson's disease and verify whether white matter microstructural longitudinal changes differ between patients with Parkinson's disease with normal cognition and those with mild cognitive impairment. METHODS: We enrolled 120 newly diagnosed patients with early stage Parkinson's disease (27 with mild cognitive impairment and 93 with normal cognition) along with 48 controls. Participants were part of the incidence of cognitive impairment in cohorts with longitudinal evaluation in Parkinson's disease study and were assessed at baseline and 18 months later with cognitive, motor tests and diffusion tensor imaging. The relationships between fractional anisotropy and mean diffusivity with disease status, cognitive and motor function were investigated. RESULTS: At baseline, patients with early stage Parkinson's disease had significantly higher widespread mean diffusivity relative to controls, regardless of cognitive status. In patients with Parkinson's disease/mild cognitive impairment, higher mean diffusivity was significantly correlated with lower attention and executive function scores. At follow-up frontal mean diffusivity increased significantly when comparing patients with Parkinson's disease/mild cognitive impairment with those with normal cognition. Baseline mean diffusivity was a significant predictor of worsening of motor features in Parkinson's disease. CONCLUSIONS: Mean diffusivity represents an important correlate of cognitive function and predictor of motor impairment in Parkinson's disease: DTI is potentially a useful tool in stratification of patients into clinical trials and to monitor the impact of treatment on motor function.
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