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Scotton WJ, Bocchetta M, Todd E, Cash DM, Oxtoby N, VandeVrede L, Heuer H, Alexander DC, Rowe JB, Morris HR, Boxer A, Rohrer JD, Wijeratne PA. A data-driven model of brain volume changes in progressive supranuclear palsy. Brain Commun 2022; 4:fcac098. [PMID: 35602649 PMCID: PMC9118104 DOI: 10.1093/braincomms/fcac098] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 12/08/2021] [Accepted: 04/11/2022] [Indexed: 11/13/2022] Open
Abstract
The most common clinical phenotype of progressive supranuclear palsy is Richardson syndrome, characterized by levodopa unresponsive symmetric parkinsonism, with a vertical supranuclear gaze palsy, early falls and cognitive impairment. There is currently no detailed understanding of the full sequence of disease pathophysiology in progressive supranuclear palsy. Determining the sequence of brain atrophy in progressive supranuclear palsy could provide important insights into the mechanisms of disease progression, as well as guide patient stratification and monitoring for clinical trials. We used a probabilistic event-based model applied to cross-sectional structural MRI scans in a large international cohort, to determine the sequence of brain atrophy in clinically diagnosed progressive supranuclear palsy Richardson syndrome. A total of 341 people with Richardson syndrome (of whom 255 had 12-month follow-up imaging) and 260 controls were included in the study. We used a combination of 12-month follow-up MRI scans, and a validated clinical rating score (progressive supranuclear palsy rating scale) to demonstrate the longitudinal consistency and utility of the event-based model's staging system. The event-based model estimated that the earliest atrophy occurs in the brainstem and subcortical regions followed by progression caudally into the superior cerebellar peduncle and deep cerebellar nuclei, and rostrally to the cortex. The sequence of cortical atrophy progresses in an anterior to posterior direction, beginning in the insula and then the frontal lobe before spreading to the temporal, parietal and finally the occipital lobe. This in vivo ordering accords with the post-mortem neuropathological staging of progressive supranuclear palsy and was robust under cross-validation. Using longitudinal information from 12-month follow-up scans, we demonstrate that subjects consistently move to later stages over this time interval, supporting the validity of the model. In addition, both clinical severity (progressive supranuclear palsy rating scale) and disease duration were significantly correlated with the predicted subject event-based model stage (P < 0.01). Our results provide new insights into the sequence of atrophy progression in progressive supranuclear palsy and offer potential utility to stratify people with this disease on entry into clinical trials based on disease stage, as well as track disease progression.
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Affiliation(s)
- W. J. Scotton
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen
Square Institute of Neurology, University College London, London, UK
- Correspondence to: William J. Scotton UCL Institute of Neurology
Department of Neurodegeneration Dementia Research Centre First Floor, 8-11 Queen Square,
WC1N 3AR London, UK E-mail:
| | - M. Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen
Square Institute of Neurology, University College London, London, UK
| | - E. Todd
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen
Square Institute of Neurology, University College London, London, UK
| | - D. M. Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen
Square Institute of Neurology, University College London, London, UK
| | - N. Oxtoby
- Centre for Medical Image Computing, Department of Computer Science, University
College London, London, UK
| | - L. VandeVrede
- Department of Neurology, Memory and Aging Center, University of
California, San Francisco, CA, USA
| | - H. Heuer
- Department of Neurology, Memory and Aging Center, University of
California, San Francisco, CA, USA
| | | | - D. C. Alexander
- Centre for Medical Image Computing, Department of Computer Science, University
College London, London, UK
| | - J. B. Rowe
- Department of Clinical Neurosciences, Cambridge University, Cambridge
University Hospitals NHS Trust, Cambridge, UK
- Medical Research Council Cognition and Brain Sciences Unit, Cambridge
University, Cambridge, UK
| | - H. R. Morris
- Department of Clinical and Movement Neurosciences, University College London
Queen Square Institute of Neurology, London, UK
- Movement Disorders Centre, University College London Queen Square Institute of
Neurology, London, UK
| | - A. Boxer
- Department of Neurology, Memory and Aging Center, University of
California, San Francisco, CA, USA
| | - J. D. Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen
Square Institute of Neurology, University College London, London, UK
| | - P. A. Wijeratne
- Centre for Medical Image Computing, Department of Computer Science, University
College London, London, UK
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