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A data-driven model of brain volume changes in progressive supranuclear palsy

Scotton, WJ; Bocchetta, M; Todd, E; Cash, DM; Oxtoby, N; Vande Vrede, L; Heuer, H; ... Wijeratne, PA; + view all (2022) A data-driven model of brain volume changes in progressive supranuclear palsy. Brain Communications , Article fcac098. 10.1093/braincomms/fcac098. (In press). Green open access

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Abstract

The most common clinical phenotype of progressive supranuclear palsy is Richardson syndrome, characterised 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 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 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.

Type: Article
Title: A data-driven model of brain volume changes in progressive supranuclear palsy
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/braincomms/fcac098
Publisher version: https://doi.org/10.1093/braincomms/fcac098
Language: English
Additional information: © The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: event-based model, disease progression, Progressive Supranuclear Palsy, biomarkers, machine learning
UCL classification: UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Movement Neurosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neurodegenerative Diseases
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS
URI: https://discovery.ucl.ac.uk/id/eprint/10147466
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