Earlier diagnosis of atypical Parkinsonian conditions from MRI using machine learning

Disease area(s): Neuroscience; Multiple system Atrophy, Corticobasal syndrome, Progressive Supranuclear Palsy
Data sources: University Hospitals Plymouth NHS Trust (UHPNT); Parkinson’s Progression Markers Initiative (PPMI);PROSPECT-M study
Project stage: Data collation
Ethical approval: Granted (Reference Number: 21/PR/0918)
Principal Investigator: Stephen Mullin
Lead Researcher: Megan Courtman
Funder(s): Rotary Club Holsworthy;
Reference:

Summary

The atypical Parkinsonian syndromes Progressive Supranuclear Palsy, Multiple System Atrophy and Corticobasal Syndrome are rapidly progressive neurological conditions with a poor prognosis. Initially they may present almost identically to Parkinson’s disease. A number of promising treatments to slow down or halt the progression of these diseases are currently being tested in drug trials. Using Artificial Intelligence, we aim to train a model to identify features on MRI brain scans which may allow earlier diagnosis of the three conditions.

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