Cauda equina compression MRI categorisation
Research type
Research Study
Full title
Cauda equina compression MRI categorisation: per-exisiting research data augmented with routinely collected examinations
IRAS ID
319417
Contact name
Mark Thurston
Contact email
Sponsor organisation
University Hospitals Plymouth NHS Trust
Duration of Study in the UK
3 years, 0 months, 0 days
Research summary
Cauda equina syndrome occurs when the nerves at the base of the spine are suddenly compressed, usually resulting in bladder dysfunction, bowel dysfunction, and/or sensory changes in the saddle area. The condition requires emergency surgery. Delayed treatment can result in long-term irreversible life-changing nerve damage. The incidence has been estimated to be 0.3-0.5 per 100,000 population per year and 19% amongst patients presenting with symptoms2. Diagnosis of nerve compression from history and examination is notoriously hard: patients can present to their GP with non-specific symptoms but have significant and unexpected critical findings on their MRI identified at the point of reporting. There is an ongoing significant backlog of radiology reporting (Cliffe et al, 2016), meaning that many patients referred from the community for MRI will not have their scan reviewed by a radiologist immediately.
Rather than being pre-programmed, supervised machine learning uses labelled datasets to train algorithms to create a model, a computer algorithm that can classify new examples (IBM, 2021). Building a model that can be generalised to new cases requires a large accurately labelled dataset.
A computer vision model that can correctly categorise MRI images would enable prioritised reporting of MRI scans with potential nerve compression.
We propose investigating a machine learning approach to investigate the possibility of automated diagnosis and localisation of nerve compression in MRI spine images. If successful, these methods could be leveraged to develop tools to support clinical pathways and decision-making.
REC name
South Central - Hampshire B Research Ethics Committee
REC reference
23/SC/0064
Date of REC Opinion
11 Feb 2023
REC opinion
Favourable Opinion