Artificial Intelligence-Assisted Magnetic Resonance Imaging for Quality, Efficiency and Equity in the National Health Service (NHS) Care of Multiple Sclerosis (AssistMS)

Queen Mary University of London

Status

Enrolling

Conditions

Multiple Sclerosis

Treatments

Device: AI software

Study type

Interventional

Funder types

Other

Industry

Identifiers

NCT07111637

Worktribe 8529379

AI_AWARD02608 (Other Grant/Funding Number)

Details and patient eligibility

About

Multiple Sclerosis (MS) is a long-term disease that affects over 150,000 people in the UK. Starting treatment early is important for managing Multiple Sclerosis (MS). It is also essential to monitor the treatment to see if it is working and to switch treatments if needed.

Magnetic resonance imaging (MRI) is the only accepted tool to monitor how well the treatment is working. Current evaluation of brain Magnetic resonance imaging (MRI) scans requires visual inspection, of which sensitivity is degraded by human, and technical factors, such as lack of time, fatigue of radiologists, and lack of standardization of image acquisition protocols across the National Health Service (NHS). MRI-readings can be significantly enhanced by artificial intelligence (AI)-assistive software. Evidence suggests the rate of new lesion detection to be 3 - 4 times higher when using assistive software compared to visual inspection of MRI scans.

In this study, an Artificial Intelligence (AI) software called "icobrain ms." developed by the company "icometrix" (Leuven, Belgium) is tested. This tool helps track MS by measuring changes in the brain using MRI scans. The AI can highlight problem areas and create reports that doctors can use to make better decisions about participants' treatment. The aim of the study is to prove that icobrain ms can be used to assist the neuro-radiologist with their visual assessment of MRI scans by a radiologist, and that it will help clinicians make more informed decisions about participants' current MS treatment.

Enrollment

1,336 estimated patients

Sex

All

Ages

18 to 99 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

Clinically Isolated Syndrome suggestive of demyelination (CIS) or definitive diagnosis of MS.
Undergoing MRI head investigation.
On an MS DMT pathway.
Access to a smartphone, tablet or computer.

Exclusion criteria

patients with Multiples Sclerosis participating in a randomised controlled CTIMP (participating in a single arm study may be included, provided this is in line with the other protocol).