Artificial intelligence-assisted magnetic resonance imaging for quality, efficiency and equity in the NHS care of multiple sclerosis (Assist-MS)

Multiple sclerosis (MS) is a chronic, disabling disease driven by an abnormal immune response to the central nervous system. Over 150,000 people live with MS in the UK costing the NHS more than £1billion/year. Early disease modifying treatment (DMT) is part of the standard of care for people with MS (pwMS). Unless effectively treated, MS leads to significant disability, and associated care costs, in most cases. However, whether any of the currently licensed fifteen DMTs is effective in an individual person with MS is unpredictable. Effective treatment monitoring is essential to (i) detect signs of disease activity before the individual suffers its effects and (ii) enable early switching to a different, hopefully (more) effective, DMT. In clinical practice, regular magnetic resonance imaging (MRI) is the only established tool for DMT efficacy monitoring. However, detecting the often subtle changes by inspecting MRI scans is time consuming, tiring and therefore error-prone. icobrain ms is a validated AI technology enabling quantification of MRI datasets, summarising findings in a structured electronic report as well as annotated images highlighting areas of change that help guide assessment. icobrain ms complements visual assessment of MRI scans and helps the clinician to decide whether or not a change in DMT is warranted. This is a prospective clinical study to compare icobrain ms-assisted MRI in the assessment of disease activity compared to current standard of practice in a real world setting. Additionally, we will undertake a health-economic analysis of the impact of icobrain ms on the disease course and NHS resources.