An AI tool has had a life-changing impact for many patients by helping clinicians to identify the signs of major strokes, allowing for faster access to specialist treatment.
The Brainomix 360 Stroke imaging tool was initially developed by a spin-out from the University of Oxford. It has since been used in more than 30 countries worldwide, and in over 70 NHS hospitals. ‘Brainomix’ might sound like a gadget from a Wallace & Gromit short film, but NHS England says that the tool has provided a second chance for thousands of patients.

The AI technology analyses CT scans in real time, looking for key biomarkers in the brain that indicate a large vessel occlusion (LVO) – a severe type of ischemic stroke caused by a blockage in one of the brain’s major arteries. Endovascular thrombectomy is a specialist treatment for this kind of major stroke, involving a minimally invasive procedure to remove the clot. While effective, this treatment is highly time sensitive. Every 20-minute delay in receiving a thrombectomy, which is generally delivered in a specialist stroke treatment centre, cuts the chance of full recovery by around 1%. Many patients are diagnosed too late for the treatment to be of benefit.
AI tool can help spot stroke signs an hour or more earlier
A tool that can speed up accurate diagnosis can be a literal life saver. NHS England said that it is of particular value in hospitals without on-site neuroradiology expertise. In such cases, faster interpretation can be critical and it was in these settings that the study found the greatest increases in diagnosis and transfer times.
The study, which was published last week in the Lancet Digital Health journal, looked at data collected by the national stroke audit registry from 107 hospitals in England over a five-year period. It found that hospitals using the AI tool saw thrombectomy rates at participating sites double (from 2.3% to 4.6%), compared with smaller increases observed at hospitals not using the technology (from 1.6% to 2.6%).
Dr David Hargroves, NHS National Clinical Director for Stroke and a co-author of the study, said: “This technology supports clinicians to make rapid treatment decisions, which means more patients can receive life- and disability-saving treatments in time – giving them a better chance of returning to independent living.”
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