New study shows Brainomix 360 AI transforms stroke treatment in England

  • The study represents the largest real-world evaluation of stroke artificial intelligence (AI) imaging, involving more than 80,000 patients at 26 sites over a 3-year period.
  • The results showed Brainomix 360 Stroke was associated with an additional 50% increase in the number of patients receiving mechanical thrombectomy, while also improving the speed of treatment by 49 minutes.

Oxford, UK and Chicago, USA - 15 May 2024 – Results from the largest prospective study of stroke AI software were presented today at the European Stroke Organisation Conference (ESOC) in Basel, showing that the implementation of Brainomix 360 Stroke was associated with a 50% greater increase in the number of patients receiving mechanical thrombectomy. Mechanical thrombectomy is a life-changing stroke treatment which can reduce disability and prevent or limit long-term care needs in patients with the most severe strokes due to blockage of a large blood vessel supplying the brain.

The study stemmed from an independent evaluation of Brainomix 360 Stroke commissioned by the UK government across five stroke networks over 3 years to determine the real-world impact of AI technology. The analysis, led by Health Innovation (HIN) Oxford & Thames Valley, was conducted using patient-level and site-level data from the Sentinel Stroke National Audit Programme (SSNAP), including more than 83,000 individual stroke patient data from the 26 sites participating in the evaluation. When compared against site-level data from 73 UK hospitals not included in the AI award, the results showed the rate of mechanical thrombectomy rose by 115% at evaluation sites, 50% higher than the increase observed at non-evaluation sites (65%).

Dr Kiruba Nagaratnam, Consultant Stroke Physician and Clinical Lead for Stroke Medicine at the Royal Berkshire NHS Foundation Trust, was the lead author of the study and presented the results Wednesday afternoon at ESOC.  “This study is the largest real-world evaluation of stroke AI software, with more than 80,000 patients assessed over 3 years. The results showed that the introduction of Brainomix 360 Stroke reduced the door-in-door-out (DIDO) time by 49 minutes – and notably, was associated with a significant increase in the number of patients receiving mechanical thrombectomy. These are very powerful results and show that the large-scale implementation of the Brainomix software as a component of a collaborative model of care in stroke networks is feasible and is associated with increasing access to mechanical thrombectomy treatment.”

Dr George Harston, Chief Medical & Innovation Officer at Brainomix and Consultant Stroke Physician at Oxford University Hospitals NHS Foundation Trust, said: "We are delighted to see the dramatic increase in stroke treatment numbers and improved treatment times across multiple stroke networks in England following the implementation of Brainomix 360 Stroke. This is the largest study of stroke AI software ever undertaken, and the results not only validate the generalisability of the findings we have seen in single-site studies, but also reflect the comprehensive nature of the Brainomix 360 Stroke platform, which uniquely delivers value to both primary and comprehensive stroke centers.

“We estimate that if the same increase on thrombectomy had been seen across the whole NHS in England, in a single calendar year the cost savings to the UK economy would be around £30 million.

"We would like to thank the Oxford HIN and NHS Accelerated Access Collaborative (AAC) for their robust evaluation and support, and to all the hospital teams and patients who collaborated in this landmark research study."

This latest study builds on a growing body of evidence validating the impact of Brainomix’s stroke AI imaging platform, including a study published earlier this year in Frontiers in Neurology1 which showed that the implementation of Brainomix 360 Stroke at the Royal Berkshire Hospital improved patient outcomes, trebling the number of stroke patients achieving functional independence from 16% to 48%.

1 Nagaratnam K et al. Artificial intelligence-based decision support software to improve the efficacy of acute stroke pathway in the NHS: an observational study. Frontiers in Neurology. 2024;14

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