Viz.ai leverages AI to detect early signs of time-sensitive medical conditions on imaging. Its first product, which received FDA clearance in February 2018, is a software platform that analyses brain CT scans using deep learning for large vessel occlusions (LVOs), or strokes, notifying a neurointerventional specialist within minutes. Its second FDA-approved product automates CT perfusion analysis, providing advanced brain imaging to help support treatment decisions.

Context

Typically, in the case of stroke, by the time it is diagnosed and an interventional team assembled, too much of a patient’s brain has been affected in order to be able to administer two therapies that can otherwise transform outcomes—clot-busting drugs and thrombectomy (clot removal).   Viz.ai provides a solution to address this problem of delayed time to diagnosis by notifying the interventionalist.

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Context

Typically, in the case of stroke, by the time it is diagnosed and an interventional team assembled, too much of a patient’s brain has been affected in order to be able to administer two therapies that can otherwise transform outcomes—clot-busting drugs and thrombectomy (clot removal).   Viz.ai provides a solution to address this problem of delayed time to diagnosis by notifying the interventionalist.

Availability/regulatory status

The product received FDA approval in February 2018 and is commercial available in the US. It is available as a research version for testing in the UK.

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Evidence to date

Evidence required for FDA approval comprised retrospective case series  analysis.  A Viz.ai study of 300 patients, which supported the FDA approval, showed that the company’s software was able to notify a stroke neurologist on average 7.3 minutes after the brain imaging took place—compared with the hours that it sometimes takes with conventional diagnostic procedures. The technology accurately identified severe strokes as precisely as expert stroke radiologists do, the study found.

Additionally, Viz.ai is currently being tested in prospective research studies in the US and Europe, which are either in progress or in setup.

Research is also in progress to show improvement in patient reported outcomes and experience measures.

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Impact for user

Viz.ai aims to achieve better outcomes for the patient through faster notification of time-sensitive conditions to the right specialist to initiate the correct treatment as soon as possible.

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Impact for healthcare system

Viz.ai aims to augment rather than replace current clinical protocols and addresses inefficiencies in workflow for any given acute diagnostic and treatment pathway, starting with large vessel occlusion stroke.

Overall value assessment

Further experience in the UK is needed but Viz.ai’s technology should improve outcomes by identifying urgent cases, notifying on-call specialists and sending them the scans directly to their smartphone or tablet in a secure environment for much quicker review.