FDA clears RapidAI's occlusion-spotting stroke software for CT scans

Red blood cells
The program is designed to help physicians triage patients in a matter of minutes, by assessing regions of the brain with reduced blood vessel density, a possible sign of a dangerous blood clot. (Wikimedia Commons)

RapidAI has secured an FDA clearance for its artificial intelligence algorithms that quickly parse brain CT scans and spot suspected large vessel occlusions, the cause of fatal or debilitating strokes.

The program is designed to help physicians triage patients in a matter of minutes, by tracking blood vessels highlighted in the scan and assessing regions of the brain with reduced blood vessel density, a possible sign of a dangerous blood clot.

This produces enhanced angiography images with color-coded overlays from a typical CT scan. The system also notifies stroke team members when a large vessel occlusion is suspected.

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In addition, this past June, RapidAI received a separate FDA computer-assisted diagnostic software clearance, known as the CADx category, for a product designed to improve physicians’ interpretations of non-contrast CT scans.

That automated program applies the standardized Alberta Stroke Program Early CT Scoring system, or ASPECTS, which is used to determine the severity of a stroke and areas of irreversible brain injury.

“Rapid ASPECTS represents the next AI-powered step forward in stroke imaging, and the groundbreaking CADx clearance from the FDA puts it in a class by itself,” said RapidAI co-founder Greg Albers, a professor of neurology at Stanford University and director of the Stanford Stroke Center. “In addition to helping stroke teams with faster triage and transfer decisions, Rapid ASPECTS also improves the accuracy of typical readers.”

Meanwhile, the company recently announced that it recorded its one millionth scan across its portfolio—spanning non-contrast CT, CT angiography and CT perfusion, as well as MRI diffusion and perfusion scans, all gathered from more than 1,600 hospitals in 50 countries. This data is in turn used to help train and enhance the performance of its machine learning algorithms.

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