FDA clears embedded AI on mobile X-ray device

September 12, 2019 //By Rich Pell
FDA clears embedded AI on mobile X-ray device
GE Healthcare (Chicago, IL) has announced that it has received Food and Drug Administration (FDA) clearance of what it says is an industry-first collection of artificial intelligence (AI) algorithms embedded on a mobile X-ray device.

The FDA's 510(k) clearance, says the company, was for its Critical Care Suite, a collection of AI algorithms designed to help reduce the turnaround time it can take for radiologists to review a suspected pneumothorax, a type of collapsed lung.

"X-ray – the world's oldest form of medical imaging – just got a whole lot smarter, and soon, the rest of our offerings will too," says Kieran Murphy, President & CEO, GE Healthcare. "GE Healthcare is leading the way in the creation of AI applications for diagnostic imaging and taking what was once a promise and turning it into a reality. By integrating AI into every aspect of care, we will ultimately improve patient outcomes, reduce waste and inefficiencies, and eliminate costly errors. Critical Care Suite is just the beginning."

While a prioritized "STAT" X-ray can sit waiting for up to eight hours for a radiologist's review, says the company, when a patient is scanned on a device with Critical Care Suite, the system automatically analyzes the images by simultaneously searching for a pneumothorax. If a pneumothorax is suspected, an alert – along with the original chest X-ray – is sent directly to the radiologist for review via picture archiving and communication systems (PACS).

The technologist also receives a subsequent on-device notification to give awareness of the prioritized cases. Quality-focused AI algorithms simultaneously analyze and flag protocol and field of view errors as well as auto rotate the images on-device.

Embedding Critical Care Suite on-device offers several benefits to radiologists and technologists, says the company. For critical findings, GE Healthcare's algorithms are a fast and reliable way to ensure AI results are generated within seconds of image acquisition, without any dependency on connectivity or transfer speeds to produce the AI results.

These results are then sent to the radiologist at the same time that the device sends the original diagnostic image, ensuring no additional processing delay. Also, automatically running quality

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