FDA clears AI-based system for detecting prostate cancer

The product promises to reduce time and cost of MRI scans

Chuck Martin

October 30, 2020

2 Min Read

The product promises to reduce time and cost of MRI scans

The US Food and Drug Administration (FDA) has granted New York-based healthcare technology startup Ezra 510(k) clearance for an AI-based system for prostate cancer screening.

The Ezra Prostate AI aims to help shorten the time of MRI-based prostate screening, and reduce the price of a scan by 15%.

The FDA clearance recognizes Ezra’s AI solution as safe and effective, allowing marketing in the US.

The clearance includes the approval to use Plexo, a cloud-based image archiving and communications platform that works in a browser, enabling radiologists to use the AI system without installing additional software.

At the forefront

The Ezra Prostate AI's segmentation capabilities can improve radiologists’ workflow efficiency by automatically rendering 3D volumes of the prostate gland and potential lesions.

"Over the past two years, our team has worked tirelessly on building Ezra's Prostate AI,” said Emi Gal, CEO and co-founder of the company. "We will continue to work towards making the interpretation of prostate MRI scans faster and more affordable, in order to support the millions of men who are at risk of prostate cancer."

Ezra launched its MRI-based prostate cancer screening service in January 2019, followed by a full-body MRI scan in May.

The company has partnered with outpatient imaging company RadNet, and reports that it helped four percent of its members detect cancer in 2019 – all of whom were asymptomatic.

"Ezra is at the forefront of MRI-based cancer screening, and the company's 510(k) FDA clearance for its Prostate AI is further validation of its innovation capabilities," said Lawrence Tanenbaum, vice president, CTO and director of MRI, CT and Advanced Imaging at RadNet.

Across FDA approvals of AI-based medical devices and algorithms, radiology accounts for 72% of medical innovations, primarily for applied image reading software, according to Nature Research.

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