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July 10, 2020

FDA grants 510(K) clearance to Infervision AI-based chest CT algorithm

The US Food and Drug Administration has granted 510(K) clearance to Infervision for its InferRead Lung CT.AI product that assists radiologists in lung segmentation.

The US Food and Drug Administration has granted 510(K) clearance to Infervision for its InferRead Lung CT.AI product that assists radiologists in lung segmentation.

This tool utilises artificial intelligence (AI) and deep learning technology to automatically perform lung segmentation and support concurrent reading.

It can also identify and label nodules of different types and can assist radiologists to detect pulmonary nodule during the review of chest CT scans.

The company noted that the system may also benefit lung cancer screening (LCS) programmes aimed at the early diagnosis and treatment of the high-risk population in the US.  Lung cancer is said to be the second most common cancer in both men and women in the US.

Following the FDA clearance, Infervision plans to move into the North American market with the launch of the product.

Infervision North America director Matt Deng said: “This is the first FDA clearance for our deep-learning-based chest CT algorithm and it will lead the way to better integration of advanced AI solutions to help the healthcare clinical workflow in the region.

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“Fast, workflow friendly, and accurate are the three key areas we have emphasised during product development. We’re very excited to be able to make our InferRead Lung CT.AI solution available to the North American market.”

InferRead Lung CT.AI, which obtained CE mark in Europe, is claimed to be used at over 380 hospitals and imaging centres worldwide.

Meanwhile, the US FDA has also cleared Therapixel’sAI-based software MammoScreens that aids radiologists in reading mammograms.

The software automatically detects and characterises suspicious soft tissue lesions and calcifications in mammogram images while assessing their likelihood of malignancy.

MammoScreen was granted FDA clearance following the results from a multi-reader multi-case study. The study found improvement in readers’ performance in cancer detection in mammograms when paired with the software.

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