In 2018, NYU and Facebook also collaborated and developed an approach called FastMRI that utilizes AI to cut MR imaging time down by four times by acquiring less data than traditionally needed for a quality image, without compromising image quality. A study in 2019 found that it was just as effective as a traditional MR.

Shenoy, who is also a cardiologist at M Health Fairview, says the research by him and his team is the first large-scale validation of the approach’s ability to exclude cardiac tumors and to diagnose them. He expects it to help lead to CMR’s incorporation in future guidelines, appropriateness documents and health policies.


“Our findings will benefit hospitals and physicians who now have large multicenter data to support the use of CMR in these patients or referral to hospitals that can do CMRs (not every hospital can do them),” he said. “Insurance providers can preferentially approve/reimburse CMR for this indication over other imaging tests. Doing one definitive imaging test rather than trying multiple other ones would save costs, decrease patient burden and anxiety and speed up treatments.”

Research was funded by the National Institutes of Health.

The findings were published in the European Heart Journal.

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