Mayo Clinic’s AI innovation inspires hope in early detection of pancreatic cancer

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By Ethan Grove

Estimated to become the second leading cause of cancer deaths in the U.S. by 2030, nearly 70% of people with pancreatic cancer face mortality within the first year of diagnosis. Unfortunately, 40% of small pancreatic cancers elude detection on CT scans until they've advanced to an incurable stage.

In a recent breakthrough, Mayo Clinic Comprehensive Cancer Center researchers built an artificial intelligence (AI) model that has shown potential for autonomous detection of pancreatic cancer on standard CTs when surgery can still promise a cure.

The group developed a highly accurate AI model — trained on more than 3,000 patients — for fully automated cancer detection, including small and otherwise difficult-to-detect tumors. Published in Gastroenterology, the journal of the American Gastroenterological Association, the study builds on the group's recent work on radiomics-based early detection models.

Most important, the model could detect visually imperceptible cancer from normal-appearing pancreases on prediagnostic CT images (those acquired at three to 36 months prior to clinical diagnosis) substantially early — a median of 438 days — before clinical diagnosis.

"These findings suggest that AI has the potential to detect hidden cancers in asymptomatic individuals, allowing for surgical treatment at a stage when a cure is still achievable," says Ajit H. Goenka, M.D., a Mayo Clinic radiologist and principal investigator and corresponding author.

Finally, the model remained reliable and accurate across diverse patient groups and variations in scanning equipment and imaging techniques. This resilience is crucial for the model's utility in a wide array of real-world medical scenarios.

The team also deconstructed the AI's decision-making process to ensure transparency, acknowledging that trust and quality control are essential for AI's broader clinical acceptance.

"We owe the progress to the ingenious efforts of the Framework for AI Software Technology, or FAST, team led by Panagiotis Korfiatis, Ph.D., complemented by our team of exceptionally bright research fellows and data science analysts," says Dr. Goenka. "They dedicated months to meticulous preparation for our initial submission and invested significant effort to astutely address the incisive queries of the panel of international reviewers."

Mayo Clinic has already initiated the steps for clinical validation and the models are undergoing regulatory processes. With backing from the Mayo Clinic Comprehensive Cancer Center, the team is set to undertake benefactor-funded prospective screening trials. The insights from these trials will refine and bolster the practical effectiveness of their innovative approach.

This research was supported by the National Cancer Institute of the National Institutes of Health under award numbers: R01CA272628 and R01CA256969, as well as from the Centene Charitable Foundation, and the Champions for Hope Pancreatic Cancer Research Program of the Funk Zitiello Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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A version of this article was originally published as a news release on the Mayo Clinic News Network.