August 13, 2019

An Artificial Intelligence Tool to Improve Pancreatic Cancer Outcomes

By Sharon Rosen

Article by Barbara Toman

Only 9% of people with pancreatic cancer live for five years after diagnosis. "That is an abysmally low number, probably the worst in human cancers," says Michael Wallace, M.D., a digestive disease specialist at the Mayo Clinic campus in Florida. "We want to get that rate substantially higher."

Artificial intelligence is providing a way to do just that. In collaboration with the University of Central Florida (UCF), Mayo Clinic has developed an algorithm that can identify individuals at high risk of pancreatic cancer. Typically, pancreatic cancer is found when it's too advanced for curable surgery. But people who are identified as high risk can be monitored to catch cancer early.

"Outcomes from other cancers — colon, breast, prostate and lung — have improved dramatically in the past decades, largely through early detection programs such as colonoscopy and mammograms," Dr. Wallace says. "We are applying that model to pancreatic cancer."

Michael Wallace, M.D.

Through the Center for Individualized Medicine, Mayo Clinic is committed to a personalized medicine approach to assessing disease risk. Artificial intelligence is key to evaluating the risk of pancreatic cancer because screening for that disease is challenging.

"The only effective screening modalities for pancreatic cancer are very expensive and somewhat invasive. We wouldn't want to screen the general population," Dr. Wallace says. "But identifying individuals who are at above-average risk for pancreatic cancer allows us to apply that screening only to them."

A first in artificial intelligence

Artificial intelligence is increasingly used to inform image analysis. But the Mayo Clinic-UCF work is the first to address pancreatic cancer.

Recent studies have found that pancreatic cancer often starts with a precancerous cyst known as an intraductal papillary mucinous neoplasm (IPMN). Like a skin mole, an IPMN is capable of remaining harmless or developing into cancer. Pancreatic cysts are commonly seen on abdominal and lung MRIs that people might have for another purpose.

"About 40% of people have some sort of pancreatic cyst. The vast majority are benign," Dr. Wallace says.

Radiologists who analyze scans of pancreatic cysts look for certain factors such as a cyst's size and location. But those factors aren't very accurate at predicting cancer risk. "If you sent people to surgery based on the existing criteria, only about half would turn out to have pancreatic cancer or an advanced precancerous cyst," Dr. Wallace says.

Like the human brain, Mayo Clinic's artificial intelligence tool learns from experience. The researchers fed into the algorithm MRIs of individuals whose IPMNs progressed to cancer, and MRIs from a control group whose IPMNs remained benign for many years. Once the algorithm was "trained," its classifications of high-risk and low-risk cysts were compared to classifications made by Mayo Clinic radiologists.

"We found that the algorithm reads a scan — which is about 1,200 images — in roughly half a second, versus the 20 to 30 minutes an average radiologist would need," Dr. Wallace says.

But the benefits go far beyond speed. The algorithm is accurate, identifying high-risk cysts with the same precision as Mayo Clinic's expert pancreatic radiologists. Yet the algorithm doesn't require a world-class radiologist.

"The algorithm can be embedded in any MRI scanner," Dr. Wallace says. "This artificial intelligence has the potential to provide high-quality image interpretation to people anywhere in the world."

The next step is further enhancing the algorithm's accuracy. Dr. Wallace and his UCF colleagues recently received National Institutes of Health funding that will allow them to feed more pancreatic cyst scans into the algorithm.

"The more cases we have, the better we can train and refine the algorithm," Dr. Wallace says. "It's like an online photo collection — the more times you tag someone's face on your photo app, the better the app is at detecting that person on unknown photographs. An algorithm that is as good as our best radiologists isn't good enough. We want the algorithm to be better than that."

More tools for earlier cancer detection

Kristin Clift

In addition to applying artificial intelligence to imaging, Mayo Clinic is using patient questionnaires and genetic DNA testing to better characterize pancreatic cancer risk. Both approaches can help patients through earlier detection and treatment of cancer.

The patient questionnaire — designed by CIM with support from the Florida Pancreas Cancer Coalition and Champions for Hope — seeks to identify individuals with genetic syndromes that can increase the risk of pancreatic cancer. People who see Dr. Wallace for any gastrointestinal issue complete the questionnaire before their appointments.

"Although this tool is low-tech, it has already helped us direct people to genetic counseling and to identify individuals with pathogenic variants associated with pancreatic cancer," says Kristin Clift, who coordinates research for the Center for Individualized Medicine.

The questionnaire goes beyond pancreatic cancer to ask about a family history of other diseases, including breast cancer. "Many people understand that the BRCA1 and BRCA2 mutation can increase your risk for breast and ovarian cancer. But those mutations also increase risk for pancreatic cancer," Clift says.

Among 430 people who completed the questionnaire, 25% met National Comprehensive Cancer Network guidelines for referral to genetic counseling and testing. Three individuals were found to have pathogenic variants associated with pancreatic cancer, including one who was found to have the disease.

"The genetic testing helped determine the best treatment option for that individual. Her sister also came in for genetic testing and was found to have the variant," Clift says. "We were able to put the sister on a screening regimen so that we can catch the cancer earlier if it develops."

For Dr. Wallace, genetic testing and artificial intelligence are critical to improving pancreatic cancer outcomes. "They both allow for early detection. There is a strong need for better classification of individual risk, and we are committed to it."

The latest in cancer care

Join us for Individualizing Medicine 2019 Conference: Precision Cancer Care through Immunotherapy and Genomics on Sept. 20-21, in Scottsdale, Arizona. 

The conference brings together experts from Mayo Clinic and across the country to present and discuss case-based approaches to using genomics and new immunotherapies that oncologists and their teams can bring back to their own patients.

Other key conference themes include:

  • CAR-T cell therapy
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  • National Cancer Institute match

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Tags: #algorithm, #Artificial Intelligence, #Champions for Hope, #digestive diseases, #Dr. Michael Wallace, #Florida Cancer Coalition, #National Comprehensive Cancer Network, #University of Central Florida, Cancer, cancer screening, center for individualized medicine, Florida Pancreas Cancer Coalition, Genetic Testing, genomics, Kristin Clift, mayo clinic, Precision Medicine

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