image: Satish Viswanath view more
Credit: Case Western Reserve University
CLEVELAND—Building on its successes in applying artificial intelligence (AI) to medical imaging to enhance treatment of other diseases, a Case Western Reserve University-led team next will test its approach with rectal cancer patients.
Specifically, the researchers hope to provide reliable guidance regarding whether patients need to have surgery as part of their treatment.
Colorectal cancer is the third most common cancer diagnosed in men and women in the United States, excluding skin cancer, and includes both colon cancer and cancers in the rectum. The American Cancer Society estimates there will be more than 45,000 new cases of rectal cancer—and more than twice as many new colon cancer cases—in 2021.
But the Case Western Reserve researchers say clinicians don’t have a reliable way to predict which rectal cancer patients would respond favorably to treatments such as chemotherapy or radiation, so most patients have to undergo invasive surgery to remove the rectum and surrounding tissue.
“In too many cases, patients are being overtreated,” said lead researcher Satish Viswanath, an assistant professor of biomedical engineering who is leading the work as a member of the Center for Computational Imaging and Personalized Diagnostics (CCIPD). “Instead, if our AI technology is successful, we could tell the clinician right up front—based on a routine MRI (magnetic resonance imaging) scan—if a patient will do well with only chemoradiation and then can be observed, without having this serious surgery.”
Collaboration and DOD grant
Working in collaboration with physicians at Cleveland Clinic, University Hospitals and the Louis Stokes Cleveland VA Medical Center, the Case Western Reserve team will apply AI techniques to thousands of digitized images from the medical institutions.
The work is supported by a three-year, $755,000 grant from the U.S. Department of Defense’s Congressionally Directed Medical Research Programs.
Other research has reported that up to 30% of people diagnosed with rectal cancer have surgery they didn’t need, Viswanath said, adding that it is often a “surgery that is costly, both financially and in the way it often affects the daily life of the patient afterward.”
Those effects can include the need for a colostomy bag, even if temporary, and possible changes in everything from sexual function and infection to mental health, according to previous research.
Viswanath is collaborating on the research with Pingfu Fu, a professor of Population and Quantitative Health at Case Western Reserve. Clinical co-investigators on the project include physicians Sharon Stein of University Hospitals; David Liska, Andrei Purysko and Smitha Krishnamurthi of Cleveland Clinic; and Eric Marderstein of the VA Medical Center.
The team will work from imaging data from more than 2,000 rectal cancer patients who had been treated at the hospitals over the last five years, and test their AI on about 450 to 500 patients.
They’ll retrospectively test their radiomics to determine if it could have shown which patients would benefit from chemoradiation therapy and which wouldn’t, requiring the surgery.
Radiomics and AI
Radiomics refers to the growing number of AI-driven methods to extract a large number of features from medical images using data-characterization algorithms. The features can then help uncover tumors and other characteristics usually invisible to the naked eye. Throughout this project, Viswanath’s team will design and validate new types of radiomic tools to capture aspects of rectal tumors related to chemoradiation response.
CCIPD Director Anant Madabhushi, the Donnell Institute Professor of Biomedical Engineering at Case Western Reserve, said Viswanath and his team have already made significant strides in using the tools to predict treatment response to rectal cancer.
Madabhushi’s lab, established in 2012 and now with more than 60 researchers, has become a global leader in the field, specializing in the detection, diagnosis and characterization of various cancers and other diseases by meshing medical imaging, machine learning and AI.
“With this award, his team will be able to validate these tools in a multi-institutional setting with CWRUs various affiliate medical partners, setting the stage for prospective clinical trials,” Madabhushi said.
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Method of Research
Meta-analysis
Subject of Research
People