ASTRONOMY

The collaborative team will utilize automated intelligence to determine the likelihood of acceptance or rejection of donor's hearts

A team of researchers in the Perelman School of Medicine at the University of Pennsylvania, Case Western Reserve University, Cleveland Clinic, and Cedars-Sinai Medical Center, were recently awarded a $3.2 million grant from the National Institutes of Health (NIH) to enhance research for improving heart transplant outcomes for patients. The four-year grant will fund a project exploring the use of artificial intelligence (AI)-driven analysis to determine the likelihood of cardiac patients accepting or rejecting a new heart.

One of the most significant risks of heart transplantation is the patient's body rejecting the donor organ. The body's immune system may see the donor heart as a foreign object and try to reject it, which can then damage the organ. Rejections occur in 30 to 40 percent of patients during the first year after transplant. However, it is widely appreciated that the current rejection grading standard has poor diagnostic accuracy, and has limited ability to discern the mechanism of rejection. These limitations expose patients to risks of both over- and under-treatment.

The team will utilize AI to analyze cardiac biopsy tissue images to distinguish potential cardiac rejection grades and detect patterns of immune cells that reveal the mechanism of rejection. Improved diagnostic accuracy may allow for earlier recognition of serious rejection and also may promote reduced rates of infection and other complications of immune-suppressing drugs taken by transplant patients. Better identification of rejection mechanisms will allow for more precise targeting of the medications. The team also hopes to identify patterns to help predict how patients will do over the long-term, and allow fewer biopsies of the heart.

Penn Medicine, Case Western, Cleveland Clinic, and Cedars-Sinai Medical Center will provide the data--digitized images of biopsies from patients who have already had transplants. The principal investigator, Kenneth B. Margulies, MD, a professor of Cardiovascular Medicine at Penn, in partnership with Anant Madabhushi, Ph.D., a professor of Biomedical Engineering at Case Western Reserve and director of the Center for Computational Imaging and Personalized Diagnostics, will apply the AI techniques to the data to see whether the initial biopsy images could have more accurately predicted which patients would accept or reject the new heart.

"This research is focused on a critical component of heart transplantation--improving patient outcomes. Unfortunately, the number of patients with end-stage heart failure is increasing. But research like this is another step in the right direction for improving survival and quality of life for heart failure patients," Margulies said. {module INSIDE STORY}

In addition, the research team will compare the relative performance of the AI analysis against human pathologists to compare their accuracy in identifying serious rejection. Previous research has shown that supercomputers were more accurate than their human counterparts in diagnostic ability. However, the team believes pathologists will not be replaced by computers; instead, Margulies asserts that "[super]computer-aided tissue diagnostics will serve as a decision support tool for pathologists, consistently and efficiently identifying subtle features that will increase the value of the diagnostic procedure and ultimately improve patient outcomes."