$3.2 Million Grant Awarded to Use AI for Improving Heart Transplant Outcomes

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 a 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 principle investigator, Kenneth B. Margulies, MD, a professor of Cardiovascular Medicine at Penn, in partnership with Anant Madabhushi, PhD, 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.

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 computers 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 "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."

Other Penn collaborators for this project include Michael D. Feldman and Priti Lal both in Pathology and Laboratory Medicine, and Eliot Peyster in Cardiovascular Medicine.

Penn Medicine is one of the world's leading academic medical centers, dedicated to the related missions of medical education, biomedical research, and excellence in patient care. Penn Medicine consists of the Raymond and Ruth Perelman School of Medicine at the University of Pennsylvania (founded in 1765 as the nation's first medical school) and the University of Pennsylvania Health System, which together form a $8.6 billion enterprise.

The Perelman School of Medicine has been ranked among the top medical schools in the United States for more than 20 years, according to U.S. News & World Report's survey of research-oriented medical schools. The School is consistently among the nation's top recipients of funding from the National Institutes of Health, with $494 million awarded in the 2019 fiscal year.

The University of Pennsylvania Health System's patient care facilities include: the Hospital of the University of Pennsylvania and Penn Presbyterian Medical Center--which are recognized as one of the nation's top "Honor Roll" hospitals by U.S. News & World Report--Chester County Hospital; Lancaster General Health; Penn Medicine Princeton Health; and Pennsylvania Hospital, the nation's first hospital, founded in 1751. Additional facilities and enterprises include Good Shepherd Penn Partners, Penn Medicine at Home, Lancaster Behavioral Health Hospital, and Princeton House Behavioral Health, among others.

Penn Medicine is powered by a talented and dedicated workforce of more than 43,900 people. The organization also has alliances with top community health systems across both Southeastern Pennsylvania and Southern New Jersey, creating more options for patients no matter where they live.

Penn Medicine is committed to improving lives and health through a variety of community-based programs and activities. In fiscal year 2019, Penn Medicine provided more than $583 million to benefit our community.

Source: https://www.med.upenn.edu/

Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.