AI Integration Aims to Solve US Heart Donor Crisis by Overhauling High-Stakes Transplant Decision-Making

New AI tools like TOPHAT help surgeons evaluate donor hearts in minutes, aiming to reduce the 70% discard rate and save more lives on transplant wait lists.

By: AXL Media

Published: Apr 22, 2026, 4:12 AM EDT

Source: Information for this report was sourced from International Society for Heart and Lung Transplantation

The Critical Window of Transplant Evaluation

At the International Society for Heart and Lung Transplantation 46th Annual Meeting, Dr. Brian Wayda of the NYU Grossman School of Medicine highlighted a persistent crisis in cardiac care: the massive shortage of donor organs. Currently, nearly 4,000 patients in the United States remain on transplant waiting lists, many of whom are on life support in intensive care units. Despite this desperate need, approximately 60% to 70% of available donor hearts are discarded. Surgeons typically face an intense 15 to 30-minute window, often during overnight hours, to review donor histories, lab tests, and imaging before deciding whether to accept or decline an organ for a specific recipient.

Data-Driven Support for Rapid Decision Cycles

To mitigate the risks associated with these time-sensitive judgment calls, researchers have introduced AI tools like TOPHAT, or the Tool Predicting Heart Acceptance for Transplant. Developed by Dr. Wayda in collaboration with Stanford Health Care cardiologist Dr. Kiran Khush, the web-based platform utilizes 20 distinct donor characteristics to estimate the probability of organ acceptance based on historical national data. This tool is designed to provide immediate context, allowing a surgical team to see how a specific donor compares to thousands of previous successful transplants, thereby reducing the likelihood that a viable heart is rejected due to perceived outliers in the donor's medical history.

Objective Analysis of Cardiac Imaging

A secondary technological advancement involves AI-assisted interpretation of echocardiograms, which are essential for assessing a donor heart's ejection fraction and overall function. Dr. Wayda noted that manual interpretation of these tests is notoriously subjective and prone to variation between different clinicians. AI-based readings have demonstrated a higher level of consistency, aligning more closely with expert interpretations than standard hospital reads. By providing an automated "second opinion," this technology helps prevent clinicians from "anchoring" on a single negative variable, such as a donor being over the age of 50, which might otherwise lead to the unnecessary rejection of a healthy organ.