A study published on June 23 in collaboration with UT and Yale researchers developed an artificial intelligence tool capable of performing and analyzing the heart using echocardiography. 

The app, PanEcho, can analyze echocardiograms, or pictures of the heart, using ultrasounds. The tool was developed and trained on nearly one million echocardiographic videos. It can perform 39 echocardiographic tasks and accurately detect conditions such as systolic dysfunction and severe aortic stenosis.

“Our teammates helped identify a total of 39 key measurements and labels that are part of a complete echocardiographic report — basically what a cardiologist would be expected to report on when they’re interpreting an exam,” said Gregory Holste, an author of the study and a doctoral candidate in the Department of Electrical and Computer Engineering. “We train the model to predict those 39 labels. Once that model is trained, you need to evaluate how it performs across those 39 tasks, and we do that through this robust multi site validation.” 

Holste said out of the functions PanEcho has, one of the most impressive is its ability to measure left ventricular ejection fraction, or the proportion of blood the left ventricle of the heart pumps out, far more accurately than human experts. Additionally, Holste said PanEcho can analyze the heart as a whole, while humans are limited to looking at the heart from one view at a time. 

“What is most unique about PanEcho is that it can do this by synthesizing information across all available views, not just curated single ones,” Holste said. “PanEcho integrates information from the entire exam — from multiple views of the heart to make a more informed, holistic decision about measurements like ejection fraction.” 

PanEcho is available for open-source use to allow researchers to use and experiment with the tool for future studies. Holste said the team has already received emails from people trying to “fine-tune” the application for different uses. 

“We know that other researchers are working on adapting PanEcho to work on pediatric scans, and this is not something that PanEcho was trained to do out of the box,” Holste said. “But, because it has seen so much data, it can fine-tune and adapt to that domain very quickly. (There are) very exciting possibilities for future research.”