11/16/2024 | Press release | Distributed by Public on 11/16/2024 16:00
Research Highlights:
Embargoed until 3:55 p.m. CT/4:55 p.m. ET, Saturday, Nov. 16, 2024
CHICAGO, Nov. 16, 2024 - Using an artificial intelligence program to read echocardiograms may reduce the wait time for results and help lead to more timely medical care, according to late-breaking science presented today at the American Heart Association's Scientific Sessions 2024. The meeting, Nov. 16-18, 2024, in Chicago, is a premier global exchange of the latest scientific advancements, research and evidence-based clinical practice updates in cardiovascular science.
In this study, an artificial intelligence program called PanEcho was tested on its ability to interpret echocardiography videos independently. An echocardiogram is a type of heart imaging that allows doctors to see heart structure and function, and it is used to diagnose and treat heart conditions.
PanEcho builds on previous AI uses in cardiology that were limited to single views of the heart and disease-specific criteria. The research team developed a novel AI system capable of comprehensive reporting for all major findings from any set of echocardiography videos.
"PanEcho has the potential to be used in simplified, AI-assisted screening echocardiograms," said Gregory Holste, M.S.E., a researcher with the Cardiovascular Data Science (CarDS) Lab at the Yale School of Medicine in New Haven, Connecticut, who presented the study. "In settings where expert readers may not be readily accessible, PanEcho could rapidly rule out abnormalities that would otherwise require urgent referral."
PanEcho's diagnostic performance was evaluated using a standard measurement of accuracy for diagnostic tests: the area under the receiver operating characteristic curve (AUC). A 100% accurate test has an AUC of 1, and an uninformative test (e.g., random guessing) has an AUC of 0.5.
The study found:
PanEcho was also evaluated on its ability to estimate continuous echocardiographic parameters, using mean absolute error, which is a measurement of the average distance between predicted values and actual values, meaning the smaller the distance, the more accurate the prediction. When evaluated in 21 tasks, PanEcho had a median normalized mean absolute error of 0.13.
PanEcho demonstrated accuracy when quantifying left ventricle dimensions and function, including:
These measurements are critical to accurately assess left ventricular structure and function, a major aspect of heart health.
"This work represents an advance in AI for echocardiography, and we hope that the public release of our AI model will encourage the research community to move toward flexible, multi-task, multi-view approaches for echocardiogram interpretation," he added.
PanEcho is limited by its retrospective validation in previously acquired data. The next step is to prospectively validate its application in real-world patient care environments to provide further insights into its clinical viability, Holste said. "It also needs to be evaluated for use with portable echocardiogram machines used in emergency rooms and smaller medical clinics, where there is potential for the biggest positive impact with AI tools."
Study background, design and details:
The principal investigator of this study was Rohan Khera, M.D., M.S., head of the CarDS Lab at Yale School of Medicine. The work was led by co-first authors and CarDS Lab members, Gregory Holste, M.S.E., and Evangelos Oikonomou, M.D., D.Phil. Additional co-authors, disclosures and funding sources are listed in the abstract.
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