Health professionals without prior ultrasound training successfully performed quality heart scans in mobile units traveling to rural U.S. communities, according to preliminary research presented at the American Heart Association’s Scientific Sessions 2026. The approach, which combined real-time artificial intelligence (AI) guidance with off-site expert review, may help overcome longstanding barriers to heart imaging in underserved regions.
The study, part of the larger RURAL (Risk Underlying Rural Areas Longitudinal) study, enrolled 4,597 adults across 10 rural counties in Alabama, Kentucky, Louisiana, and Mississippi between November 2021 and June 2026. Fourteen non-sonographers—including nurses, nursing assistants, and CT technologists—completed a two-hour training curriculum on AI-guided ultrasound. The results were striking: 98% of scans captured all six standard echocardiography views required by the study protocol, and core laboratory experts rated more than 99% of studies as adequate for measurements. Diagnostic-quality images ranged from 77% to 94% for individual views, and 81% of scans were completed within the 15-minute target window, with a median time of 9.5 minutes.
“Echocardiography is one of the most useful tools we have in cardiovascular research; however, it has historically been very hard to deliver in rural communities,” said study author Sanjana Ravi, M.D., an internal medicine and pediatrics resident at Duke University School of Medicine. “With real-time AI guidance and a rigorous quality-control system behind it, a nurse or CT technologist in a mobile unit can produce heart images good enough for research and good enough to flag serious heart problems that need follow-up, bringing the imaging to the community rather than asking the community to travel to it.”
The implications for rural health equity are significant. According to Lee H. Schwamm, M.D., FAHA, a member of the American Heart Association’s volunteer committee on AI and Technology Innovation, “1 in 5 Americans lives in a rural area, which limits their access to critical diagnostic testing and specialty care. In this hybrid model, community-based non-experts were able to create a human-AI partnership with the acquisition software to enable the capture of echocardiogram images that could be read by off-site experts. This novel approach brings heart imaging to local communities and truly meets people where they are. If confirmed in further studies, this approach could serve as a model for other specialties and diagnostic modalities.”
Critical findings were identified in 133 scans, most commonly an ejection fraction below 50%, indicating reduced heart pumping function. Of these, 99% were returned to participants within three days, demonstrating the system’s ability to promptly flag serious conditions. The study authors note limitations, including the absence of a direct comparison with sonographer-acquired images, the use of a single software brand, and the involvement of only one core laboratory. The results may not be generalizable to non-rural populations or settings outside a core-lab-supported research framework, and the study did not evaluate whether returning results influenced participants’ care or health outcomes.
For more information on echocardiography, visit the American Heart Association’s echocardiography resource. The full abstract is available as abstract poster MDP2290, and additional details can be found in the release link. The research will be presented at Scientific Sessions 2026.
