Health professionals without prior ultrasound training successfully captured diagnostic-quality heart scans in rural communities using artificial intelligence (AI) guidance and off-site expert review, according to preliminary research presented at the American Heart Association’s Scientific Sessions 2026. The findings suggest a scalable model for delivering echocardiography—ultrasound imaging of the heart—to areas where imaging specialists and equipment are scarce, and for including rural populations in cardiovascular research.
The study, part of the larger RURAL (Risk Underlying Rural Areas Longitudinal) study, equipped nurses, nursing assistants, and CT technologists with a two-hour training curriculum and real-time AI software that helps users obtain standard heart views. Fourteen non-sonographers performed scans on 4,597 participants across 10 rural counties in Alabama, Kentucky, Louisiana, and Mississippi using a mobile health unit. The AI tool provided live guidance, and images were reviewed remotely by experts at the Duke Clinical Research Institute Imaging Core Laboratory.
Results were striking: 98% of scans included 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 for individual views ranged from 77% to 94%, and scans were completed within the 15-minute target window 81% of the time, with a median of 9.5 minutes. Critical findings, such as an ejection fraction below 50%, were identified in 133 scans, and 99% of those results were returned to participants within three days.
“We were surprised at how quickly and well the nurses and CT technologists who had never done a heart ultrasound were able to adapt to this technology and produce quality images for review by experts,” 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 are significant for rural health equity. 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.” Schwamm was not involved in the study.
Echocardiography is a key tool for diagnosing heart murmurs, valve damage, congenital defects, and other conditions, as described by the American Heart Association. However, its delivery in rural settings has been limited by a shortage of sonographers and imaging specialists. The study’s approach could help overcome these barriers by decentralizing image acquisition while maintaining quality through AI and remote expert oversight.
The research has limitations: it lacked a direct comparison with sonographer-acquired images, used only one AI software brand, and involved a single core laboratory. Results may not generalize to non-rural populations or settings without core-lab support. The study also did not assess whether returning results influenced participants’ care. The findings are considered preliminary until published in a peer-reviewed journal and were presented at Scientific Sessions 2026, a global forum for cardiovascular science. The abstract is available as abstract poster MDP2290. The American Heart Association has also issued new guidance for responsible AI use in health care and previously reported that artificial intelligence-enhanced ECGs may speed heart failure diagnosis and treatment. More details are available in the release link.
