Health professionals with no prior ultrasound training successfully performed 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 study, part of the larger RURAL (Risk Underlying Rural Areas Longitudinal) study, suggests a potential solution to the shortage of imaging specialists in rural areas.
The research, which will be presented in Chicago from Nov. 6-9, involved 4,597 volunteer participants in 10 rural counties across Alabama, Kentucky, Louisiana and Mississippi. Fourteen non-sonographers—nurses, nursing assistants and CT technicians—completed a two-hour training in AI-guided ultrasound. Using real-time AI software, they captured heart images in a mobile health unit. The scans were then reviewed by experts at the Duke Clinical Research Institute Imaging Core Laboratory.
Results showed that 98% of scans included all six standard echocardiography views required by the study protocol, and more than 99% were rated adequate for measurements by core lab experts. Diagnostic-quality images ranged from 77% to 94% for individual views. Scans were completed within the 15-minute target 81% of the time, with a median time of 9.5 minutes. Critical findings, such as reduced ejection fraction, were identified in 133 scans, and 99% of these 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 importance of this approach is underscored by the limited access to specialized care in rural America. "1 in 5 Americans lives in a rural area, which limits their access to critical diagnostic testing and specialty care," said Lee H. Schwamm, M.D., FAHA, a member of the American Heart Association's volunteer committee on AI and Technology Innovation. "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."
Echocardiography uses ultrasound to provide live, moving images of the heart's structure and function. According to the American Heart Association, the test can be ordered for various heart conditions, including heart murmurs, damaged valves, unexplained chest pain, congenital heart defects, and a history of heart attack or stroke.
The study has limitations, including no direct comparison between sonographer-acquired and AI-guided non-sonographer images, and the use of only one software brand and one core laboratory. Results may not be generalizable to non-rural populations or settings outside a core-lab-supported research environment. The findings are considered preliminary until published in a peer-reviewed journal.
This research adds to the growing body of evidence on AI in cardiovascular care, following earlier American Heart Association releases such as New guidance offered for responsible AI use in health care and Artificial intelligence-enhanced ECGs may speed heart failure diagnosis and treatment. For more details, see the release link and the abstract poster MDP2290.
