Chinese researchers investigate use of AI-assisted ultrasound by general practitioners to detect carotid plaque

Applications of AI


Providence, Rhode Island, May 27, 2026 /PRNewswire/ — In a new feasibility study published in the Annals of Family Medicine, general practitioners (GPs) in China were able to accurately detect carotid artery plaque (an indicator of cardiovascular disease) in high-risk patients using AI-assisted portable ultrasound. However, the authors caution that more extensive testing is needed before this approach can be widely adopted, as diagnostic performance was inconsistent across participating general practitioners.

Key findings from a study investigating general practitioners' ability to screen for carotid plaque using AI-enhanced point-of-care ultrasound after systematic training. Published in Annals of Family Medicine, May/June 2026.
Key findings from a study investigating general practitioners’ ability to screen for carotid plaque using AI-enhanced point-of-care ultrasound after systematic training. Published in Annals of Family Medicine, May/June 2026.

Carotid plaques are accumulations in the arterial walls of the neck that are associated with the development of atherosclerotic cardiovascular disease. Point-of-care ultrasound, also known as POCUS, is a new tool used in primary care. Artificial intelligence (AI) capabilities have recently been added to POCUS to improve image quality and diagnostic accuracy. This study investigated whether AI-assisted POCUS, combined with a training program, could help general practitioners in China use POCUS to screen for carotid plaque in their community clinics.

This study was conducted in Shanghai, China. Seven GPs completed a training program that combined classroom instruction with hands-on practice using AI-assisted POCUS. They recruited 169 patients at high risk for atherosclerotic cardiovascular disease from four community health centers during routine outpatient visits and offered free carotid plaque testing. Each patient was scanned by both a general practitioner and a senior ultrasound specialist. The device uses AI software to analyze ultrasound images in real time and alerts the operator with an on-screen marker when it detects potential plaque. Two senior ultrasound specialists independently reviewed all archived records and images to determine who had carotid plaque. This served as a benchmark for evaluating GP findings.

When examining the presence or absence of plaque across patients, general practitioners correctly identified about 87% of patients with plaque and correctly excluded about 91% of patients without plaque. Their findings showed a high level of agreement with senior ultrasound professional benchmarks. Among vessels in which plaque was confirmed, missed cases were concentrated at the bifurcation point where the carotid artery bifurcates (18.6%, 22/118). The authors suggest that this may be due to limitations of the AI ​​systems themselves in the field, or gaps in how GPs incorporate AI feedback into their workflows. Misidentifying plaques in patients who actually did not have them was less common.

Each scan took about eight minutes to complete, but the researchers acknowledged that this may be difficult to extrapolate to typical GP appointments, where consultation times tend to be short. They suggest that this approach may be suitable, at least initially, for more focused settings such as stroke screening clinics, community health outreach campaigns, and home care programs. The authors describe this as the first study of its kind to test structured POCUS training for Chinese general practitioners in a real clinical setting, including AI assistance.

“Wide implementation of this AI-assisted POCUS approach will require standardized operator-specific training modules and further validation in a larger and more heterogeneous general practitioner cohort to ensure uniform and reliable performance,” the authors write.

Cited article:

Diagnostic performance of general practitioners in carotid plaque detection using AI-enhanced point-of-care ultrasound after systematic training

Liu Xiaochun, MD. Xicheng Yao, Bachelor of Science. Dr. Huayang; and Dr. Zhigang Pan

Funding: This study was supported by the Shanghai Municipal Health Commission Key Supported Discipline Construction (General Practice 2023 ZDFC0401).

Family medicine annual report is an open-access, peer-reviewed, indexed research journal that provides an interdisciplinary forum for new evidence-based information impacting the field of primary care. Released in May 2003, Family medicine annual report is sponsored by six family medicine organizations, including the American College of Family Physicians, the American Board of Family Medicine, the Association of Family Medicine Teachers, the Society of Family Medicine, the Association of Family Medicine Training Directors, and the North American Primary Care Research Group. Family medicine annual report Published online six times a year, it is free of charge and contains original research in the clinical, biomedical, social, and health services fields, as well as methodological and theoretical contributions, and selected reviews, essays, and editorials. The complete editorial content and interactive discussion group for each published article can be accessed free of charge through the journal’s website (www.AnnFamMed.org).

(PRNewsfoto/Annals of Family Medicine)
(PRNewsfoto/Annals of Family Medicine)
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