Improving structural heart disease screening: AI-ECG and novice AI-guided focused cardiac ultrasound
Structural heart disease (SHD) causes substantial morbidity, yet early detection is limited. In this prospective study, AI-enhanced ECG and AI-guided focused cardiac ultrasound (AI-FoCUS) were assessed for detecting SHD (left ventricular EF < 40%, ≥moderate aortic stenosis, hypertrophic cardiomyopathy, or cardiac amyloidosis) in 995 adults against comprehensive echocardiography performed within 30 min of AI-FoCUS. Nine complete novices used handheld ultrasound (Philips Lumify) with real-time AI guidance (UltraSight) with images interpreted by blinded experts. AI-FoCUS was feasible in 97.3%. Prevalence was 5.0% for EF < 40%, 3.5% for ≥moderate aortic stenosis, and 8.8% for hypertrophic cardiomyopathy or amyloidosis. AI-ECG alone yielded NPV 95.8% but PPV 29.6%, limiting standalone screening. AI-FoCUS alone achieved PPV 95.4% and NPV 98.0%, however requires imaging in all. A two-step strategy (positive AI-ECG followed by AI-FoCUS) maintained high PPV/NPV (96.1%/95.6%) but limited FoCUS imaging to 47%.In this echo referral cohort, novice AI-guided FoCUS acquisition with blinded expert interpretation was feasible and accurate for detecting selected SHD phenotypes. A two-step AI-ECG then AI-FoCUS strategy reduced FoCUS utilization, but lowered sensitivity compared with AI-FoCUS for all. However, both FoCUS-based strategies were superior to AI-ECG based screening alone. This work requires further assessment and validation in lower prevalence populations.
Authors
- Sorin V. Pislaru (ORCID: https://orcid.org/0000-0002-5256-3150)
- Jeffrey G. Malins (ORCID: https://orcid.org/0000-0002-2932-256X)
- Jeremy J. Thaden (ORCID: https://orcid.org/0000-0003-4489-2349)
- Jwan A. Naser (ORCID: https://orcid.org/0000-0002-6210-7669)
- Conor J. Kane
- Jessica Zacher
- Christie Greason
- Timothy J. Poterucha (ORCID: https://orcid.org/0000-0001-7284-3937)
- Jared G. Bird
- Mayari A. Gulati
- Francisco Lopez-Jimenez
- Gal Tsaban
- Jude Kovac
- Zachi I. Attia
- Méabh M. Killalea
- Maria M. Crestanello
- Eunjung Lee
- Garvan C. Kane
- Daniel A. Schonfeld
- Paul A. Friedman
- Jordan Borgeson
Institutions
- Mayo Clinic in Arizona (US)
- Mayo Clinic in Florida (US)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2026-06-09
- DOI
- https://doi.org/10.1038/s41746-026-02856-3
- Primary Topic
- Ultrasound in Clinical Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Mayo Clinic
- University College Dublin