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Improving structural heart disease screening: AI-ECG and novice AI-guided focused cardiac ultrasound
Méabh M Killalea1, Jordan Borgeson1, Conor J Kane1
1Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
Insights
AI-guided focused cardiac ultrasound (AI-FoCUS) and AI-enhanced ECG show promise for detecting structural heart disease (SHD). A two-step approach reduced imaging needs while maintaining accuracy, outperforming AI-ECG screening alone.
Area of Science:
- Cardiology
- Artificial Intelligence
- Medical Imaging
Background:
- Structural heart disease (SHD) presents a significant health burden with limited early detection methods.
- Current diagnostic approaches can be resource-intensive and may not be widely accessible.
Purpose of the Study:
- To evaluate the feasibility and accuracy of AI-enhanced electrocardiogram (AI-ECG) and AI-guided focused cardiac ultrasound (AI-FoCUS) for detecting specific SHD phenotypes.
- To compare a two-step AI-ECG followed by AI-FoCUS strategy against standalone AI-FoCUS and AI-ECG screening.
Main Methods:
- A prospective study involving 995 adults, assessing AI-ECG and AI-FoCUS against comprehensive echocardiography.
- Novices utilized handheld ultrasound with real-time AI guidance (UltraSight), with images interpreted by blinded experts.
- SHD phenotypes included low ejection fraction, moderate aortic stenosis, hypertrophic cardiomyopathy, and cardiac amyloidosis.
Main Results:
- AI-FoCUS was feasible in 97.3% of cases.
- Standalone AI-FoCUS demonstrated high positive predictive value (PPV) of 95.4% and negative predictive value (NPV) of 98.0%.
- The two-step AI-ECG/AI-FoCUS strategy achieved high PPV (96.1%) and NPV (95.6%), reducing FoCUS utilization to 47% but lowering sensitivity compared to universal AI-FoCUS.
Conclusions:
- Novice-performed AI-guided FoCUS acquisition is feasible and accurate for detecting selected SHD phenotypes in an echo referral setting.
- A two-step AI-ECG then AI-FoCUS strategy effectively reduces the need for ultrasound imaging while maintaining high diagnostic performance.
- Both AI-FoCUS-based strategies significantly outperformed AI-ECG screening alone, highlighting the potential of AI in SHD detection.
Abstract:
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.
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