Key result
AI-enabled handheld ultrasound identifies reduced LVEF with ~90% accuracy vs. standard echocardiography.
Why the study?
Despite growing clinical uptake of AI-enabled handheld ultrasound devices to streamline cardiac evaluation, their diagnostic accuracy in determining reduced LVEF, particularly by novice operators and in real-world clinical settings, had not been comprehensively established.
Do commercially available AI-enabled handheld ultrasound devices accurately identify reduced left ventricular ejection fraction compared with standard transthoracic echocardiography in adult patients?
Meta-Analysis (n=2,879)
Do commercially available AI-enabled handheld ultrasound devices accurately identify reduced left ventricular ejection fraction compared with standard transthoracic echocardiography in adult patients?
AI-enabled handheld ultrasound devices demonstrate high overall accuracy (90%) and specificity (93%) for identifying reduced LVEF compared to standard TTE, supporting their utility as screening and triage tools despite substantial inter-study heterogeneity.
Supports point-of-care screening for reduced LVEF; extends evidence for AI-enabled handheld ultrasound in heart failure pathways.
Introduction Transthoracic echocardiography (TTE) underpins the diagnosis, phenotyping and subsequent management of heart failure (HF). However, access to high-quality cardiac imaging remains inequitable. Globally, workforce shortages, rising HF prevalence, and increasing service demand contribute to diagnostic delays and variation in care.1-2 Artificial intelligence (AI)-enabled handheld ultrasound devices (HUDs) have emerged as a potential solution, offering the possibility of streamlining or decentralising cardiac evaluation. Despite growing clinical uptake, the diagnostic accuracy of AI-enabled HUDs, particularly when used by novice operators and in real-world clinical settings, has not been comprehensively established. Purpose We conducted a systematic review and meta-analysis to determine the diagnostic accuracy of commercially available AI-enabled HUD compared with TTE in determining reduced left ventricular ejection fraction (LVEF). Methods The protocol was registered with PROSPERO. We searched PubMed, MEDLINE, Embase, and CENTRAL from inception to 1 February 2026 for studies comparing AI-enabled HUDs with standard echocardiography in adult patients. Two reviewers independently screened and extracted data; studies were included only if 2×2 confusion matrices could be derived for AI-enabled HUD versus TTE. Where this was not possible, but the study appeared potentially relevant, we made requests to corresponding authors. Risk of bias and applicability were assessed using QUADAS-2. All statistical analyses were performed using STATA 19 (StataCorp. 2025. Stata Statistical Software: Release 19. College Station, TX: StataCorp LLC.). We pooled diagnostic accuracy using random-effects and hierarchical summary receiver operating characteristic (HSROC), reported 95% confidence intervals and I², and analysed subgroups by operator experience and LVEF cut-off. Results Seventeen studies including 2,879 examinations were included. There was variability across studies in the threshold for reduced LVEF used for diagnostic accuracy analyses. The overall sensitivity was 0.80 (0.74 – 0.87, I2 = 86.34%), specificity 0.93 (0.91 – 0.95, I2 = 82.24%), PPV 0.80 (0.74 – 0.86, I2 = 85.85%), NPV 0.91 (0.87 – 0.95, I2 = 97.02%), and accuracy 0.90 (0.87 – 0.93, I2 = 90.86%). Sensitivity was higher for novices (0.91 [0.85–0.98]) compared to experts (0.70 [0.60–0.81]). Overall, AI correctly classified examinations most commonly when utilising 30% thresholds (accuracy 0.96 [0.95 – 0.98]); it performed worst in 40% thresholds (accuracy 0.85 [0.76 – 0.94], I2 = 96.19%). Conclusion AI-enabled HUD demonstrated excellent performance for identifying reduced LVEF, supporting its use as a screening and triage tool. However, substantial inter-study heterogeneity and operator-dependent differences indicate performance is context-specific and should be interpreted with training, scan protocol, and manufacturer information.HSROC CurvePRISMA Flow Chart
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Winarta et al. (2026) conducted a meta-analysis in Reduced left ventricular ejection fraction (LVEF) / Heart failure (n=2,879). AI-enabled handheld ultrasound devices (HUDs) vs. Standard transthoracic echocardiography (TTE) was evaluated on Diagnostic accuracy for determining reduced left ventricular ejection fraction (LVEF) (Accuracy 0.90 (Sensitivity 0.80, Specificity 0.93), 95% CI 0.87-0.93). AI-enabled handheld ultrasound demonstrated 0.90 accuracy (95% CI 0.87–0.93), 0.80 sensitivity, and 0.93 specificity compared with standard echocardiography for identifying reduced LVEF.
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