ArticleEuropean heart journal. Imaging methods and practice2026
The impact of heart rate on echocardiographic measures of left ventricular function: novel insights facilitated by deep learning.
Article in European heart journal. Imaging methods and practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Deep Learning for Cardiac Wall Motion Analysis: A Review of Methods, Challenges, and Clinical Applications.Annals of biomedical engineering · 2026Review
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8 authors.
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Abstract
Background: Echocardiographic measurements of the left ventricle (LV) are fundamental in diagnosing and monitoring cardiac disease. Still, current understanding of how heart rate influences these measurements is incomplete. We aimed to explore the relationship between heart rate and LV global longitudinal strain (GLS), ejection fraction (LVEF), end-diastolic (LVEDV), and end-systolic volumes (LVESV), using atrial pacing and a transparent multi-step deep learning (DL)-based method for fully automated measurements. Methods and results: Fifty participants with permanent pacemakers were enrolled. Heart rate was increased by atrial pacing in increments of 10 beats/min, from 50 to 140 beats/min, with echocardiographic 10-beat cine-loops recorded at each step. A DL-based method was utilized to measure GLS, LVEF, LVEDV, and LVESV at all levels.A total of 10 161 heart cycles were analysed, with 97% feasibility. As heart rate increased, all LV measures displayed significant and near-linear reductions. From 60 to 140 beats/min, GLS decreased by 32% (95% CI: 19-44%), LVEF by 33% (95% CI: 19-47%), LVEDV by 31% (95% CI: 19-43%), and LVESV by 10% (95% CI: -5% to 24%). Processing time per cardiac cycle was 1.3 (0.4) s, corresponding to 3.7 h for the entire dataset. Conclusion: Heart rate significantly influences echocardiographic measures of LV function and volume, emphasizing the necessity of incorporating heart rate into clinical interpretation and reporting of echocardiographic measurements. This study further demonstrates the potential of DL to advance cardiovascular research by enabling rapid, accurate, and reproducible analyses, previously unachievable due to the inherent constraints of manual measurements.
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