ArticleEuropean heart journal. Cardiovascular Imaging2024
Automatic measurements of left ventricular volumes and ejection fraction by artificial intelligence: clinical validation in real time and large databases.
Article in European heart journal. Cardiovascular Imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.
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Who cites it
38 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.
- Practical guidance for echocardiography for cancer therapy-related cardiac dysfunction: 2026 focused update.Journal of echocardiography · 2026Guideline
- Real-time deep learning-based image guiding and automated left ventricular measurements to reduce test-retest variability.Open heart · 2025Trial
- Automated echocardiographic measurements for longitudinal monitoring of ATTR cardiomyopathy: agreement and repeatability analysis.The international journal of cardiovascular imaging · 2026Article
- The diagnostic accuracy of left ventricular ejection fraction assessment between visual and artificial intelligence-based algorithms on bedside ultrasound.Cardiovascular ultrasound · 2026Article
- Dual-flow convolutional neural network for automatic measurement of left ventricular ejection fraction and global longitudinal strain in echocardiography.PLOS digital health · 2026Article
- Artificial Intelligence-Enhanced Cardiac Point-of-Care Ultrasound: A Prospective Single-Arm Study.Mayo Clinic proceedings. Digital health · 2026Article
- Smarter FoCUS: AI-guided focused cardiac ultrasound enables novice detection of left ventricular dysfunction.European heart journal. Digital health · 2026Article
- Fully automated artificial intelligence-based echocardiographic analysis substantially reduces workflow time while preserving measurement accuracy: a pilot study.Journal of cardiovascular imaging · 2026Article
- Artificial intelligence across the cardiovascular diagnostic pathway: a case-based narrative review.Cardiovascular diagnosis and therapy · 2026Review
- Reproducibility of echocardiographic measurements of left ventricular systolic function: a systematic review and meta-analysis comparing artificial intelligence and clinician estimates.European heart journal. Digital health · 2026Review
- Artificial Intelligence and Digital Technology in Cardiovascular Imaging: A Narrative Review.Biotech (Basel (Switzerland)) · 2026Review
- Artificial intelligence-enhanced echocardiography in cardiovascular disease management.Nature reviews. Cardiology · 2026Review
- A Multimodular AI Algorithm for Automated Assessment of Left Ventricular Function in Ischemic Heart Disease: Ejection Fraction, Wall Motion, and Regional Myocardial Segmentation.Balkan medical journal · 2026Article
- Artificial intelligence implementation in automated heart chambers quantification during pharmacological stress echocardiography.European heart journal. Digital health · 2026Article
- The impact of heart rate on echocardiographic measures of left ventricular function: novel insights facilitated by deep learning.European heart journal. Imaging methods and practice · 2026Article
- Use of artificial intelligence for detecting left ventricular dysfunction and predicting incident heart failure risk.ESC heart failure · 2025Review
- A deep learning-based pipeline for large-scale echocardiography data curation and measurements.European heart journal. Digital health · 2025Article
- Generative augmentations for improved cardiac ultrasound segmentation using diffusion models.Scientific reports · 2025Article
- How can common errors in left heart echocardiography be avoided? An expert proposalby the German Working Group of Cardiovascular Ultrasound.Clinical research in cardiology : official journal of the German Cardiac Society · 2025Review
- Artificial intelligence in the diagnosis and management planning of bicuspid aortic valvular disease: a case series.European heart journal. Case reports · 2025Article
Corrections and comments
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Authors and funding
14 authors at 3 institutions in 1 country.
Funding
Abstract
aimsEchocardiography is a cornerstone in cardiac imaging, and left ventricular (LV) ejection fraction (EF) is a key parameter for patient management. Recent advances in artificial intelligence (AI) have enabled fully automatic measurements of LV volumes and EF both during scanning and in stored recordings. The aim of this study was to evaluate the impact of implementing AI measurements on acquisition and processing time and test-retest reproducibility compared with standard clinical workflow, as well as to study the agreement with reference in large internal and external databases. METHODS AND
resultsFully automatic measurements of LV volumes and EF by a novel AI software were compared with manual measurements in the following clinical scenarios: (i) in real time use during scanning of 50 consecutive patients, (ii) in 40 subjects with repeated echocardiographic examinations and manual measurements by 4 readers, and (iii) in large internal and external research databases of 1881 and 849 subjects, respectively. Real-time AI measurements significantly reduced the total acquisition and processing time by 77% (median 5.3 min, P < 0.001) compared with standard clinical workflow. Test-retest reproducibility of AI measurements was superior in inter-observer scenarios and non-inferior in intra-observer scenarios. AI measurements showed good agreement with reference measurements both in real time and in large research databases.
conclusionThe software reduced the time taken to perform and volumetrically analyse routine echocardiograms without a decrease in accuracy compared with experts.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.