ArticleEcho research and practice2025
Can automation and artificial intelligence reduce echocardiography scan time and ultrasound system interaction?
Article in Echo research and practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- The diagnostic accuracy of left ventricular ejection fraction assessment between visual and artificial intelligence-based algorithms on bedside ultrasound.Cardiovascular ultrasound · 2026Article
- Reinventing the echocardiography workflow: from manual quantification to artificial intelligence-driven comprehensive interpretation.Journal of cardiovascular imaging · 2026Review
- Artificial intelligence in echocardiography: a position statement from the British Society of Echocardiography.Echo research and practice · 2026Review
- Artificial Intelligence and Digital Technology in Cardiovascular Imaging: A Narrative Review.Biotech (Basel (Switzerland)) · 2026Review
- Development and Validation of Echocardiography Artificial Intelligence Models: A Narrative Review.Journal of clinical medicine · 2025Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe number of patients referred for and requiring a transthoracic echocardiogram (TTE) has increased over the years resulting in more cardiac sonographers reporting work related musculoskeletal pain. We sought to determine if a scanning protocol that replaced conventional workflows with advanced technologies such as multiplane imaging, artificial intelligence (AI) and automation could be used to optimise conventional workflows and potentially reduce ergonomic risk for cardiac sonographers. The aim was to assess whether this alternate protocol could reduce active scanning time as well as interaction with the ultrasound machine compared to a standard echocardiogram without a reduction in image quality and interpretability. METHOD AND
resultsVolunteer participants were recruited for a study that comprised of two TTE's with separate protocols. Both were clinically complete, but Protocol A combined automation, AI assisted acquisition and measurement, simultaneous and multiplane imaging whilst Protocol B reflected a standard scanning protocol without these additional technologies. Keystrokes were significantly reduced with the advanced protocol as compared to the typical protocol (230.9 ± 24.2 vs. 502.8 ± 56.2; difference 271.9 ± 61.3, p < 0.001). Furthermore, there was a reduction in scan time with protocol A compared to protocol B the standard TTE protocol (13.4 ± 2.3 min vs. 18.0 ± 2.6 min; difference 4.6 ± 2.9 min, p < 0.001) as well as a decrease of approximately 27% in the time the sonographers were required to reach beyond a neutral position on the ultrasound console.
conclusionsA TTE protocol that embraces modern technologies such as AI, automation, and multiplane imaging shows potential for a reduction in ultrasound keystrokes and scan time without a reduction in quality and interpretability. This may aid a reduction in ergonomic workload as compared to a standard TTE.
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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.