Evidence map›Paper›PMID 39045079›Full record

ArticleEuropean heart journal. Imaging methods and practice2023

Real-time guidance by deep learning of experienced operators to improve the standardization of echocardiographic acquisitions.

Sigbjorn Sabo, David Pasdeloup, Hakon Neergaard Pettersen, Erik Smistad, Andreas Østvik, Sindre Hellum Olaisen, Stian Bergseng Stølen, Bjørnar Leangen Grenne, Espen Holte, Lasse Lovstakken and 1 more

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European heart journal. Imaging methods and practice, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04580095 (Technology Revisiting Ultrasound Solutions of Tomorrow - Artificial Intelligence for Improved Echocardiography), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

NCT04580095 nacompletednot on this map

Technology Revisiting Ultrasound Solutions of Tomorrow - Artificial Intelligence for Improved Echocardiography

TypeinterventionalSponsorHelse Nord-Trøndelag HFRan2020 to 2021Enrolled88ConditionsHeart DiseasesArmsAI algorithm for apical foreshortening in echocardiography
3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Trial
  2. Article
  3. Diagnostic Tests for Stage B Heart Failure.Current cardiology reports · 2026
    Review
  4. Article
  5. Review
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Sigbjorn SaboDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, PO Box 8905, 7491 Trondheim, Norway.ORCID https://orcid.org/0000-0001-6906-5169
David PasdeloupDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, PO Box 8905, 7491 Trondheim, Norway.ORCID https://orcid.org/0000-0002-0160-1268
Hakon Neergaard PettersenDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, PO Box 8905, 7491 Trondheim, Norway.
Erik SmistadDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, PO Box 8905, 7491 Trondheim, Norway.ORCID https://orcid.org/0000-0002-7258-4709
Andreas ØstvikDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, PO Box 8905, 7491 Trondheim, Norway.ORCID https://orcid.org/0000-0003-3895-2683
Sindre Hellum OlaisenDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, PO Box 8905, 7491 Trondheim, Norway.ORCID https://orcid.org/0009-0005-7931-4145
Stian Bergseng StølenClinic of Cardiology, St.Olavs University Hospital, Prinsesse Kristinas gate 3, 7030 Trondheim, Norway.
Bjørnar Leangen GrenneDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, PO Box 8905, 7491 Trondheim, Norway.ORCID https://orcid.org/0000-0002-2984-6865
Espen HolteDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, PO Box 8905, 7491 Trondheim, Norway.ORCID https://orcid.org/0000-0002-8891-1372
Lasse LovstakkenDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, PO Box 8905, 7491 Trondheim, Norway.ORCID https://orcid.org/0000-0003-2474-9588
Havard DalenDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, PO Box 8905, 7491 Trondheim, Norway.ORCID https://orcid.org/0000-0003-1192-3663

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: Impaired standardization of echocardiograms may increase inter-operator variability. This study aimed to determine whether the real-time guidance of experienced sonographers by deep learning (DL) could improve the standardization of apical recordings. Methods and results: Patients ( Conclusion: Real-time guidance by DL improved the standardization of echocardiographic acquisitions by experienced sonographers. Future studies should evaluate the impact with respect to variability of measurements and when used by less-experienced operators. ClinicalTrialsgov Identifier: NCT04580095.

Indexed as

artificial intelligenceechocardiographymachine learningoperator feedbackreal time

Identifiers

PMID39045079
PMCPMC11195719

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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.