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dc.contributor.authorOlaisen, Sindre Hellum
dc.contributor.authorSmistad, Erik
dc.contributor.authorEspeland, Torvald
dc.contributor.authorHu, Jieyu
dc.contributor.authorPasdeloup, David Francis Pierre
dc.contributor.authorØstvik, Andreas
dc.contributor.authorAakhus, Svend
dc.contributor.authorRösner, Assami
dc.contributor.authorMalm, Siri
dc.contributor.authorStylidis, Michael
dc.contributor.authorHolte, Espen
dc.contributor.authorGrenne, Bjørnar Leangen
dc.contributor.authorLøvstakken, Lasse
dc.contributor.authorDalen, Håvard
dc.date.accessioned2024-02-05T12:05:15Z
dc.date.available2024-02-05T12:05:15Z
dc.date.issued2023-10-26
dc.description.abstractAims - Echocardiography 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.<p> <p>Methods and results - Fully 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.<p> <p>Conclusion - The software reduced the time taken to perform and volumetrically analyse routine echocardiograms without a decrease in accuracy compared with experts.en_US
dc.identifier.citationOlaisen SH, Smistad E, Espeland T, Hu J, Pasdeloup DFP, Østvik A, Aakhus S, Rösner A, Malm S, Stylidis S, Holte E, Grenne BL, Løvstakken L, Dalen HD. Automatic measurements of left ventricular volumes and ejection fraction by artificial intelligence: clinical validation in real time and large databases. European Heart Journal-Cardiovascular Imaging. 2023
dc.identifier.cristinIDFRIDAID 2190780
dc.identifier.doi10.1093/ehjci/jead280
dc.identifier.issn2047-2404
dc.identifier.issn2047-2412
dc.identifier.urihttps://hdl.handle.net/10037/32842
dc.language.isoengen_US
dc.publisherOxford University Pressen_US
dc.relation.journalEuropean Heart Journal-Cardiovascular Imaging
dc.relation.projectIDNorges forskningsråd: 10.1093/ehjci/jead280
dc.rights.holderCopyright 2023 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0en_US
dc.rightsAttribution-NonCommercial 4.0 International (CC BY-NC 4.0)en_US
dc.titleAutomatic measurements of left ventricular volumes and ejection fraction by artificial intelligence: clinical validation in real time and large databasesen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
Except where otherwise noted, this item's license is described as Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)