dc.contributor.author | Salte, Ivar Mjåland | |
dc.contributor.author | Østvik, Andreas | |
dc.contributor.author | Olaisen, Sindre Hellum | |
dc.contributor.author | Karlsen, Sigve | |
dc.contributor.author | Dahlslett, Thomas | |
dc.contributor.author | Smistad, Erik | |
dc.contributor.author | Eriksen-Volnes, Torfinn Kirknes | |
dc.contributor.author | Brunvand, Harald | |
dc.contributor.author | Haugaa, Kristina Ingrid Helena Hermann | |
dc.contributor.author | Edvardsen, Thor | |
dc.contributor.author | Dalen, Håvard | |
dc.contributor.author | Løvstakken, Lasse | |
dc.contributor.author | Grenne, Bjørnar Leangen | |
dc.date.accessioned | 2023-09-20T13:11:38Z | |
dc.date.available | 2023-09-20T13:11:38Z | |
dc.date.created | 2023-05-02T09:09:12Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Journal of the American Society of Echocardiography. 2023, 36 (7), 788-799. | en_US |
dc.identifier.issn | 0894-7317 | |
dc.identifier.uri | https://hdl.handle.net/11250/3090840 | |
dc.description.abstract | Aims: Assessment of left ventricular (LV) function by echocardiography is hampered by modest test-retest reproducibility. A novel artificial intelligence (AI) method based on deep learning provides fully automated measurements of LV global longitudinal strain (GLS) and may improve the clinical utility of echocardiography by reducing user-related variability. The aim of this study was to assess within-patient test-retest reproducibility of LV GLS measured by the novel AI method in repeated echocardiograms recorded by different echocardiographers and to compare the results to manual measurements.
Methods: Two test-retest data sets (n = 40 and n = 32) were obtained at separate centers. Repeated recordings were acquired in immediate succession by 2 different echocardiographers at each center. For each data set, 4 readers measured GLS in both recordings using a semiautomatic method to construct test-retest interreader and intrareader scenarios. Agreement, mean absolute difference, and minimal detectable change (MDC) were compared to analyses by AI. In a subset of 10 patients, beat-to-beat variability in 3 cardiac cycles was assessed by 2 readers and AI.
Results: Test-retest variability was lower with AI compared with interreader scenarios (data set I: MDC = 3.7 vs 5.5, mean absolute difference = 1.4 vs 2.1, respectively; data set II: MDC = 3.9 vs 5.2, mean absolute difference = 1.6 vs 1.9, respectively; all P < .05). There was bias in GLS measurements in 13 of 24 test-retest interreader scenarios (largest bias, 3.2 strain units). In contrast, there was no bias in measurements by AI. Beat-to-beat MDCs were 1.5, 2.1, and 2.3 for AI and the 2 readers, respectively. Processing time for analyses of GLS by the AI method was 7.9 ± 2.8 seconds.
Conclusion: A fast AI method for automated measurements of LV GLS reduced test-retest variability and removed bias between readers in both test-retest data sets. By improving the precision and reproducibility, AI may increase the clinical utility of echocardiography. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Deep Learning for Improved Precision and Reproducibility of Left Ventricular Strain in Echocardiography: A Test-Retest Study | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | en_US |
dc.rights.holder | Copyright 2023 by the American Society of Echocardiography. Published by Elsevier Inc. | en_US |
dc.source.pagenumber | 788-799 | en_US |
dc.source.volume | 36 | en_US |
dc.source.journal | Journal of the American Society of Echocardiography | en_US |
dc.source.issue | 7 | en_US |
dc.identifier.doi | 10.1016/j.echo.2023.02.017 | |
dc.identifier.cristin | 2144589 | |
dc.relation.project | Norges forskningsråd: 237887 | en_US |
dc.relation.project | Norges forskningsråd: 309762 | en_US |
dc.relation.project | Helse Sør-Øst RHF: 2017207 | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 2 | |