Deep Learning for Improved Precision and Reproducibility of Left Ventricular Strain in Echocardiography: A Test-Retest Study

作者：Ivar Mjåland Salte, Andreas Østvik, Sindre Hellum Olaisen, Sigve Karlsen, Thomas Dahlslett, Erik Smistad, Torfinn Eriksen‐Volnes, Harald Brunvand, Kristina Hermann Haugaa, Thor Edvardsen, Håvard Dalen, Lasse Løvstakken, Bjørnar Leangen Grenne · 发表于：Journal of the American Society of Echocardiography · 年份：2023 · DOI：10.1016/j.echo.2023.02.017 · 被引用次数：47 · 研究领域：Cardiovascular Function and Risk Factors、Pulmonary Hypertension Research and Treatments、Elasticity and Material Modeling

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 inter...