Hu Wan Yu, Yu Yan Cheng, Dai Li Ya, Li Shi Yan, Zhao Bo Wen
Department of Diagnostic Ultrasound & Echocardiography, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China.
Department of Ultrasonography, Affiliated Hospital of Hangzhou Normal University, Hangzhou, People's Republic of China.
J Ultrasound Med. 2021 May;40(5):953-962. doi: 10.1002/jum.15469. Epub 2020 Aug 28.
To explore the inter- and intra-observer reliability of Sonography-based Volume Computer Aided Diagnosis (SonoVCAD) in the display of 8 diagnostic planes of fetal echocardiography and to evaluate its efficiency.
Three-dimensional volume data sets of the 56 normal singleton fetuses were acquired from a 4-chamber view by using a volume probe. After processing the data sets by using SonoVCAD, 8 cardiac diagnostic planes were displayed automatically. Three doctors with different experiences of performing fetal echocardiography evaluated each diagnostic plane and the success rates of 8 diagnostic planes were calculated. Inter-observer and intra-observer reliabilities were estimated by Cohen's kappa statistics.
A total of 276 volume data sets acquired from the 56 normal fetuses were used for SonoVCAD analysis and display. The success rate of each diagnostic section was more than 90%, ranging from 90.6% to 99.6%. Among 276 volumes, 81.5% (225/276) of volumes were able to generate all 8 diagnostic views successfully. Moderate to substantial agreement (kappa, 0.509-0.794) was found between 2 less experienced operators. Moderate to near-perfect agreement (kappa, 0.439-0.933) was found between an expert and 2 less experienced sonographers. Intra-observer reliability was substantial to near-perfect (kappa, 0.602-0.903). The efficiency of SonoVCAD was assessed. The expert spent less time than 2 less experienced examiners (P < 0.001) but no significant difference was found between 2 less experienced examiners (P = 0.176). Besides, SonoVCAD consumed significantly less time than 2-dimensional ultrasound (P < 0.001).
SonoVCAD can significantly improve the success rates of 8 diagnostic planes in fetal echocardiography with low operator dependency, good reproducibility and high efficiency.
探讨基于超声的容积计算机辅助诊断(SonoVCAD)在胎儿超声心动图8个诊断平面显示中的观察者间及观察者内可靠性,并评估其效率。
使用容积探头从四腔心切面获取56例正常单胎胎儿的三维容积数据集。使用SonoVCAD处理数据集后,自动显示8个心脏诊断平面。三名具有不同胎儿超声心动图检查经验的医生对每个诊断平面进行评估,并计算8个诊断平面的成功率。通过Cohen's kappa统计量估计观察者间和观察者内的可靠性。
共对56例正常胎儿获取的276个容积数据集进行SonoVCAD分析和显示。每个诊断切面的成功率均超过90%,范围为90.6%至99.6%。在276个容积中,81.5%(225/276)的容积能够成功生成所有8个诊断视图。经验较少的2名操作者之间存在中度至高度一致性(kappa,0.509 - 0.794)。一名专家与2名经验较少的超声检查人员之间存在中度至近乎完美的一致性(kappa,0.439 - 0.933)。观察者内可靠性为高度至近乎完美(kappa,0.602 - 0.903)。评估了SonoVCAD的效率。专家花费的时间比2名经验较少的检查人员少(P < 0.001),但2名经验较少的检查人员之间未发现显著差异(P = 0.176)。此外,SonoVCAD比二维超声消耗的时间显著减少(P < 0.001)。
SonoVCAD可显著提高胎儿超声心动图8个诊断平面的成功率,具有低操作者依赖性、良好的可重复性和高效率。