Spitzer Ernest, Camacho Benjamin, Mrevlje Blaz, Brandendburg Hans-Jelle, Ren Claire B
Cardialysis, Clinical Trial Management & Core Laboratories, Rotterdam, The Netherlands.
Thoraxcenter, Erasmus University Medical Center, Rotterdam, The Netherlands.
J Cardiovasc Imaging. 2023 Jul;31(3):135-141. doi: 10.4250/jcvi.2022.0130.
Global longitudinal strain (GLS) is an accurate and reproducible parameter of left ventricular (LV) systolic function which has shown meaningful prognostic value. Fast, user-friendly, and accurate tools are required for its widespread implementation. We aim to compare a novel web-based tool with two established algorithms for strain analysis and test its reproducibility.
Thirty echocardiographic datasets with focused LV acquisitions were analyzed using three different semi-automated endocardial GLS algorithms by two readers. Analyses were repeated by one reader for the purpose of intra-observer variability. CAAS Qardia (Pie Medical Imaging) was compared with 2DCPA and AutoLV (TomTec).
Mean GLS values were -15.0 ± 3.5% from Qardia, -15.3 ± 4.0% from 2DCPA, and -15.2 ± 3.8% from AutoLV. Mean GLS between Qardia and 2DCPA were not statistically different (p = 0.359), with a bias of -0.3%, limits of agreement (LOA) of 3.7%, and an intra-class correlation coefficient (ICC) of 0.88. Mean GLS between Qardia and AutoLV were not statistically different (p = 0.637), with a bias of -0.2%, LOA of 3.4%, and an ICC of 0.89. The coefficient of variation (CV) for intra-observer variability was 4.4% for Qardia, 8.4% 2DCPA, and 7.7% AutoLV. The CV for inter-observer variability was 4.5%, 8.1%, and 8.0%, respectively.
In echocardiographic datasets of good image quality analyzed at an independent core laboratory using a standardized annotation method, a novel web-based tool for GLS analysis showed consistent results when compared with two algorithms of an established platform. Moreover, inter- and intra-observer reproducibility results were excellent.
整体纵向应变(GLS)是左心室(LV)收缩功能的一个准确且可重复的参数,已显示出有意义的预后价值。其广泛应用需要快速、用户友好且准确的工具。我们旨在将一种新型基于网络的工具与两种既定的应变分析算法进行比较,并测试其可重复性。
由两名读者使用三种不同的半自动心内膜GLS算法对30个聚焦于左心室采集的超声心动图数据集进行分析。为了评估观察者内变异性,由一名读者重复进行分析。将CAAS Qardia(Pie Medical Imaging公司)与2DCPA和AutoLV(TomTec公司)进行比较。
Qardia得出的平均GLS值为-15.0±3.5%,2DCPA为-15.3±4.0%,AutoLV为-15.2±3.8%。Qardia与2DCPA之间的平均GLS无统计学差异(p = 0.359),偏差为-0.3%,一致性界限(LOA)为3.7%,组内相关系数(ICC)为0.88。Qardia与AutoLV之间的平均GLS无统计学差异(p = 0.637),偏差为-0.2%,LOA为3.4%,ICC为0.89。观察者内变异性的变异系数(CV),Qardia为4.4%,2DCPA为8.4%,AutoLV为7.7%。观察者间变异性的CV分别为4.5%、8.1%和8.0%。
在独立核心实验室使用标准化标注方法分析的图像质量良好的超声心动图数据集中,一种新型基于网络的GLS分析工具与既定平台的两种算法相比,结果一致。此外,观察者间和观察者内的可重复性结果都非常好。