Mekonnen Demeke, Spitzer Ernest, McFadden Eugene P, Caplice Noel M, Ren Claire B
Cardialysis, Rotterdam, The Netherlands.
Cardiology Department, Cork University Hospital, Cork, Ireland.
Int J Cardiovasc Imaging. 2025 Apr 29. doi: 10.1007/s10554-025-03409-7.
The aim of this sub-analysis of the RESUS-AMI trial was to evaluate the correlation of artificial intelligence (AI)-assisted echocardiographic global longitudinal strain (GLS) assessments with infarct size, left ventricular ejection fraction (LVEF) and volumes from cardiac magnetic resonance (CMR) imaging, in patients undergoing primary percutaneous coronary intervention for ST-elevation myocardial infarction. The reproducibility of GLS and other echocardiographic parameters derived with the AI-assisted software were also assessed.
This is a post-hoc imaging sub-analysis of the RESUS-AMI trial. Echocardiographic LVEF, volumes and GLS were measured with AI-assisted software (CAAS Qardia 2.0) using automated and semi-automated methods. The CMR LVEF, LV dimensions and infarct size were obtained from a CMR core lab with an off-line workstation (CAAS MRV 4.1).
In total 169 echocardiograms were analysed and the GLS showed moderate correlation with the CMR infarct size (r = 0.58 automated and 0.64 semi-automated, both p < 0.001) and LVEF (r=-0.63 automated and - 0.65 semi-automated, both p < 0.001) from 81 CMR recordings. GLS also showed moderate correlation with the LVEF (r= -0.51 automated and - 0.67 semi-automated, both p < 0.001) from echocardiography. The inter-observer reproducibility was excellent in GLS from both the automated (intraclass correlation (ICC) = 0.94, bias = 0.08, limit of agreement (LOA) = 1.75) and semi-automated analysis (ICC = 0.93, bias=-0.68, LOA = 1.44). The intra-observer reproducibility was excellent in all echocardiographic measurements.
GLS derived from the AI-assisted software (automated or semi-automated) could be used as a marker of LV systolic function as it correlates well the infarct size and LVEF assessed with CMR and LVEF with echocardiography.
本项对RESUS-AMI试验的亚分析旨在评估人工智能（AI）辅助超声心动图整体纵向应变（GLS）评估与梗死面积、左心室射血分数（LVEF）以及接受ST段抬高型心肌梗死直接经皮冠状动脉介入治疗患者的心脏磁共振（CMR）成像测得的心室容积之间的相关性。还评估了使用AI辅助软件得出的GLS及其他超声心动图参数的可重复性。
这是对RESUS-AMI试验的一项事后成像亚分析。使用AI辅助软件（CAAS Qardia 2.0）通过自动和半自动方法测量超声心动图LVEF、容积和GLS。CMR LVEF、左心室尺寸和梗死面积由一个配备离线工作站（CAAS MRV 4.1）的CMR核心实验室获得。
共分析了169份超声心动图，GLS与来自81份CMR记录的CMR梗死面积（自动测量r = 0.58，半自动测量r = 0.64，均p < 0.001）和LVEF（自动测量r = -0.63，半自动测量r = -0.65，均p < 0.001）呈中度相关。GLS与超声心动图测得的LVEF（自动测量r = -0.51，半自动测量r = -0.67，均p < 0.001）也呈中度相关。自动分析（组内相关系数（ICC）= 0.94，偏差 = 0.08，一致性界限（LOA）= 1.75）和半自动分析（ICC = 0.93，偏差 = -0.68，LOA = 1.44）得出的GLS观察者间可重复性均极佳。所有超声心动图测量的观察者内可重复性均极佳。
源自AI辅助软件（自动或半自动）的GLS可作为左心室收缩功能的标志物，因为它与CMR评估的梗死面积和LVEF以及超声心动图评估的LVEF相关性良好。
