The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Shaare Zedek Medical Center, Jerusalem, Israel.
J Am Soc Echocardiogr. 2023 Sep;36(9):967-977. doi: 10.1016/j.echo.2023.05.015. Epub 2023 Jun 17.
Right ventricular (RV) function is important in the evaluation of cardiac function, but its assessment using standard transthoracic echocardiography (TTE) remains challenging. Cardiac magnetic resonance imaging (CMR) is considered the gold standard. The American Society of Echocardiography recommends surrogate measures of RV function and RV ejection fraction (RVEF) by TTE, including fractional area change (FAC), free wall strain (FWS), and tricuspid annular planar systolic excursion (TAPSE), but they require technical expertise in acquisition and quantification.
The aim of this study was to evaluate the sensitivity, specificity, and positive and negative predictive values of FAC, FWS, and TAPSE derived using a rapid, novel artificial intelligence (AI) software (LVivoRV) from a single-plane transthoracic echocardiographic apical four-chamber, RV-focused view without ultrasound-enhancing agents for detecting abnormal RV function compared with CMR-derived RVEF. RV dysfunction was defined as RVEF < 50% and RVEF < 40% on CMR.
TTE and CMR were performed within a median of 10 days (interquartile range, 2-32 days) of each other in 225 consecutive patients without interval procedural or pharmacologic intervention. The sensitivity and negative predictive value to detect CMR-defined RV dysfunction when all three AI-derived parameters (FAC, FWS, and TAPSE) were abnormal were 91% and 96%, while those of expert physician reads were 91% and 97%. Specificity and positive predictive value were lower (50% and 32%) compared with expert physician-read echocardiograms (82% and 56%).
AI-derived measurements of FAC, FWS, and TAPSE had excellent sensitivity and negative predictive value for ruling out significant RV dysfunction (CMR RVEF < 40%), comparable with that of expert physician readers, but lower specificity. Thus AI, using American Society of Echocardiography guidelines, may serve as a useful screening tool for rapid bedside assessment to exclude significant RV dysfunction.
右心室（RV）功能对于心脏功能评估很重要，但使用标准经胸超声心动图（TTE）评估其功能仍然具有挑战性。心脏磁共振成像（CMR）被认为是金标准。美国超声心动图学会推荐使用 TTE 测量 RV 功能和 RV 射血分数（RVEF）的替代指标，包括分数面积变化（FAC）、游离壁应变（FWS）和三尖瓣环平面收缩期位移（TAPSE），但这些指标在采集和定量方面需要技术专长。
本研究的目的是评估使用快速、新型人工智能（AI）软件（LVivoRV）从单个平面经胸超声心动图心尖四腔、RV 焦点视图中获得的 FAC、FWS 和 TAPSE 的敏感性、特异性以及阳性和阴性预测值，该视图无需使用超声增强剂，用于检测与 CMR 衍生的 RVEF 相比异常 RV 功能。RV 功能障碍定义为 CMR 上的 RVEF<50%和 RVEF<40%。
在 225 例连续患者中，TTE 和 CMR 在彼此中位数 10 天（四分位距，2-32 天）内进行，其间无间隔程序或药物干预。当所有三个 AI 衍生参数（FAC、FWS 和 TAPSE）异常时，检测 CMR 定义的 RV 功能障碍的敏感性和阴性预测值分别为 91%和 96%，而专家医生阅读的敏感性和阴性预测值分别为 91%和 97%。与专家医生阅读的超声心动图相比，特异性和阳性预测值较低（分别为 50%和 32%）（分别为 82%和 56%）。
AI 衍生的 FAC、FWS 和 TAPSE 测量值对排除严重 RV 功能障碍（CMR RVEF<40%）具有出色的敏感性和阴性预测值，与专家医生读者相当，但特异性较低。因此，根据美国超声心动图学会指南，AI 可能作为一种有用的床边快速评估筛查工具，用于排除严重 RV 功能障碍。
