The Echocardiographic Evaluation of the Right Heart: Current and Future Advances

Purpose of ReviewTo discuss physiologic and methodologic advances in the echocardiographic assessment of right heart (RH) function, including the emergence of artificial intelligence (AI) and point-of-care ultrasound.Recent FindingsRecent studies have highlighted the prognostic value of right ventricular (RV) longitudinal strain, RV end-systolic dimensions, and right atrial (RA) size and function in pulmonary hypertension and heart failure. While RA pressure is a central marker of right heart diastolic function, the recent emphasis on venous excess imaging (VExUS) has provided granularity to the systemic consequences of RH failure. Several methodological advances are also changing the landscape of RH imaging including post-processing 3D software to delineate the non-longitudinal (radial, anteroposterior, and circumferential) components of RV function, as well as AI segmentation- and non-segmentation-based quantification. Together with recent guidelines and advances in AI technology, the field is shifting from specific RV functional metrics to integrated RH disease-specific phenotypes.SummaryA modern echocardiographic evaluation of RH function should focus on the entire cardiopulmonary venous unit-from the venous to the pulmonary arterial system. Together, a multi-parametric approach, guided by physiology and AI algorithms, will help define novel integrated RH profiles for improved disease detection and monitoring.Graphical Abstract: Advances in right heart echocardiography will incorporate a physiologic, multi-parametric approach that is augmented by deep learning to develop integrated right heart phenotypes. Ao Aorta, LV left ventricle, RA right atria, RV right ventricle, PA pulmonary artery

Automated summary

The echocardiographic assessment of right heart function has seen advancements in both physiology and methodology, including the emergence of artificial intelligence and point-of-care ultrasound. Recent studies have highlighted the prognostic value of certain metrics such as right ventricular longitudinal strain, right ventricular end-systolic dimensions, and right atrial size and function in pulmonary hypertension and heart failure. Methodological advances such as post-processing 3D software and AI-based quantification are also changing the landscape of right heart imaging. A multi-parametric approach guided by physiology and AI algorithms can help define integrated right heart profiles for improved disease detection and monitoring.