How to use imaging endpoints reflecting the pulmonary circulation & RV

Artificial intelligence-based cardiac motion mapping offers predictive insights into pulmonary hypertension (PH) disease progression and its impact on the heart. We proposed an automated deep learning pipeline for bi-ventricular segmentation and 3D wall motion analysis in PH rodent models for bridging the clinical developments. 

In the study “Echocardiographic grading of right ventricular afterload in left heart disease: relation to right ventricular function, pulsatile and resistant load, and outcome,” Bech-Hanssen et al. addressed an interesting topic about severity gradation using right ventricular (RV) afterload echocardiographic assessment.

Right ventricular heart failure (RV HF) is the leading cause of death in pulmonary arterial hypertension (PAH). Relevance of the low-risk status assessment using available diagnostic tools requires a reliable confirmation.