Why the study?
This study aimed to identify strain-volume loop characteristics that differentiate heart failure patients from individuals without cardiac disease.
Does strain-volume loop analysis using 3D echocardiography accurately differentiate heart failure phenotypes from individuals without cardiac disease?
Does strain-volume loop analysis using 3D echocardiography accurately differentiate heart failure phenotypes from individuals without cardiac disease?
Strain-volume loop analysis using 3D echocardiography provides a novel, non-invasive method to accurately classify heart failure phenotypes based on systolic and diastolic mechanics.
BACKGROUND AND OBJECTIVES: Strain-volume loop (SVL) dynamics demonstrate the relationship between myocardial strain and left ventricular (LV) volume throughout the cardiac cycle, offering insights into both systolic and diastolic function. This study aimed to identify SVL characteristics that differentiate heart failure (HF) patients from those without cardiac disease. METHODS: This retrospective analysis included 352 individuals who underwent 3-dimensional (3D) echocardiography at tertiary care hospitals. Participants were classified into no cardiac disease, HF with preserved ejection fraction (HFpEF), and HF with reduced ejection fraction (HFrEF) groups. Temporal 3D strain and LV volume data from each frame were used to construct SVLs. Key parameters-systolic, early and late diastolic slopes, area between curves, and peak strain-were analyzed. RESULTS: Patients with HFpEF exhibited lower systolic slopes compared to those without cardiac disease, while patients with HFrEF had the lowest values (p<0.001). During early diastole, individuals without cardiac disease exhibited a sharp strain change relative to volume, whereas the HFpEF and HFrEF groups showed diminished changes. Differences in early and late diastolic slopes and the area between the systolic and diastolic curves progressively decreased from individuals without cardiac disease to those with HFpEF and HFrEF. Support vector machine analysis using SVL parameters showed strong discrimination, with 0.878 overall accuracy in classifying the 3 groups. CONCLUSIONS: SVL analysis comprehensively represents the strain-volume relationship, distinguishing HF patients from those without cardiac disease. It may serve as a non-invasive tool for evaluating cardiac function, providing insights into functional transitions across HF phenotypes.
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Lee et al. (2026) studied this question.
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