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Strain imaging in heart failure: from early detection to prognostic assessment

Sep 2026 · ESC Heart Failure · Vol 13 · 0 citations · 123 references
Medicine

TL;DR

In conclusion, strain imaging has expanded from a specialized technique to a part of contemporary HF evaluation by capturing myocardial mechanics, which enables early detection, precise phenotyping, robust risk stratification, and timely therapy monitoring.

Abstract

Abstract Traditional left ventricle ejection fraction (LVEF)-centric approaches often detect cardiac dysfunction late and offer limited insights into myocardial mechanics. Myocardial strain imaging by two-dimensional speckle-tracking echocardiography has emerged as a high-sensitivity alternative for comprehensive evaluation of heart failure (HF). This synthesis evaluates the diagnostic, prognostic, and therapeutic monitoring capabilities of multi-chamber strain imaging across the HF spectrum. Based on current evidence, global longitudinal strain (GLS) provides superior sensitivity over LVEF in detecting subclinical myocardial injury. In preclinical settings (Stage B HF), a GLS <16% is an important diagnostic criterion, reclassifying 13% of asymptomatic patients and predicting a four-fold higher risk of HF hospitalization. In cardio-oncology, a 15% relative decline in GLS successfully identifies subclinical toxicity before LVEF drops. Across HF phenotypes, GLS <16% has been incorporated as a minor diagnostic criterion for heart failure with preserved ejection fraction (HFpEF). GLS is a 1.6-fold better prognostic marker than LVEF (particularly in preclinical stages and HFpEF) and exhibits a more linear relationship with mortality. Furthermore, left atrial reservoir strain (<18%) accurately grades diastolic dysfunction, while right ventricular free-wall longitudinal strain acts as a powerful independent predictor of death. In conclusion, strain imaging has expanded from a specialized technique to a part of contemporary HF evaluation. By capturing myocardial mechanics, it enables early detection, precise phenotyping, robust risk stratification, and timely therapy monitoring.

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