Ultrasound-Based Hemodynamic Force Trajectories in a Murine Model of Reversible Pressure Overload

Abstract

Hemodynamic forces (HDF) quantify intraventricular pressure gradients as integrated vectors derived from myocardial motion and blood flow, providing a sensitive marker of left ventricular pump efficiency beyond conventional metrics such as ejection fraction or strain. Although HDF analysis has been clinically validated in heart failure, it remains underexplored in preclinical models. To determine whether HDF metrics derived from high-resolution murine echocardiography can sensitively track cardiac dysfunction and predict functional recovery, male mice (n = 8) underwent serial echocardiography at baseline, after transverse aortic constriction (TAC), and four weeks after aortic debanding (deTAC). Left ventricular function and interval-specific HDF components were quantified, including longitudinal and transverse forces over predefined systolic and diastolic windows. Longitudinal interval-based parameters emerged as sensitive, integrative markers of LV dysfunction after TAC and DeTAC. Notably, a novel systolic acceleration-to-relaxation longitudinal HDF ratio showed the strongest associations with pressure overload and subsequent functional recovery (baseline vs TAC: p < 0.001; TAC vs deTAC: p < 0.001; baseline vs deTAC: p = 0.043). In contrast, diastolic HDF indices, including the previously proposed longitudinal e-wave ratio, did not significantly differentiate between time points. Transverse HDF over the systolic impulse interval further demonstrated potential for predicting post-surgical recovery following unloading. These findings support systolic HDF metrics, particularly longitudinal and transverse interval-based parameters, as sensitive integrative markers of LV dysfunction and reverse remodeling in preclinical pressure-overload models, and highlight their translational relevance for echocardiography-based HDF analysis. Key pointsHemodynamic force (HDF) analysis evaluate intraventricular pressure gradients as integrated vectors of myocardial motion and blood flow, providing complementary markers of pump (in)efficiency beyond ejection fraction or strain. High-resolution murine echocardiography enables robust derivation of interval-specific HDF metrics. Systolic HDF metrics, particularly transverse components during impulse intervals showed potential for predicting recovery. Systolic HDF reflect key changes in force generation and intraventricular flow during pressure overload, allowing early detection of maladaptive remodeling and treatment response, with strong translational potential for non-invasive risk stratification in aortic stenosis patients.