The single-beat method accurately estimated left ventricular dead-space volume across 10,000 simulated heart models, enabling non-invasive computation of filling fraction without preload manipulation.
Does a single-beat extrapolation method accurately estimate the dead-space volume of the left ventricle compared to prescribed volumes in synthetic models?
A novel single-beat method accurately estimates left ventricular dead-space volume in-silico, enabling non-invasive calculation of filling fraction to better characterize cardiac preload and heart failure subtypes.
Effect estimate: Strong correlation with minimal deviations across 10,000 in-silico heart models
Abstract Accurate assessment of cardiac preload remains a clinical challenge, particularly in heart failure patients where preload manipulation is impractical or contraindicated. Ejection fraction (EF), while widely used, reflects a combination of preload, contractility, and afterload, and may obscure the specific contribution of preload. Inspired by a preload recruitable stroke work (PRSW) model for heart function, a concise, three factor expression for ejection fraction (EF) can be obtained where EF is directly proportional to preload, directly proportional to contractility, and inversely proportional to afterload. The contractility and afterload factors are common metrics; whereas the preload factor, filling fraction (FF), is a novel, dimensionless preload metric that sets a physiologic upperbound on EF. Unfortunately, FF measurement requires an estimate of the volume intercept or dead-space volume of the left ventricle, and such a measure has, conventionally, required preload manipulation with extrapolation to the volume axis. To address this, we propose a single-beat extrapolation method for estimating the volume intercept using end-diastolic and end-systolic measurements. In-silico testing across 10,000 synthetic left ventricular geometries demonstrates strong agreement between the estimated intercept and actual, prescribed dead-space volumes. This method enables non-invasive computation of FF from single-beat data without the need for in vivo preload manipulation. Potential clinical applications include characterizing cardiac function, stratifying heart failure subtypes, and enhancing diagnostic precision when EF is preserved but preload reserve is impaired. Future validation in clinical imaging datasets is warranted to assess real-world applicability.
Hager et al. (Mon,) conducted a other in Patients with heart failure with reduced ejection fraction (HFrEF), characterized by EF < 0.5 and increased left ventricular dead-space volume. Single-beat method for estimating left ventricular dead-space volume (absolute minimum volume, AMV) vs. Classic preload variation method requiring preload manipulation was evaluated on Accuracy of single-beat estimated dead-space volume (AMV) compared to actual prescribed dead-space volume (V_W) in left ventricular models (Strong correlation with minimal deviations across 10,000 in-silico heart models). The single-beat method accurately estimated left ventricular dead-space volume across 10,000 simulated heart models, enabling non-invasive computation of filling fraction without preload manipulation.