Filling Fraction and Single Beat Method for Estimating Dead-Space Volume of Left Ventricle

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.

Authors

Institutions

Publication Details

Journal
Cardiovascular Engineering and Technology
Published
2026-03-02
DOI
https://doi.org/10.1007/s13239-025-00809-7
Primary Topic
Cardiovascular Function and Risk Factors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Filling Fraction and Single Beat Method for Estimating Dead-Space Volume of Left Ventricle

Melanie P. Hager, John C. Criscione, George V. Letsou
Cardiovascular Engineering and Technology
Cardiovascular Function and Risk Factors
article

Filling Fraction and Single Beat Method for Estimating Dead-Space Volume of Left Ventricle

Melanie P. Hager, John C. Criscione, George V. Letsou
article en

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.

Cardiovascular Engineering and Technology
Andover Eye Associates (US), Texas A&M Health Science Center (US), University of Houston (US), Texas A&M University (US), Bryan College (US)
Openalex Percentile: Top 43%
Cardiovascular Function and Risk Factors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.