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Updated: Aug 6, 2026

Cardiac Pressure-Volume Loop Analysis Using Conductance Catheters in Mice
Published on: September 17, 2015
Method for generating right ventricular pressure-volume loops in routine practice
Nils Kremer1, Felix Glocker1, Simon Schaefer1
1Department of Internal Medicine, Justus-Liebig-University Giessen, Universities of Giessen and Marburg Lung Center, Member of the German Center for Lung Research, Giessen, Germany.
Background:
Analysis of pressure-volume (PV) loops from conductance catheterization is the gold standard for evaluating right ventricular (RV) function, but the complexity of conductance catheterization limits clinical implementation. This study validates a novel method for reconstructing RV PV loops from pressure waveforms acquired during routine right heart catheterization (RHC).
Methods:
An algorithm was developed to estimate RV volume from pressure using the hydromotive source pressure model with external calibration. The method was validated against conductance catheterization in swine (preclinical cohort) and in patients with pulmonary hypertension (clinical cohort), and against 3-dimensional echocardiography in patients with routine RHC (feasibility cohort). Agreement was assessed using Bland-Altman analysis and correlation.
Results:
In the preclinical cohort (n = 10, 22 recordings), pressure-derived stroke work (SW) demonstrated very good agreement with conductance values (bias -0.4%; percentage error 7.0%). End-diastolic volume (EDV) showed moderate agreement (bias 3.7%; percentage error 29.0%). In the clinical cohort (n = 44, 44 recordings), agreement was good for SW (bias -2.8%; percentage error 14.6%) and borderline for EDV (bias -5.5%; percentage error 35.3%). In the feasibility cohort (n = 29, 29 recordings), agreement was good for ejection fraction (EF) (bias 2.2%, percentage error 30.3%) and moderate for stroke volume (SV), EDV, end-systolic elastance (Ees), and arterial elastance. All parameters correlated strongly with reference values (Pearson r ≥ 0.79, p < 0.001).
Conclusion:
This pressure-based method reconstructs RV PV loops from standard RHC data and reliably estimates SW, contractility, and afterload, supporting its integration into routine clinical workflows (tool freely available at https://pv-loop-generator.onrender.com).

