Patient-Specific Lumped-Parameter Model for Quantifying Vessel-Specific Remodeling and Predicting Right Ventricular Function in Pulmonary Hypertension.

ABSTRACT:

Purpose

Pulmonary hypertension (PH) is a heterogeneous disease with patient-specific variability and vessel-specific remodeling, which eventually lead to right ventricular (RV) failure. The gold standard for RV assessment-pressure-volume (PV) loop acquisition-is invasive and limited to specialized settings. This study aims to develop a patient-specific lumped-parameter model that quantifies vessel-specific remodeling and simulates RV PV loops across PH phenotypes using routine clinical data.

Methods

A lumped-parameter model was calibrated using right heart catheterization and echocardiography data. Model agreement was assessed by R² values for pressure and flow goodness-of-fit, and model-derived hemodynamic metrics were compared with clinical values. A dimensionality reduction approach was applied to investigate how well different PH phenotypes could be separated.

Results

Across the cohort, the lumped-parameter model showed good agreement with clinical data. Model-derived vessel-specific (pulmonary arterial, capillary, venular) parameters highlighted physiological distinctions among phenotypes. Predicted RV PV loops revealed phenotype-specific differences in right ventricular volumes, pressures, and stroke work. The linear discriminant analysis (LDA) demonstrated qualitative separability, indicating that model-derived, nonmeasurable features offer additional discriminatory information.

Conclusion

Our results demonstrate that lumped-parameter models can be calibrated to clinical data to quantify vessel-specific remodeling and simulate RV pressure-volume dynamics to provide useful information for distinguishing among different PH phenotypes. This underscores the potential of computational models as noninvasive, clinically feasible tools for assessing in-depth pulmonary vascular and RV function in PH.

SUBMITTER: Lechuga CG 

PROVIDER: S-EPMC12835583 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature