The puzzle centers on the right ventricle, the muscular chamber that pumps deoxygenated blood into the pulmonary arteries. Clinical studies stretching back roughly eight decades have consistently documented that the right ventricle’s ejection fraction, the gold-standard measure of its pumping efficiency, drops after lung resection, typically by around twelve percent on average. What has remained fiercely debated is why. One school of thought holds that removing lung tissue raises the afterload, the resistance and stiffness the ventricle must work against, because the same cardiac output must now squeeze through fewer vessels. Another suspects that the surgery itself injures the heart muscle, perhaps through an inflammatory cascade, blunting its contractility. Because these two mechanisms cannot be independently manipulated in a living patient, the debate has stalled.

The Glasgow team, led by Shiting Huang and Ankush Aggarwal, attacked the problem with a lumped parameter model, a mathematical representation of the cardiovascular system built on a hydraulic-electrical analogy in which voltage stands for pressure and current for blood flow. Their closed-loop simulation contains four heart chambers governed by time-varying elastance functions, four valves modeled with turbulence and inertance effects, and two circulations, systemic and pulmonary, each represented by a three-element Windkessel network capturing resistance, compliance, and characteristic impedance. Fourteen state variables, including chamber volumes, valve flows, and valve opening states, evolve through coupled differential equations integrated over ten cardiac cycles until the system reaches a steady state.

Getting the baseline right was itself a serious undertaking. Because parameters in closed-loop models interact rather than acting in isolation, values lifted directly from the literature produced non-physiological results. The researchers therefore ran an exhaustive search over more than half a million Sobol-sampled parameter combinations, selecting the set whose outputs best matched reference values for ventricular pressures, stroke volumes, ejection fractions, and pulmonary arterial pressures. They then stress-tested the model with both local sensitivity analysis, perturbing each parameter by one percent, and a global Sobol analysis spanning nearly 3.7 million parameter sets. Two parameters dominated: pulmonary vascular resistance and maximal right ventricular elastance, the mathematical embodiment of contractility.

To simulate surgery, the team treated the lung as a set of parallel segments and removed a fraction of them, which raises effective resistance and impedance while shrinking compliance in proportion to the tissue lost. For the alternative mechanism, they simply reduced the right ventricle’s maximal elastance, mimicking a loss of contractile strength. The striking result is that the two mechanisms produce nearly identical trends across almost every clinically routine measurement. Right ventricular volumes balloon in both scenarios, with end-systolic volume rising by up to thirty-four percent, and ejection fraction falls by roughly twelve percent either way. On the left side of the heart, changes remain modest, consistent with clinical reports that left ventricular function is largely preserved.

But three measurements split the mechanisms decisively. Right ventricular systolic pressure and pulmonary arterial systolic and diastolic pressures rise sharply under afterload increase, by nearly fifty percent in the pulmonary artery, yet fall under contractility loss. The timing differs too: afterload elevation raises pressures across the whole of systole, whereas contractility loss depresses them mainly in early systole. Pressure-volume loops tell the same story from a different angle, with the right ventricular loop shifting toward higher pressures and volumes under afterload increase but toward lower pressures and higher volumes under contractility loss. In principle, then, a simple pressure measurement in the pulmonary artery could reveal which mechanism, or what mixture of both, is driving an individual patient’s decline.

When the team compared their simulations against the published clinical literature, the agreement was encouraging. The model reproduces the observed five to twenty percent declines in ejection fraction and the reported increases in right ventricular volumes. It even accommodates the contradictory pressure findings scattered through the literature: studies reporting rising pulmonary pressures align with the afterload scenario, while the one study that recorded a slight decrease fits the contractility-loss scenario. This suggests that the historical confusion in clinical data may not reflect measurement error so much as genuine heterogeneity, with different patients experiencing different blends of the two mechanisms.

The clinical implications could be substantial. If pressure measurements can quantify the precise combination of afterload increase and contractility loss in a given patient, treatment could be tailored accordingly: pulmonary vasodilators and careful fluid management for afterload-driven dysfunction, inotropic support for contractility-driven failure. Animal studies have shown that right ventricular function can remain depressed even after afterload normalizes, hinting that contractile injury is real and persistent, and the new model provides a framework for testing how much each mechanism contributes. The researchers emphasize that the model is deliberately simple, a first step rather than a finished clinical tool.

Limitations remain. The baseline assumes a healthy heart, whereas lung cancer patients often carry comorbidities; compensatory mechanisms and long-term adaptation are absent; the ventricles are not coupled; and a lumped model cannot capture localized wave reflections in the pulmonary tree, which recent clinical work has implicated in right ventricular impairment. Quantitative validation against patient-specific cohorts is still needed. Yet the significance of the study lies less in its numbers than in its proof of concept: for the first time, the cardiovascular consequences of lung resection can be simulated, decomposed, and compared against eight decades of clinical observation. As the model is refined with real patient data, it could evolve into a decision-support system that identifies vulnerable right ventricles before they fail, turning a long-standing surgical mystery into a manageable, measurable risk.

Subject of Research: Computational modeling of right ventricular dysfunction mechanisms following lung resection surgery

Article Title: Cardiovascular function changes following lung resection: a computational model to compare afterload increase and contractility loss mechanisms

Article References: Huang, S., Pant, S., McGinty, S., Good, R., Shelley, B., & Aggarwal, A. (2026). Cardiovascular function changes following lung resection: a computational model to compare afterload increase and contractility loss mechanisms. Medical & Biological Engineering & Computing. https://doi.org/10.1007/s11517-026-03682-1

Image Credits: AI Generated

DOI: 10.1007/s11517-026-03682-1

Keywords: lung resection, right ventricle, RV dysfunction, afterload, contractility, lumped parameter model, cardiovascular modeling, pulmonary circulation, lung cancer surgery, ejection fraction, hemodynamics, sensitivity analysis