Cardiovascular mechanics in the early stages of pulmonary hypertension: a computational study

Sebastián Acosta*, Charles Puelz, Béatrice Rivière, Daniel J. Penny, Kenneth Martin Brady, Craig G. Rusin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


We formulate and study a new mathematical model of pulmonary hypertension. Based on principles of fluid and elastic dynamics, we introduce a model that quantifies the stiffening of pulmonary vasculature (arteries and arterioles) to reproduce the hemodynamics of the pulmonary system, including physiologically consistent dependence between compliance and resistance. This pulmonary model is embedded in a closed-loop network of the major vessels in the body, approximated as one-dimensional elastic tubes, and zero-dimensional models for the heart and other organs. Increasingly severe pulmonary hypertension is modeled in the context of two extreme scenarios: (1) no cardiac compensation and (2) compensation to achieve constant cardiac output. Simulations from the computational model are used to estimate cardiac workload, as well as pressure and flow traces at several locations. We also quantify the sensitivity of several diagnostic indicators to the progression of pulmonary arterial stiffening. Simulation results indicate that pulmonary pulse pressure, pulmonary vascular compliance, pulmonary RC time, luminal distensibility of the pulmonary artery, and pulmonary vascular impedance are much better suited to detect the early stages of pulmonary hypertension than mean pulmonary arterial pressure and pulmonary vascular resistance, which are conventionally employed as diagnostic indicators for this disease.

Original languageEnglish (US)
Pages (from-to)2093-2112
Number of pages20
JournalBiomechanics and Modeling in Mechanobiology
Issue number6
StatePublished - Dec 1 2017


  • Blood flow
  • Cardiovascular mechanics
  • Computational hemodynamics
  • Pulmonary arterial hypertension

ASJC Scopus subject areas

  • Mechanical Engineering
  • Biotechnology
  • Modeling and Simulation


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