Journal article
A computational model of contributors to pulmonary hypertensive disease: impacts of whole lung and focal disease distributions
Pulmonary circulation, Vol.11(4), pp.1-15
10/01/2021
DOI: 10.1177/20458940211056527
PMCID: PMC8607494
PMID: 34820115
Abstract
Pulmonary hypertension has multiple etiologies and so can be difficult to diagnose, prognose, and treat. Diagnosis is typically made via invasive hemodynamic measurements in the main pulmonary artery and is based on observed elevation of mean pulmonary artery pressure. This static mean pressure enables diagnosis, but does not easily allow assessment of the severity of pulmonary hypertension, nor the etiology of the disease, which may impact treatment. Assessment of the dynamic properties of pressure and flow data obtained from catheterization potentially allows more meaningful assessment of the strain on the right heart and may help to distinguish between disease phenotypes. However, mechanistic understanding of how the distribution of disease in the lung leading to pulmonary hypertension impacts the dynamics of blood flow in the main pulmonary artery and/or the pulmonary capillaries is lacking. We present a computational model of the pulmonary vasculature, parameterized to characteristic features of pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension to help understand how the two conditions differ in terms of pulmonary vascular response to disease. Our model incorporates key features known to contribute to pulmonary vascular function in health and disease, including anatomical structure and multiple contributions from gravity. The model suggests that dynamic measurements obtained from catheterization potentially distinguish between distal and proximal vasculopathy typical of pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension. However, the model suggests a non-linear relationship between these data and vascular structural changes typical of pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension which may impede analysis of these metrics to distinguish between cohorts.
Details
- Title: Subtitle
- A computational model of contributors to pulmonary hypertensive disease: impacts of whole lung and focal disease distributions
- Creators
- Behdad Shaarbaf Ebrahimi - University of AucklandMerryn H. Tawhai - University of AucklandHaribalan Kumar - University of AucklandKelly S. Burrowes - University of AucklandEric A. Hoffman - University of IowaMargaret L. Wilsher - University of Auckland, Faculty of Medical and Health SciencesDavid Milne - Auckland City HospitalAlys R. Clark - University of Auckland
- Resource Type
- Journal article
- Publication Details
- Pulmonary circulation, Vol.11(4), pp.1-15
- Publisher
- Sage
- DOI
- 10.1177/20458940211056527
- PMID
- 34820115
- PMCID
- PMC8607494
- ISSN
- 2045-8932
- eISSN
- 2045-8940
- Number of pages
- 15
- Grant note
- New Zealand Ministry of Business, Innovation and Employment's Catalyst Strategic fund 14-UOA-019 / Royal Society Te Aparangi Rutherford Discovery Fellowship Medical Technologies Centre of Research Excellence R01HL112986 / NIH; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA
- Language
- English
- Date published
- 10/01/2021
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Internal Medicine
- Record Identifier
- 9984318716502771
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