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A Computational Growth and Remodeling Framework for Adaptive and Maladaptive Pulmonary Arterial Hemodynamics

Hemodynamic loading is known to contribute to the development and progression of pulmonary arterial hypertension (PAH). This loading drives changes in mechanobiological stimuli that affect cellular phenotypes and lead to pulmonary vascular remodeling. Computational models have been used to simulate...

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Autores principales: Szafron, Jason M., Yang, Weiguang, Feinstein, Jeffrey A., Rabinovitch, Marlene, Marsden, Alison L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10153237/
https://www.ncbi.nlm.nih.gov/pubmed/37131683
http://dx.doi.org/10.1101/2023.04.20.537714
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author Szafron, Jason M.
Yang, Weiguang
Feinstein, Jeffrey A.
Rabinovitch, Marlene
Marsden, Alison L.
author_facet Szafron, Jason M.
Yang, Weiguang
Feinstein, Jeffrey A.
Rabinovitch, Marlene
Marsden, Alison L.
author_sort Szafron, Jason M.
collection PubMed
description Hemodynamic loading is known to contribute to the development and progression of pulmonary arterial hypertension (PAH). This loading drives changes in mechanobiological stimuli that affect cellular phenotypes and lead to pulmonary vascular remodeling. Computational models have been used to simulate mechanobiological metrics of interest, such as wall shear stress, at single time points for PAH patients. However, there is a need for new approaches that simulate disease evolution to allow for prediction of long-term outcomes. In this work, we develop a framework that models the pulmonary arterial tree through adaptive and maladaptive responses to mechanical and biological perturbations. We coupled a constrained mixture theory-based growth and remodeling framework for the vessel wall with a morphometric tree representation of the pulmonary arterial vasculature. We show that non-uniform mechanical behavior is important to establish the homeostatic state of the pulmonary arterial tree, and that hemodynamic feedback is essential for simulating disease time courses. We also employed a series of maladaptive constitutive models, such as smooth muscle hyperproliferation and stiffening, to identify critical contributors to development of PAH phenotypes. Together, these simulations demonstrate an important step towards predicting changes in metrics of clinical interest for PAH patients and simulating potential treatment approaches.
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spelling pubmed-101532372023-05-03 A Computational Growth and Remodeling Framework for Adaptive and Maladaptive Pulmonary Arterial Hemodynamics Szafron, Jason M. Yang, Weiguang Feinstein, Jeffrey A. Rabinovitch, Marlene Marsden, Alison L. bioRxiv Article Hemodynamic loading is known to contribute to the development and progression of pulmonary arterial hypertension (PAH). This loading drives changes in mechanobiological stimuli that affect cellular phenotypes and lead to pulmonary vascular remodeling. Computational models have been used to simulate mechanobiological metrics of interest, such as wall shear stress, at single time points for PAH patients. However, there is a need for new approaches that simulate disease evolution to allow for prediction of long-term outcomes. In this work, we develop a framework that models the pulmonary arterial tree through adaptive and maladaptive responses to mechanical and biological perturbations. We coupled a constrained mixture theory-based growth and remodeling framework for the vessel wall with a morphometric tree representation of the pulmonary arterial vasculature. We show that non-uniform mechanical behavior is important to establish the homeostatic state of the pulmonary arterial tree, and that hemodynamic feedback is essential for simulating disease time courses. We also employed a series of maladaptive constitutive models, such as smooth muscle hyperproliferation and stiffening, to identify critical contributors to development of PAH phenotypes. Together, these simulations demonstrate an important step towards predicting changes in metrics of clinical interest for PAH patients and simulating potential treatment approaches. Cold Spring Harbor Laboratory 2023-04-21 /pmc/articles/PMC10153237/ /pubmed/37131683 http://dx.doi.org/10.1101/2023.04.20.537714 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Szafron, Jason M.
Yang, Weiguang
Feinstein, Jeffrey A.
Rabinovitch, Marlene
Marsden, Alison L.
A Computational Growth and Remodeling Framework for Adaptive and Maladaptive Pulmonary Arterial Hemodynamics
title A Computational Growth and Remodeling Framework for Adaptive and Maladaptive Pulmonary Arterial Hemodynamics
title_full A Computational Growth and Remodeling Framework for Adaptive and Maladaptive Pulmonary Arterial Hemodynamics
title_fullStr A Computational Growth and Remodeling Framework for Adaptive and Maladaptive Pulmonary Arterial Hemodynamics
title_full_unstemmed A Computational Growth and Remodeling Framework for Adaptive and Maladaptive Pulmonary Arterial Hemodynamics
title_short A Computational Growth and Remodeling Framework for Adaptive and Maladaptive Pulmonary Arterial Hemodynamics
title_sort computational growth and remodeling framework for adaptive and maladaptive pulmonary arterial hemodynamics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10153237/
https://www.ncbi.nlm.nih.gov/pubmed/37131683
http://dx.doi.org/10.1101/2023.04.20.537714
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