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Data-driven computational models of ventricular-arterial hemodynamics in pediatric pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a complex disease involving increased resistance in the pulmonary arteries and subsequent right ventricular (RV) remodeling. Ventricular-arterial interactions are fundamental to PAH pathophysiology but are rarely captured in computational models. It is import...

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Autores principales: Tossas-Betancourt, Christopher, Li, Nathan Y., Shavik, Sheikh M., Afton, Katherine, Beckman, Brian, Whiteside, Wendy, Olive, Mary K., Lim, Heang M., Lu, Jimmy C., Phelps, Christina M., Gajarski, Robert J., Lee, Simon, Nordsletten, David A., Grifka, Ronald G., Dorfman, Adam L., Baek, Seungik, Lee, Lik Chuan, Figueroa, C. Alberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490558/
https://www.ncbi.nlm.nih.gov/pubmed/36160862
http://dx.doi.org/10.3389/fphys.2022.958734
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author Tossas-Betancourt, Christopher
Li, Nathan Y.
Shavik, Sheikh M.
Afton, Katherine
Beckman, Brian
Whiteside, Wendy
Olive, Mary K.
Lim, Heang M.
Lu, Jimmy C.
Phelps, Christina M.
Gajarski, Robert J.
Lee, Simon
Nordsletten, David A.
Grifka, Ronald G.
Dorfman, Adam L.
Baek, Seungik
Lee, Lik Chuan
Figueroa, C. Alberto
author_facet Tossas-Betancourt, Christopher
Li, Nathan Y.
Shavik, Sheikh M.
Afton, Katherine
Beckman, Brian
Whiteside, Wendy
Olive, Mary K.
Lim, Heang M.
Lu, Jimmy C.
Phelps, Christina M.
Gajarski, Robert J.
Lee, Simon
Nordsletten, David A.
Grifka, Ronald G.
Dorfman, Adam L.
Baek, Seungik
Lee, Lik Chuan
Figueroa, C. Alberto
author_sort Tossas-Betancourt, Christopher
collection PubMed
description Pulmonary arterial hypertension (PAH) is a complex disease involving increased resistance in the pulmonary arteries and subsequent right ventricular (RV) remodeling. Ventricular-arterial interactions are fundamental to PAH pathophysiology but are rarely captured in computational models. It is important to identify metrics that capture and quantify these interactions to inform our understanding of this disease as well as potentially facilitate patient stratification. Towards this end, we developed and calibrated two multi-scale high-resolution closed-loop computational models using open-source software: a high-resolution arterial model implemented using CRIMSON, and a high-resolution ventricular model implemented using FEniCS. Models were constructed with clinical data including non-invasive imaging and invasive hemodynamic measurements from a cohort of pediatric PAH patients. A contribution of this work is the discussion of inconsistencies in anatomical and hemodynamic data routinely acquired in PAH patients. We proposed and implemented strategies to mitigate these inconsistencies, and subsequently use this data to inform and calibrate computational models of the ventricles and large arteries. Computational models based on adjusted clinical data were calibrated until the simulated results for the high-resolution arterial models matched within 10% of adjusted data consisting of pressure and flow, whereas the high-resolution ventricular models were calibrated until simulation results matched adjusted data of volume and pressure waveforms within 10%. A statistical analysis was performed to correlate numerous data-derived and model-derived metrics with clinically assessed disease severity. Several model-derived metrics were strongly correlated with clinically assessed disease severity, suggesting that computational models may aid in assessing PAH severity.
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spelling pubmed-94905582022-09-22 Data-driven computational models of ventricular-arterial hemodynamics in pediatric pulmonary arterial hypertension Tossas-Betancourt, Christopher Li, Nathan Y. Shavik, Sheikh M. Afton, Katherine Beckman, Brian Whiteside, Wendy Olive, Mary K. Lim, Heang M. Lu, Jimmy C. Phelps, Christina M. Gajarski, Robert J. Lee, Simon Nordsletten, David A. Grifka, Ronald G. Dorfman, Adam L. Baek, Seungik Lee, Lik Chuan Figueroa, C. Alberto Front Physiol Physiology Pulmonary arterial hypertension (PAH) is a complex disease involving increased resistance in the pulmonary arteries and subsequent right ventricular (RV) remodeling. Ventricular-arterial interactions are fundamental to PAH pathophysiology but are rarely captured in computational models. It is important to identify metrics that capture and quantify these interactions to inform our understanding of this disease as well as potentially facilitate patient stratification. Towards this end, we developed and calibrated two multi-scale high-resolution closed-loop computational models using open-source software: a high-resolution arterial model implemented using CRIMSON, and a high-resolution ventricular model implemented using FEniCS. Models were constructed with clinical data including non-invasive imaging and invasive hemodynamic measurements from a cohort of pediatric PAH patients. A contribution of this work is the discussion of inconsistencies in anatomical and hemodynamic data routinely acquired in PAH patients. We proposed and implemented strategies to mitigate these inconsistencies, and subsequently use this data to inform and calibrate computational models of the ventricles and large arteries. Computational models based on adjusted clinical data were calibrated until the simulated results for the high-resolution arterial models matched within 10% of adjusted data consisting of pressure and flow, whereas the high-resolution ventricular models were calibrated until simulation results matched adjusted data of volume and pressure waveforms within 10%. A statistical analysis was performed to correlate numerous data-derived and model-derived metrics with clinically assessed disease severity. Several model-derived metrics were strongly correlated with clinically assessed disease severity, suggesting that computational models may aid in assessing PAH severity. Frontiers Media S.A. 2022-09-07 /pmc/articles/PMC9490558/ /pubmed/36160862 http://dx.doi.org/10.3389/fphys.2022.958734 Text en Copyright © 2022 Tossas-Betancourt, Li, Shavik, Afton, Beckman, Whiteside, Olive, Lim, Lu, Phelps, Gajarski, Lee, Nordsletten, Grifka, Dorfman, Baek, Lee and Figueroa. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Tossas-Betancourt, Christopher
Li, Nathan Y.
Shavik, Sheikh M.
Afton, Katherine
Beckman, Brian
Whiteside, Wendy
Olive, Mary K.
Lim, Heang M.
Lu, Jimmy C.
Phelps, Christina M.
Gajarski, Robert J.
Lee, Simon
Nordsletten, David A.
Grifka, Ronald G.
Dorfman, Adam L.
Baek, Seungik
Lee, Lik Chuan
Figueroa, C. Alberto
Data-driven computational models of ventricular-arterial hemodynamics in pediatric pulmonary arterial hypertension
title Data-driven computational models of ventricular-arterial hemodynamics in pediatric pulmonary arterial hypertension
title_full Data-driven computational models of ventricular-arterial hemodynamics in pediatric pulmonary arterial hypertension
title_fullStr Data-driven computational models of ventricular-arterial hemodynamics in pediatric pulmonary arterial hypertension
title_full_unstemmed Data-driven computational models of ventricular-arterial hemodynamics in pediatric pulmonary arterial hypertension
title_short Data-driven computational models of ventricular-arterial hemodynamics in pediatric pulmonary arterial hypertension
title_sort data-driven computational models of ventricular-arterial hemodynamics in pediatric pulmonary arterial hypertension
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490558/
https://www.ncbi.nlm.nih.gov/pubmed/36160862
http://dx.doi.org/10.3389/fphys.2022.958734
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