A computational bio-chemo-mechanical model of in vivo tissue-engineered vascular graft development

Abstract Stenosis is the primary complication of current tissue-engineered vascular grafts used in pediatric congenital cardiac surgery. Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in sc...

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Veröffentlicht in:Integrative biology (Cambridge) 2020-04, Vol.12 (3), p.47-63
Hauptverfasser: Khosravi, Ramak, Ramachandra, Abhay B, Szafron, Jason M, Schiavazzi, Daniele E, Breuer, Christopher K, Humphrey, Jay D
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container_title Integrative biology (Cambridge)
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creator Khosravi, Ramak
Ramachandra, Abhay B
Szafron, Jason M
Schiavazzi, Daniele E
Breuer, Christopher K
Humphrey, Jay D
description Abstract Stenosis is the primary complication of current tissue-engineered vascular grafts used in pediatric congenital cardiac surgery. Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in scaffold design or therapeutic strategies to prevent narrowing. In contrast, computational modeling promises to enable time- and cost-efficient examinations of factors leading to narrowing. Whereas past models have been limited by their phenomenological basis, we present a new mechanistic model that integrates molecular- and cellular-driven immuno- and mechano-mediated contributions to in vivo neotissue development within implanted polymeric scaffolds. Model parameters are inferred directly from in vivo measurements for an inferior vena cava interposition graft model in the mouse that are augmented by data from the literature. By complementing Bayesian estimation with identifiability analysis and simplex optimization, we found optimal parameter values that match model outputs with experimental targets and quantify variability due to measurement uncertainty. Utility is illustrated by parametrically exploring possible graft narrowing as a function of scaffold pore size, macrophage activity, and the immunomodulatory cytokine transforming growth factor beta 1 (TGF-β1). The model captures salient temporal profiles of infiltrating immune and synthetic cells and associated secretion of cytokines, proteases, and matrix constituents throughout neovessel evolution, and parametric studies suggest that modulating scaffold immunogenicity with early immunomodulatory therapies may reduce graft narrowing without compromising compliance.
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Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in scaffold design or therapeutic strategies to prevent narrowing. In contrast, computational modeling promises to enable time- and cost-efficient examinations of factors leading to narrowing. Whereas past models have been limited by their phenomenological basis, we present a new mechanistic model that integrates molecular- and cellular-driven immuno- and mechano-mediated contributions to in vivo neotissue development within implanted polymeric scaffolds. Model parameters are inferred directly from in vivo measurements for an inferior vena cava interposition graft model in the mouse that are augmented by data from the literature. By complementing Bayesian estimation with identifiability analysis and simplex optimization, we found optimal parameter values that match model outputs with experimental targets and quantify variability due to measurement uncertainty. Utility is illustrated by parametrically exploring possible graft narrowing as a function of scaffold pore size, macrophage activity, and the immunomodulatory cytokine transforming growth factor beta 1 (TGF-β1). 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Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in scaffold design or therapeutic strategies to prevent narrowing. In contrast, computational modeling promises to enable time- and cost-efficient examinations of factors leading to narrowing. Whereas past models have been limited by their phenomenological basis, we present a new mechanistic model that integrates molecular- and cellular-driven immuno- and mechano-mediated contributions to in vivo neotissue development within implanted polymeric scaffolds. Model parameters are inferred directly from in vivo measurements for an inferior vena cava interposition graft model in the mouse that are augmented by data from the literature. 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source MEDLINE; Oxford University Press Journals All Titles (1996-Current)
subjects Algorithms
Animal models
Animals
Bayes Theorem
Bayesian analysis
Blood Vessel Prosthesis
Computer applications
Computer Simulation
Cytokines
Fibroblasts - metabolism
Grafting
Growth factors
Heart
Heart surgery
Heart transplantation
Immunogenicity
Immunomodulation
Inflammation
Macrophages
Macrophages - metabolism
Mathematical models
Mice
Monocytes - metabolism
Optimization
Original
Parameter identification
Pediatrics
Polymers - chemistry
Pore size
Prosthesis Design
Scaffolds
Sensitivity and Specificity
Signal Transduction
Stenosis
Tissue engineering
Tissue Engineering - methods
Tissue Scaffolds
Transforming Growth Factor beta1 - metabolism
Transforming growth factor-b1
Vena Cava, Inferior - surgery
title A computational bio-chemo-mechanical model of in vivo tissue-engineered vascular graft development
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