Growth and remodeling in the pulmonary autograft: Computational evaluation using kinematic growth models and constrained mixture theory

Vastmans, Julie; Maes, Lauranne; Peirlinck, Mathias; Vanderveken, Emma; Rega, Filip; Kuhl, Ellen; Famaey, Nele

doi:10.1002/cnm.3545

Cited by 13 publications

(5 citation statements)

References 40 publications

(99 reference statements)

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“…By providing data on microstructure, mechanical properties, geometry, hemodynamics and the underlying pathways, experimental models can enable numerical simulation of autograft remodeling ( 163 , 164 ). Subsequently, the ideal conditions for remodeling, or conversely, the risk of dissection, could be identified in so-called in silico trials ( 165 ).…”

Section: Discussionmentioning

confidence: 99%

Understanding Pulmonary Autograft Remodeling After the Ross Procedure: Stick to the Facts

Hoof

Verbrugghe

Jones

et al. 2022

Front. Cardiovasc. Med.

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The Ross, or pulmonary autograft, procedure presents a fascinating mechanobiological scenario. Due to the common embryological origin of the aortic and pulmonary root, the conotruncus, several authors have hypothesized that a pulmonary autograft has the innate potential to remodel into an aortic phenotype once exposed to systemic conditions. Most of our understanding of pulmonary autograft mechanobiology stems from the remodeling observed in the arterial wall, rather than the valve, simply because there have been many opportunities to study the walls of dilated autografts explanted at reoperation. While previous histological studies provided important clues on autograft adaptation, a comprehensive understanding of its determinants and underlying mechanisms is needed so that the Ross procedure can become a widely accepted aortic valve substitute in select patients. It is clear that protecting the autograft during the early adaptation phase is crucial to avoid initiating a sequence of pathological remodeling. External support in the freestanding Ross procedure should aim to prevent dilatation while simultaneously promoting remodeling, rather than preventing dilatation at the cost of vascular atrophy. To define the optimal mechanical properties and geometry for external support, the ideal conditions for autograft remodeling and the timeline of mechanical adaptation must be determined. We aimed to rigorously review pulmonary autograft remodeling after the Ross procedure. Starting from the developmental, microstructural and biomechanical differences between the pulmonary artery and aorta, we review autograft mechanobiology in relation to distinct clinical failure mechanisms while aiming to identify unmet clinical needs, gaps in current knowledge and areas for further research. By correlating clinical and experimental observations of autograft remodeling with established principles in cardiovascular mechanobiology, we aim to present an up-to-date overview of all factors involved in extracellular matrix remodeling, their interactions and potential underlying molecular mechanisms.

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Section: Discussionmentioning

confidence: 99%

Understanding Pulmonary Autograft Remodeling After the Ross Procedure: Stick to the Facts

Hoof

Verbrugghe

Jones

et al. 2022

Front. Cardiovasc. Med.

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“…Computational simulations play a pivotal role in understanding and predicting the biomechanical factors of a wide variety of cardiovascular diseases [8, 60, 61]. In vascular medicine, knowing the precise stress and strain fields across the vascular wall is critical for understanding the formation, growth, and rupture of aneurysms [28]; for identifying high-risk regions of plaque formation, rupture, and thrombosis [48]; and for optimizing stent materials, structure, and deployment in aortic stenosis [31].…”

Section: Motivationmentioning

confidence: 99%

Democratizing biomedical simulation through automated model discovery and a universal material subroutine

Peirlinck,

Linka,

Hurtado

et al. 2023

Preprint

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Personalized computational simulations have emerged as a vital tool to understand the biomechanical factors of a disease, predict disease progression, and design personalized intervention. Material modeling is critical for realistic biomedical simulations, and poor model selection can have life-threatening consequences for the patient. However, selecting the best model requires a profound domain knowledge and is limited to a few highly specialized experts in the field. Here we explore the feasibility of eliminating user involvement and automate the process of material modeling in finite element analyses. We leverage recent developments in constitutive neural networks, machine learning, and artificial intelligence to discover the best constitutive model from thousands of possible combinations of a few functional building blocks. We integrate all discoverable models into the finite element workflow by creating a universal material subroutine that contains more than 60,000 models, made up of 16 individual terms. We prototype this workflow using biaxial extension tests from healthy human arteries as input and stress and stretch profiles across the human aortic arch as output. Our results suggest that constitutive neural networks can robustly discover various flavors of arterial models from data, feed these models directly into a finite element simulation, and predict stress and strain profiles that compare favorably to the classical Holzapfel model. Replacing dozens of individual material subroutines by a single universal material subroutine–populated directly via automated model discovery–will make finite element simulations more user-friendly, more robust, and less vulnerable to human error. Democratizing finite element simulation by automating model selection could induce a paradigm shift in physics-based modeling, broaden access to simulation technologies, and empower individuals with varying levels of expertise and diverse backgrounds to actively participate in scientific discovery and push the boundaries of biomedical simulation.

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“…Computational models have already been used to investigate the long-term outcomes of a pulmonary autograft [18,19,20]. On the other hand, simulations have shown that both an external support and gradual loading can promote benign adaptation in vascular growth and remodeling (G&R) [21,22].…”

Section: Introductionmentioning

confidence: 99%

“…computational model in this study relies on an axisymmetric geometry, neglecting circumferential and axial variations. Future work should overcome this limitation by integrating specific finite element geometries derived from MRI scans, as demonstrated by Vastmans et al[13,19]. Furthermore, rather than using a simplified interposition graft model of the Ross procedure, autograft data from actual heart valve experiments is already accessible in-house through Van Hoof et al[14], which should bring us closer to real-world Ross…”

mentioning

confidence: 99%

Drivers of Vascular Growth and Remodeling: A Computational Framework to Promote Benign Adaptation in the Ross Procedure

Vervenne,

Maes,

Van Hoof

et al. 2023

Preprint

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Growth and remodeling in the pulmonary autograft: Computational evaluation using kinematic growth models and constrained mixture theory

Cited by 13 publications

References 40 publications

Understanding Pulmonary Autograft Remodeling After the Ross Procedure: Stick to the Facts

Understanding Pulmonary Autograft Remodeling After the Ross Procedure: Stick to the Facts

Democratizing biomedical simulation through automated model discovery and a universal material subroutine

Drivers of Vascular Growth and Remodeling: A Computational Framework to Promote Benign Adaptation in the Ross Procedure

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