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Fluid–structure–growth modeling in ascending aortic aneurysm: capability to reproduce a patient case.

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Title: Fluid–structure–growth modeling in ascending aortic aneurysm: capability to reproduce a patient case.
Authors: Yan, Kexin1,2,3 (AUTHOR) kexin.yan@insa-lyon.fr, Ye, Wenfeng1 (AUTHOR) wenfeng.ye@ansys.com, Martínez, Antonio1 (AUTHOR) antonio.martinezpascual@ansys.com, Geronzi, Leonardo4 (AUTHOR) leonardo.geronzi@uniroma2.it, Escrig, Pierre2 (AUTHOR) pierre.escrig@chu-rennes.fr, Tomasi, Jacques2 (AUTHOR) jacques.tomasi@chu-rennes.fr, Rochette, Michel1 (AUTHOR) michel.rochette@ansys.com, Haigron, Pascal2 (AUTHOR) pascal.haigron@univ-rennes.fr, Bel-Brunon, Aline3 (AUTHOR) aline.bel-brunon@univ-eiffel.fr
Source: Biomechanics & Modeling in Mechanobiology. Apr2025, Vol. 24 Issue 2, p405-422. 18p.
Subjects: Ascending aorta aneurysms, Clinical decision support systems, Thoracic aneurysms, Computational fluid dynamics, Jets (Fluid dynamics)
Abstract: Predicting the evolution of ascending aortic aneurysm (AscAA) growth is a challenge, complicated by the intricate interplay of aortic geometry, tissue behavior, and blood flow dynamics. We investigate a flow-structural growth and remodeling (FSG) model based on the homogenized constrained mixture theory to simulate realistic AscAA growth evolution. Our approach involves initiating a finite element model with an initial elastin insult, driven by the distribution of Time-Averaged Wall Shear Stress (TAWSS) derived from computational fluid dynamics simulations. Through FSG simulation, we first calibrate the growth and remodeling material parameters to reproduce the growth observed on a patient-specific case. Then, we explore the influence of two critical parameters: the direction of the inlet jet flow, which affects the zone of significant TAWSS, and prestretch, which impacts the tissue homeostatic state. Our results show that calibrating material parameters, inlet flow direction, and prestretch allows to reproduce the observed growth, and that prestretch calibration and inlet flow direction significantly influence the simulated growth pattern. Our workflow can be applied to additional patient cases to confirm these tendencies and progress toward a predictive tool for clinical decision support. [ABSTRACT FROM AUTHOR]
Copyright of Biomechanics & Modeling in Mechanobiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Fluid–structure–growth modeling in ascending aortic aneurysm: capability to reproduce a patient case.
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  Data: <searchLink fieldCode="AR" term="%22Yan%2C+Kexin%22">Yan, Kexin</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> kexin.yan@insa-lyon.fr</i><br /><searchLink fieldCode="AR" term="%22Ye%2C+Wenfeng%22">Ye, Wenfeng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wenfeng.ye@ansys.com</i><br /><searchLink fieldCode="AR" term="%22Martínez%2C+Antonio%22">Martínez, Antonio</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> antonio.martinezpascual@ansys.com</i><br /><searchLink fieldCode="AR" term="%22Geronzi%2C+Leonardo%22">Geronzi, Leonardo</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> leonardo.geronzi@uniroma2.it</i><br /><searchLink fieldCode="AR" term="%22Escrig%2C+Pierre%22">Escrig, Pierre</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> pierre.escrig@chu-rennes.fr</i><br /><searchLink fieldCode="AR" term="%22Tomasi%2C+Jacques%22">Tomasi, Jacques</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> jacques.tomasi@chu-rennes.fr</i><br /><searchLink fieldCode="AR" term="%22Rochette%2C+Michel%22">Rochette, Michel</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> michel.rochette@ansys.com</i><br /><searchLink fieldCode="AR" term="%22Haigron%2C+Pascal%22">Haigron, Pascal</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> pascal.haigron@univ-rennes.fr</i><br /><searchLink fieldCode="AR" term="%22Bel-Brunon%2C+Aline%22">Bel-Brunon, Aline</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> aline.bel-brunon@univ-eiffel.fr</i>
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  Data: <searchLink fieldCode="JN" term="%22Biomechanics+%26+Modeling+in+Mechanobiology%22">Biomechanics & Modeling in Mechanobiology</searchLink>. Apr2025, Vol. 24 Issue 2, p405-422. 18p.
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  Data: <searchLink fieldCode="DE" term="%22Ascending+aorta+aneurysms%22">Ascending aorta aneurysms</searchLink><br /><searchLink fieldCode="DE" term="%22Clinical+decision+support+systems%22">Clinical decision support systems</searchLink><br /><searchLink fieldCode="DE" term="%22Thoracic+aneurysms%22">Thoracic aneurysms</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+fluid+dynamics%22">Computational fluid dynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Jets+%28Fluid+dynamics%29%22">Jets (Fluid dynamics)</searchLink>
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  Label: Abstract
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  Data: Predicting the evolution of ascending aortic aneurysm (AscAA) growth is a challenge, complicated by the intricate interplay of aortic geometry, tissue behavior, and blood flow dynamics. We investigate a flow-structural growth and remodeling (FSG) model based on the homogenized constrained mixture theory to simulate realistic AscAA growth evolution. Our approach involves initiating a finite element model with an initial elastin insult, driven by the distribution of Time-Averaged Wall Shear Stress (TAWSS) derived from computational fluid dynamics simulations. Through FSG simulation, we first calibrate the growth and remodeling material parameters to reproduce the growth observed on a patient-specific case. Then, we explore the influence of two critical parameters: the direction of the inlet jet flow, which affects the zone of significant TAWSS, and prestretch, which impacts the tissue homeostatic state. Our results show that calibrating material parameters, inlet flow direction, and prestretch allows to reproduce the observed growth, and that prestretch calibration and inlet flow direction significantly influence the simulated growth pattern. Our workflow can be applied to additional patient cases to confirm these tendencies and progress toward a predictive tool for clinical decision support. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Biomechanics & Modeling in Mechanobiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Type: general
      – SubjectFull: Clinical decision support systems
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              Text: Apr2025
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