Evaluating the Stress State and the Load-Bearing Fraction as Predicted by an In Vivo Parameter Identification Method for the Abdominal Aorta

<b>Background:</b> Arterial mechanics are crucial to cardiovascular functionality. The pressure-strain elastic modulus often delineates mechanical properties. Emerging methods use non-linear continuum mechanics and non-convex minimization to identify tissue-specific parameters in vivo. Reliability of these methods, particularly their accuracy in representing the in vivo stress state, is a significant concern. This study aims to compare the predicted stress state and the collagen-attributed load-bearing fraction with the stress state from in silico experiments. <b>Methods:</b> Our team has evaluated an in vivo parameter identification method through in silico experiments involving finite element models and demonstrated good agreement with the parameters of a healthy abdominal aorta. <b>Results:</b> The findings suggest that the circumferential stress state is well represented for an abdominal aorta with a low transmural stress gradient. Larger discrepancies are observed in the axial direction. The agreement deteriorates in both directions with an increasing transmural stress gradient, attributed to the membrane model's inability to capture transmural gradients. The collagen-attributed load-bearing fraction is well predicted, particularly in the circumferential direction. <b>Conclusions:</b> These findings underscore the importance of investigating both isotropic and anisotropic aspects of the vessel wall. This evaluation advances the parameter identification method towards clinical application as a potential tool for assessing arterial mechanics.

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Publication Details

Journal
Medical Sciences
Published
2025-01-27
DOI
https://doi.org/10.3390/medsci13010009
Primary Topic
Elasticity and Material Modeling
Type
article
Field-Weighted Citation Impact
0.00

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article

Evaluating the Stress State and the Load-Bearing Fraction as Predicted by an In Vivo Parameter Identification Method for the Abdominal Aorta

Jerker Karlsson, Carl‐Johan Thore, Jan-Lucas Gade, Carl‐Johan Carlhäll et al.
Medical Sciences
Elasticity and Material Modeling
article

Evaluating the Stress State and the Load-Bearing Fraction as Predicted by an In Vivo Parameter Identification Method for the Abdominal Aorta

Jerker Karlsson, Carl‐Johan Thore, Jan-Lucas Gade, Carl‐Johan Carlhäll, Jan Engvall, Jonas Stålhand
article en

Abstract

<b>Background:</b> Arterial mechanics are crucial to cardiovascular functionality. The pressure-strain elastic modulus often delineates mechanical properties. Emerging methods use non-linear continuum mechanics and non-convex minimization to identify tissue-specific parameters in vivo. Reliability of these methods, particularly their accuracy in representing the in vivo stress state, is a significant concern. This study aims to compare the predicted stress state and the collagen-attributed load-bearing fraction with the stress state from in silico experiments. <b>Methods:</b> Our team has evaluated an in vivo parameter identification method through in silico experiments involving finite element models and demonstrated good agreement with the parameters of a healthy abdominal aorta. <b>Results:</b> The findings suggest that the circumferential stress state is well represented for an abdominal aorta with a low transmural stress gradient. Larger discrepancies are observed in the axial direction. The agreement deteriorates in both directions with an increasing transmural stress gradient, attributed to the membrane model's inability to capture transmural gradients. The collagen-attributed load-bearing fraction is well predicted, particularly in the circumferential direction. <b>Conclusions:</b> These findings underscore the importance of investigating both isotropic and anisotropic aspects of the vessel wall. This evaluation advances the parameter identification method towards clinical application as a potential tool for assessing arterial mechanics.

Medical SciencesVol. 13(1)
Linköping University (SE)
Region Östergötland, Lunds Universitet, Hjärt-Lungfonden, Linköpings Universitet, Vetenskapsrådet
Openalex Percentile: Top 99%
Elasticity and Material Modeling
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