Back

Capturing Regional Variation in Aortic Mechanics: Dual-Estimation Method for Material Parameter Identification and Biological Correlation

Lahuerta, R. D.; Miyakawa, A. A.; Maizato, M. J. S.; Crajoinas, R.; da Silva, B. D.; Krieger, J. E.; Krieger, E. M.; Cestari, I. A.

2026-06-02 bioengineering
10.64898/2026.05.29.728673 bioRxiv
Show abstract

The aorta shows significant regional variation in geometry and composition. This complexity makes numerical modeling challenging, as it requires identifying material parameters. Typically, the Holzapfel-Gasser-Ogden model is used. However, it suffers from nonuniqueness and sensitivity to outliers, which can obscure biological variation. In addition, standard compressible formulations with a volumetric-isochoric split fail to couple volumetric and anisotropic responses. To address these issues, a regularized dual-estimation framework was introduced. This framework combines a global baseline estimator with local refinement while maintaining structural material continuity. Furthermore, it uses a Modified Anisotropic model to improve the representation of compressibility physics. For validation, the approach included uniaxial extension and protein quantification from Wistar rats. The results show that the proximal ascending/aortic-arch segment is most compliant at low stretch, whereas the abdominal aorta stiffens earlier and becomes fiber-dominated at lower stretch levels. Notably, these trends align directionally with regional composition. However, the fitted stress components are model-based descriptors rather than direct measurements of individual constituents.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
Biomechanics and Modeling in Mechanobiology
25 papers in training set
Top 0.1%
28.6%
2
Journal of the Mechanical Behavior of Biomedical Materials
22 papers in training set
Top 0.1%
10.8%
3
Acta Biomaterialia
85 papers in training set
Top 0.1%
10.8%
50% of probability mass above
4
International Journal for Numerical Methods in Biomedical Engineering
12 papers in training set
Top 0.1%
7.4%
5
Computers in Biology and Medicine
120 papers in training set
Top 0.4%
5.0%
6
Annals of Biomedical Engineering
34 papers in training set
Top 0.2%
4.5%
7
PLOS Computational Biology
1633 papers in training set
Top 7%
4.5%
8
Journal of Biomechanics
57 papers in training set
Top 0.2%
3.8%
9
Journal of The Royal Society Interface
189 papers in training set
Top 1%
3.7%
10
PLOS ONE
4510 papers in training set
Top 45%
2.4%
11
Journal of Biomechanical Engineering
17 papers in training set
Top 0.1%
2.0%
12
Computer Methods and Programs in Biomedicine
27 papers in training set
Top 0.3%
1.8%
13
Scientific Reports
3102 papers in training set
Top 56%
1.7%
14
APL Bioengineering
18 papers in training set
Top 0.2%
1.0%
15
Frontiers in Physics
20 papers in training set
Top 0.7%
0.8%
16
IEEE Transactions on Biomedical Engineering
38 papers in training set
Top 0.9%
0.8%
17
Biophysical Journal
545 papers in training set
Top 6%
0.7%
18
Advanced Science
249 papers in training set
Top 23%
0.5%
19
Human Brain Mapping
295 papers in training set
Top 5%
0.5%
20
Epidemics
104 papers in training set
Top 2%
0.5%