Literature DB >> 30413984

On the computation of in vivo transmural mean stress of patient-specific aortic wall.

Minliang Liu1, Liang Liang1, Haofei Liu2, Ming Zhang2, Caitlin Martin1, Wei Sun3.   

Abstract

It is well known that residual deformations/stresses alter the mechanical behavior of arteries, e.g., the pressure-diameter curves. In an effort to enable personalized analysis of the aortic wall stress, approaches have been developed to incorporate experimentally derived residual deformations into in vivo loaded geometries in finite element simulations using thick-walled models. Solid elements are typically used to account for "bending-like" residual deformations. Yet, the difficulty in obtaining patient-specific residual deformations and material properties has become one of the biggest challenges of these thick-walled models. In thin-walled models, fortunately, static determinacy offers an appealing prospect that allows for the calculation of the thin-walled membrane stress without patient-specific material properties. The membrane stress can be computed using forward analysis by enforcing an extremely stiff material property as penalty treatment, which is referred to as the forward penalty approach. However, thin-walled membrane elements, which have zero bending stiffness, are incompatible with the residual deformations, and therefore, it is often stated as a limitation of thin-walled models. In this paper, by comparing the predicted stresses from thin-walled models and thick-walled models, we demonstrate that the transmural mean stress is approximately the same for the two models and can be readily obtained from in vivo clinical images without knowing the patient-specific material properties and residual deformations. Computation of patient-specific mean stress can be greatly simplified by using the forward penalty approach, which may be clinically valuable.

Entities:  

Keywords:  Forward penalty approach; Membrane stress; Residual stress; Transmural mean stress

Mesh:

Year:  2018        PMID: 30413984      PMCID: PMC6420364          DOI: 10.1007/s10237-018-1089-5

Source DB:  PubMed          Journal:  Biomech Model Mechanobiol        ISSN: 1617-7940


  28 in total

1.  Three-dimensional finite element analysis of residual stress in arteries.

Authors:  M L Raghavan; S Trivedi; A Nagaraj; D D McPherson; K B Chandran
Journal:  Ann Biomed Eng       Date:  2004-02       Impact factor: 3.934

2.  Layer-specific damage experiments and modeling of human thoracic and abdominal aortas with non-atherosclerotic intimal thickening.

Authors:  Hannah Weisbecker; David M Pierce; Peter Regitnig; Gerhard A Holzapfel
Journal:  J Mech Behav Biomed Mater       Date:  2012-03-28

3.  A generalized prestressing algorithm for finite element simulations of preloaded geometries with application to the aorta.

Authors:  Hannah Weisbecker; David M Pierce; Gerhard A Holzapfel
Journal:  Int J Numer Method Biomed Eng       Date:  2014-03-04       Impact factor: 2.747

4.  A machine learning approach to investigate the relationship between shape features and numerically predicted risk of ascending aortic aneurysm.

Authors:  Liang Liang; Minliang Liu; Caitlin Martin; John A Elefteriades; Wei Sun
Journal:  Biomech Model Mechanobiol       Date:  2017-04-06

5.  Patient-specific finite element analysis of ascending aorta aneurysms.

Authors:  Caitlin Martin; Wei Sun; John Elefteriades
Journal:  Am J Physiol Heart Circ Physiol       Date:  2015-03-13       Impact factor: 4.733

Review 6.  Hyperelastic modelling of arterial layers with distributed collagen fibre orientations.

Authors:  T Christian Gasser; Ray W Ogden; Gerhard A Holzapfel
Journal:  J R Soc Interface       Date:  2006-02-22       Impact factor: 4.118

7.  On the prospect of patient-specific biomechanics without patient-specific properties of tissues.

Authors:  Karol Miller; Jia Lu
Journal:  J Mech Behav Biomed Mater       Date:  2013-02-09

8.  A simple, effective and clinically applicable method to compute abdominal aortic aneurysm wall stress.

Authors:  Grand Roman Joldes; Karol Miller; Adam Wittek; Barry Doyle
Journal:  J Mech Behav Biomed Mater       Date:  2015-08-05

9.  Effect of layer heterogeneity on the biomechanical properties of ascending thoracic aortic aneurysms.

Authors:  Dimitrios P Sokolis; Eleftherios P Kritharis; Dimitrios C Iliopoulos
Journal:  Med Biol Eng Comput       Date:  2012-08-25       Impact factor: 2.602

10.  Variation of mechanical properties along the length of the aorta in C57bl/6 mice.

Authors:  Xiaomei Guo; Ghassan S Kassab
Journal:  Am J Physiol Heart Circ Physiol       Date:  2003-12       Impact factor: 4.733

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  3 in total

1.  Estimation of in vivo constitutive parameters of the aortic wall using a machine learning approach.

Authors:  Minliang Liu; Liang Liang; Wei Sun
Journal:  Comput Methods Appl Mech Eng       Date:  2018-12-28       Impact factor: 6.756

2.  Engineering analysis of aortic wall stress and root dilatation in the V-shape surgery for treatment of ascending aortic aneurysms.

Authors:  Hai Dong; Minliang Liu; Tongran Qin; Liang Liang; Bulat Ziganshin; Hesham Ellauzi; Mohammad Zafar; Sophie Jang; John Elefteriades; Wei Sun
Journal:  Interact Cardiovasc Thorac Surg       Date:  2022-06-01

3.  Identification of in vivo nonlinear anisotropic mechanical properties of ascending thoracic aortic aneurysm from patient-specific CT scans.

Authors:  Minliang Liu; Liang Liang; Fatiesa Sulejmani; Xiaoying Lou; Glen Iannucci; Edward Chen; Bradley Leshnower; Wei Sun
Journal:  Sci Rep       Date:  2019-09-10       Impact factor: 4.996

  3 in total

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