Suppr超能文献

评估主动脉壁的体内力学特性:一种多分辨率直接搜索方法。

Estimation of in vivo mechanical properties of the aortic wall: A multi-resolution direct search approach.

机构信息

Tissue Mechanics Laboratory, The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States.

Tissue Mechanics Laboratory, The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States.

出版信息

J Mech Behav Biomed Mater. 2018 Jan;77:649-659. doi: 10.1016/j.jmbbm.2017.10.022. Epub 2017 Oct 20.

Abstract

The patient-specific biomechanical analysis of the aorta requires in vivo mechanical properties of individual patients. Existing approaches for estimating in vivo material properties often demand high computational cost and mesh correspondence of the aortic wall between different cardiac phases. In this paper, we propose a novel multi-resolution direct search (MRDS) approach for estimation of the nonlinear, anisotropic constitutive parameters of the aortic wall. Based on the finite element (FE) updating scheme, the MRDS approach consists of the following three steps: (1) representing constitutive parameters with multiple resolutions using principal component analysis (PCA), (2) building links between the discretized PCA spaces at different resolutions, and (3) searching the PCA spaces in a 'coarse to fine' fashion following the links. The estimation of material parameters is achieved by minimizing a node-to-surface error function, which does not need mesh correspondence. The method was validated through a numerical experiment by using the in vivo data from a patient with ascending thoracic aortic aneurysm (ATAA), the results show that the number of FE iterations was significantly reduced compared to previous methods. The approach was also applied to the in vivo CT data from an aged healthy human patient, and using the estimated material parameters, the FE-computed geometry was well matched with the image-derived geometry. This novel MRDS approach may facilitate the personalized biomechanical analysis of aortic tissues, such as the rupture risk analysis of ATAA, which requires fast feedback to clinicians.

摘要

患者特定的主动脉生物力学分析需要个体患者的体内力学特性。现有的估计体内材料特性的方法通常需要主动脉壁在不同心动周期之间的高计算成本和网格对应。在本文中,我们提出了一种新颖的多分辨率直接搜索(MRDS)方法,用于估计主动脉壁的非线性各向异性本构参数。基于有限元(FE)更新方案,MRDS 方法包括以下三个步骤:(1)使用主成分分析(PCA)用多个分辨率表示本构参数,(2)在不同分辨率的离散 PCA 空间之间建立链接,以及(3)按照链接以“从粗到细”的方式搜索 PCA 空间。材料参数的估计是通过最小化节点到曲面误差函数来实现的,该函数不需要网格对应。该方法通过使用升主动脉瘤(ATAA)患者的体内数据进行数值实验进行了验证,结果表明与以前的方法相比,FE 迭代次数显著减少。该方法还应用于老年健康人体的体内 CT 数据,并且使用估计的材料参数,FE 计算的几何形状与图像衍生的几何形状很好地匹配。这种新颖的 MRDS 方法可以促进主动脉组织的个性化生物力学分析,例如 ATAA 的破裂风险分析,这需要快速反馈给临床医生。

相似文献

1
Estimation of in vivo mechanical properties of the aortic wall: A multi-resolution direct search approach.
J Mech Behav Biomed Mater. 2018 Jan;77:649-659. doi: 10.1016/j.jmbbm.2017.10.022. Epub 2017 Oct 20.
2
A new inverse method for estimation of in vivo mechanical properties of the aortic wall.
J Mech Behav Biomed Mater. 2017 Aug;72:148-158. doi: 10.1016/j.jmbbm.2017.05.001. Epub 2017 May 2.
3
Ascending thoracic aortic aneurysm wall stress analysis using patient-specific finite element modeling of in vivo magnetic resonance imaging.
Interact Cardiovasc Thorac Surg. 2015 Oct;21(4):471-80. doi: 10.1093/icvts/ivv186. Epub 2015 Jul 14.
5
On the role of material properties in ascending thoracic aortic aneurysms.
Comput Biol Med. 2019 Jun;109:70-78. doi: 10.1016/j.compbiomed.2019.04.022. Epub 2019 Apr 24.
8
High levels of 18F-FDG uptake in aortic aneurysm wall are associated with high wall stress.
Eur J Vasc Endovasc Surg. 2010 Mar;39(3):295-301. doi: 10.1016/j.ejvs.2009.10.016. Epub 2009 Nov 18.
9
In Vivo Strain Analysis of Dilated Ascending Thoracic Aorta by ECG-Gated CT Angiographic Imaging.
Ann Biomed Eng. 2017 Dec;45(12):2911-2920. doi: 10.1007/s10439-017-1915-4. Epub 2017 Sep 7.

引用本文的文献

2
Estimating nonlinear anisotropic properties of healthy and aneurysm ascending aortas using magnetic resonance imaging.
Biomech Model Mechanobiol. 2025 Feb;24(1):233-250. doi: 10.1007/s10237-024-01907-6. Epub 2024 Nov 26.
3
Characterizing atherosclerotic tissues: analysis of mechanical properties using intravascular ultrasound and inverse finite element methods.
Front Bioeng Biotechnol. 2023 Dec 13;11:1304278. doi: 10.3389/fbioe.2023.1304278. eCollection 2023.
4
5
PyTorch-FEA: Autograd-enabled finite element analysis methods with applications for biomechanical analysis of human aorta.
Comput Methods Programs Biomed. 2023 Aug;238:107616. doi: 10.1016/j.cmpb.2023.107616. Epub 2023 May 18.
7
A generic physics-informed neural network-based constitutive model for soft biological tissues.
Comput Methods Appl Mech Eng. 2020 Dec 1;372. doi: 10.1016/j.cma.2020.113402. Epub 2020 Sep 10.
8
Recent Advances in Biomechanical Characterization of Thoracic Aortic Aneurysms.
Front Cardiovasc Med. 2020 May 12;7:75. doi: 10.3389/fcvm.2020.00075. eCollection 2020.
10
Estimation of constitutive parameters of the aortic wall using a machine learning approach.
Comput Methods Appl Mech Eng. 2019 Apr 15;347:201-217. doi: 10.1016/j.cma.2018.12.030. Epub 2018 Dec 28.

本文引用的文献

1
A new inverse method for estimation of in vivo mechanical properties of the aortic wall.
J Mech Behav Biomed Mater. 2017 Aug;72:148-158. doi: 10.1016/j.jmbbm.2017.05.001. Epub 2017 May 2.
2
A machine learning approach to investigate the relationship between shape features and numerically predicted risk of ascending aortic aneurysm.
Biomech Model Mechanobiol. 2017 Oct;16(5):1519-1533. doi: 10.1007/s10237-017-0903-9. Epub 2017 Apr 6.
3
Regional distribution of circumferential residual strains in the human aorta according to age and gender.
J Mech Behav Biomed Mater. 2017 Mar;67:87-100. doi: 10.1016/j.jmbbm.2016.12.003. Epub 2016 Dec 8.
4
Towards patient-specific modeling of mitral valve repair: 3D transesophageal echocardiography-derived parameter estimation.
Med Image Anal. 2017 Jan;35:599-609. doi: 10.1016/j.media.2016.09.006. Epub 2016 Sep 27.
5
Local mechanical properties of human ascending thoracic aneurysms.
J Mech Behav Biomed Mater. 2016 Aug;61:235-249. doi: 10.1016/j.jmbbm.2016.03.025. Epub 2016 Apr 1.
6
Imaging Techniques for Diagnosis of Thoracic Aortic Atherosclerosis.
Int J Vasc Med. 2016;2016:4726094. doi: 10.1155/2016/4726094. Epub 2016 Feb 4.
7
Influence of limited field-of-view on wall stress analysis in abdominal aortic aneurysms.
J Biomech. 2016 Aug 16;49(12):2405-12. doi: 10.1016/j.jbiomech.2016.01.020. Epub 2016 Feb 6.
9
A simple, effective and clinically applicable method to compute abdominal aortic aneurysm wall stress.
J Mech Behav Biomed Mater. 2016 May;58:139-148. doi: 10.1016/j.jmbbm.2015.07.029. Epub 2015 Aug 5.
10
Predictive Models with Patient Specific Material Properties for the Biomechanical Behavior of Ascending Thoracic Aneurysms.
Ann Biomed Eng. 2016 Jan;44(1):84-98. doi: 10.1007/s10439-015-1374-8. Epub 2015 Jul 16.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验