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动脉粥样硬化斑块局部力学特性表征框架:超声位移成像与有限元逆分析相结合

A Framework for Local Mechanical Characterization of Atherosclerotic Plaques: Combination of Ultrasound Displacement Imaging and Inverse Finite Element Analysis.

作者信息

Akyildiz Ali C, Hansen Hendrik H G, Nieuwstadt Harm A, Speelman Lambert, De Korte Chris L, van der Steen Antonius F W, Gijsen Frank J H

机构信息

Biomechanics Lab, Department of Biomedical Engineering, Thoraxcenter, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.

Department of Mechanical, Aerospace and Nuclear Engineering, Rensselaer Polytechnic Institute, Troy, USA.

出版信息

Ann Biomed Eng. 2016 Apr;44(4):968-79. doi: 10.1007/s10439-015-1410-8. Epub 2015 Sep 23.

DOI:10.1007/s10439-015-1410-8
PMID:26399991
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4826666/
Abstract

Biomechanical models have the potential to predict plaque rupture. For reliable models, correct material properties of plaque components are a prerequisite. This study presents a new technique, where high resolution ultrasound displacement imaging and inverse finite element (FE) modeling is combined, to estimate material properties of plaque components. Iliac arteries with plaques were excised from 6 atherosclerotic pigs and subjected to an inflation test with pressures ranging from 10 to 120 mmHg. The arteries were imaged with high frequency 40 MHz ultrasound. Deformation maps of the plaques were reconstructed by cross correlation of the ultrasound radiofrequency data. Subsequently, the arteries were perfusion fixed for histology and structural components were identified. The histological data were registered to the ultrasound data to construct FE model of the plaques. Material properties of the arterial wall and the intima of the atherosclerotic plaques were estimated using a grid search method. The computed displacement fields showed good agreement with the measured displacement fields, implying that the FE models were able to capture local inhomogeneities within the plaque. On average, nonlinear stiffening of both the wall and the intima was observed, and the wall of the atheroslcerotic porcine iliac arteries was markedly stiffer than the intima (877 ± 459 vs. 100 ± 68 kPa at 100 mmHg). The large spread in the data further illustrates the wide variation of the material properties. We demonstrated the feasibility of a mixed experimental-numerical framework to determine the material properties of arterial wall and intima of atherosclerotic plaques from intact arteries, and concluded that, due to the observed variation, plaque specific properties are required for accurate stress simulations.

摘要

生物力学模型有预测斑块破裂的潜力。对于可靠的模型而言,斑块成分正确的材料属性是一个前提条件。本研究提出了一种新技术,即将高分辨率超声位移成像与有限元逆建模相结合,以估计斑块成分的材料属性。从6只动脉粥样硬化猪身上切除带有斑块的髂动脉,并在10至120 mmHg的压力范围内进行膨胀试验。用40 MHz高频超声对动脉进行成像。通过超声射频数据的互相关重建斑块的变形图。随后,对动脉进行灌注固定以进行组织学检查并识别结构成分。将组织学数据与超声数据配准以构建斑块的有限元模型。使用网格搜索方法估计动脉壁和动脉粥样硬化斑块内膜的材料属性。计算得到的位移场与测量得到的位移场显示出良好的一致性,这意味着有限元模型能够捕捉斑块内的局部不均匀性。平均而言,观察到壁和内膜都存在非线性硬化,并且动脉粥样硬化猪髂动脉的壁明显比内膜硬(在100 mmHg时为877±459 vs. 100±68 kPa)。数据中的较大离散度进一步说明了材料属性的广泛变化。我们证明了一个混合实验 - 数值框架用于从完整动脉确定动脉粥样硬化斑块的动脉壁和内膜材料属性的可行性,并得出结论,由于观察到的变化,准确的应力模拟需要斑块特定的属性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1adc/4826666/7fdb18de19cf/10439_2015_1410_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1adc/4826666/65c8a1328dda/10439_2015_1410_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1adc/4826666/91bee19e11b5/10439_2015_1410_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1adc/4826666/ce2dd3429acc/10439_2015_1410_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1adc/4826666/8c9e38c25aa4/10439_2015_1410_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1adc/4826666/7fdb18de19cf/10439_2015_1410_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1adc/4826666/65c8a1328dda/10439_2015_1410_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1adc/4826666/91bee19e11b5/10439_2015_1410_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1adc/4826666/ce2dd3429acc/10439_2015_1410_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1adc/4826666/8c9e38c25aa4/10439_2015_1410_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1adc/4826666/7fdb18de19cf/10439_2015_1410_Fig5_HTML.jpg

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