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本文引用的文献

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Prediction of Atherosclerotic Plaque Development in an In Vivo Coronary Arterial Segment Based on a Multilevel Modeling Approach.基于多水平建模方法对体内冠状动脉节段动脉粥样硬化斑块发展的预测
IEEE Trans Biomed Eng. 2017 Aug;64(8):1721-1730. doi: 10.1109/TBME.2016.2619489. Epub 2016 Oct 19.
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Numerical simulations of a 3D fluid-structure interaction model for blood flow in an atherosclerotic artery.动脉粥样硬化动脉中血流的三维流固耦合模型的数值模拟。
Math Biosci Eng. 2017 Feb 1;14(1):179-193. doi: 10.3934/mbe.2017012.
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Quantify patient-specific coronary material property and its impact on stress/strain calculations using in vivo IVUS data and 3D FSI models: a pilot study.利用体内血管内超声(IVUS)数据和三维流体结构相互作用(FSI)模型量化患者特异性冠状动脉材料特性及其对应力/应变计算的影响:一项初步研究。
Biomech Model Mechanobiol. 2017 Feb;16(1):333-344. doi: 10.1007/s10237-016-0820-3. Epub 2016 Aug 25.
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Morphological and Stress Vulnerability Indices for Human Coronary Plaques and Their Correlations with Cap Thickness and Lipid Percent: An IVUS-Based Fluid-Structure Interaction Multi-patient Study.基于血管内超声的多患者流体-结构相互作用研究:人类冠状动脉斑块的形态学和应力易损性指数及其与帽厚度和脂质百分比的相关性
PLoS Comput Biol. 2015 Dec 9;11(12):e1004652. doi: 10.1371/journal.pcbi.1004652. eCollection 2015 Dec.
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Carotid Plaque Morphological Classification Compared With Biomechanical Cap Stress: Implications for a Magnetic Resonance Imaging-Based Assessment.颈动脉斑块形态学分类与生物力学帽状应力的比较:基于磁共振成像评估的意义
Stroke. 2015 Aug;46(8):2124-8. doi: 10.1161/STROKEAHA.115.009707. Epub 2015 Jun 16.
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IVUS-based FSI models for human coronary plaque progression study: components, correlation and predictive analysis.基于血管内超声的血流动力学模拟模型用于人类冠状动脉斑块进展研究:组成部分、相关性及预测分析
Ann Biomed Eng. 2015 Jan;43(1):107-21. doi: 10.1007/s10439-014-1118-1. Epub 2014 Sep 23.
7
Material properties of components in human carotid atherosclerotic plaques: a uniaxial extension study.人类颈动脉粥样硬化斑块中各成分的材料特性:一项单轴拉伸研究。
Acta Biomater. 2014 Dec;10(12):5055-5063. doi: 10.1016/j.actbio.2014.09.001. Epub 2014 Sep 6.
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Image-based modeling for better understanding and assessment of atherosclerotic plaque progression and vulnerability: data, modeling, validation, uncertainty and predictions.基于图像的建模可更好地理解和评估动脉粥样硬化斑块的进展和易损性:数据、建模、验证、不确定性和预测。
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9
Combination of plaque burden, wall shear stress, and plaque phenotype has incremental value for prediction of coronary atherosclerotic plaque progression and vulnerability.斑块负荷、壁面剪应力和斑块表型的组合对于预测冠状动脉粥样硬化斑块进展和易损性具有增量价值。
Atherosclerosis. 2014 Feb;232(2):271-6. doi: 10.1016/j.atherosclerosis.2013.11.049. Epub 2013 Dec 1.
10
Prediction of progression of coronary artery disease and clinical outcomes using vascular profiling of endothelial shear stress and arterial plaque characteristics: the PREDICTION Study.利用内皮剪切应力和动脉斑块特征的血管分析预测冠状动脉疾病进展和临床结局:PREDICTION 研究。
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基于患者特异性血管内超声在基线和随访时的流体-结构相互作用模型,通过形态学和生物力学因素预测冠状动脉斑块进展:一项初步研究。

Fluid-structure interaction models based on patient-specific IVUS at baseline and follow-up for prediction of coronary plaque progression by morphological and biomechanical factors: A preliminary study.

作者信息

Wang Liang, Tang Dalin, Maehara Akiko, Wu Zheyang, Yang Chun, Muccigrosso David, Zheng Jie, Bach Richard, Billiar Kristen L, Mintz Gary S

机构信息

School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; Mathematical Sciences Department, Worcester Polytechnic Institute, MA, USA.

School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; Mathematical Sciences Department, Worcester Polytechnic Institute, MA, USA.

出版信息

J Biomech. 2018 Feb 8;68:43-50. doi: 10.1016/j.jbiomech.2017.12.007. Epub 2017 Dec 15.

DOI:10.1016/j.jbiomech.2017.12.007
PMID:29274686
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5783767/
Abstract

Plaque morphology and biomechanics are believed to be closely associated with plaque progression. In this paper, we test the hypothesis that integrating morphological and biomechanical risk factors would result in better predictive power for plaque progression prediction. A sample size of 374 intravascular ultrasound (IVUS) slices was obtained from 9 patients with IVUS follow-up data. 3D fluid-structure interaction models were constructed to obtain both structural stress/strain and fluid biomechanical conditions. Data for eight morphological and biomechanical risk factors were extracted for each slice. Plaque area increase (PAI) and wall thickness increase (WTI) were chosen as two measures for plaque progression. Progression measure and risk factors were fed to generalized linear mixed models and linear mixed-effect models to perform prediction and correlation analysis, respectively. All combinations of eight risk factors were exhausted to identify the optimal predictor(s) with highest prediction accuracy defined as sum of sensitivity and specificity. When using a single risk factor, plaque wall stress (PWS) at baseline was the best predictor for plaque progression (PAI and WTI). The optimal predictor among all possible combinations for PAI was PWS + PWSn + Lipid percent + Min cap thickness + Plaque Area (PA) + Plaque Burden (PB) (prediction accuracy = 1.5928) while Wall Thickness (WT) + Plaque Wall Strain (PWSn) + Plaque Area (PA) was the best for WTI (1.2589). This indicated that PAI was a more predictable measure than WTI. The combination including both morphological and biomechanical parameters had improved prediction accuracy, compared to predictions using only morphological features.

摘要

斑块形态学和生物力学被认为与斑块进展密切相关。在本文中,我们检验了这样一个假设,即整合形态学和生物力学风险因素将对斑块进展预测产生更好的预测能力。从9例有血管内超声(IVUS)随访数据的患者中获取了374个血管内超声切片样本。构建了三维流固相互作用模型,以获得结构应力/应变和流体生物力学条件。为每个切片提取了八个形态学和生物力学风险因素的数据。选择斑块面积增加(PAI)和管壁厚度增加(WTI)作为斑块进展的两个指标。将进展指标和风险因素分别输入广义线性混合模型和线性混合效应模型进行预测和相关性分析。穷尽八个风险因素的所有组合,以确定预测准确性最高的最佳预测指标,预测准确性定义为敏感性和特异性之和。当使用单一风险因素时,基线时的斑块壁应力(PWS)是斑块进展(PAI和WTI)的最佳预测指标。PAI所有可能组合中的最佳预测指标是PWS + PWSn + 脂质百分比 + 最小帽厚度 + 斑块面积(PA)+ 斑块负荷(PB)(预测准确性 = 1.5928),而管壁厚度(WT)+ 斑块壁应变(PWSn)+ 斑块面积(PA)对WTI是最佳的(1.2589)。这表明PAI比WTI是更可预测的指标。与仅使用形态学特征的预测相比,包括形态学和生物力学参数的组合提高了预测准确性。

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