Choosing the optimal wall shear parameter for the prediction of plaque location-A patient-specific computational study in human right coronary arteries

被引:75
作者
Knight, Joseph [1 ]
Olgac, Ufuk [1 ]
Saur, Stefan C. [2 ]
Poulikakos, Dimos [1 ]
Marshall, William, Jr. [3 ]
Cattin, Philippe C. [2 ,4 ]
Alkadhi, Hatem [5 ]
Kurtcuoglu, Vartan [1 ]
机构
[1] ETH, Dept Mech & Proc Engn, Lab Thermodynam Emerging Technol, CH-8092 Zurich, Switzerland
[2] ETH, Dept Informat Technol & Elect Engn, Comp Vis Lab, CH-8092 Zurich, Switzerland
[3] Univ S Florida, Coll Med, Tampa, FL 33620 USA
[4] Univ Basel, Med Image Anal Ctr, Basel, Switzerland
[5] Univ Zurich Hosp, Inst Diagnost Radiol, CH-8091 Zurich, Switzerland
基金
瑞士国家科学基金会;
关键词
Computed tomography; Wall shear-stress; Oscillatory shear index; Relative residence time; Computational fluid dynamics; Plaque prediction; BLOOD-FLOW PATTERNS; NATURAL-HISTORY; STRESS; ATHEROSCLEROSIS; HEMODYNAMICS; ACCUMULATION; PERMEABILITY; PROGRESSION; SIMULATION; SITES;
D O I
10.1016/j.atherosclerosis.2010.03.001
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: Average wall shear-stress (AWSS), average wall shear-stress gradient (AWSSG), oscillatory shear index (OSI) and relative residence time (RRT) are believed to predict areas vulnerable to plaque formation in the coronary arteries. Our aim was to analyze the correlation of these parameters in patients' vessels before the onset of atherosclerosis to the specific plaque sites thereafter, and to compare the parameters' sensitivity and positive predictive value. Methods: We obtained 30 patient-specific geometries (mean age 67.1 (+/- 9.2) years, all with stable angina) of the right coronary artery (RCA) using dual-source computed tomography (CT) and virtually removed any plaque present. We then performed computational fluid dynamics (CFD) simulations to calculate the wall shear parameters. Results: For the 120 total plaques, AWSS had on average a higher sensitivity for the prediction of plaque locations (72 +/- 25%) than AWSSG (68 +/- 36%), OSI (60 +/- 30%, p < 0.05), and RRT (69 +/- 59%); while OSI had a higher positive predict value (PPV) (68 +/- 34%) than AWSS(47 +/- 27%, p < 0.001), AWSSG(37 +/- 23, p < 0.001) and RRT (59 +/- 34%). A significant difference was also found between AWSSG and RRT (p < 0.01) concerning PPV. Conclusions: OSI and RRT are the optimal parameters when the number of false positives is to be minimized. AWSS accurately identifies the largest number of plaques, but produces more false positives than OSI and RRT. (C) 2010 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:445 / 450
页数:6
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