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 (+ or - 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 + or - 25%) than AWSSG (68 + or - 36%), OSI (60 + or - 30%, p<0.05), and RRT (69 + or - 59%); while OSI had a higher positive predict value (PPV) (68 + or - 34%) than AWSS (47 + or - 27%, p<0.001), AWSSG (37 + or - 23, p<0.001) and RRT (59 + or - 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. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.
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 (+ or - 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 + or - 25%) than AWSSG (68 + or - 36%), OSI (60 + or - 30%, p<0.05), and RRT (69 + or - 59%); while OSI had a higher positive predict value (PPV) (68 + or - 34%) than AWSS (47 + or - 27%, p<0.001), AWSSG (37 + or - 23, p<0.001) and RRT (59 + or - 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. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.
Authors: Nicolas Baeyens; Chirosree Bandyopadhyay; Brian G Coon; Sanguk Yun; Martin A Schwartz Journal: J Clin Invest Date: 2016-03-01 Impact factor: 14.808
Authors: Margaret N Holme; Georg Schulz; Hans Deyhle; Timm Weitkamp; Felix Beckmann; Johannes A Lobrinus; Farhad Rikhtegar; Vartan Kurtcuoglu; Irene Zanette; Till Saxer; Bert Müller Journal: Nat Protoc Date: 2014-05-22 Impact factor: 13.491
Authors: P Assemat; K K Siu; J A Armitage; S N Hokke; A Dart; J Chin-Dusting; K Hourigan Journal: Comput Struct Biotechnol J Date: 2014-08-02 Impact factor: 7.271