Browsing by Author "Saba, L."

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A Review on Carotid Ultrasound Atherosclerotic Tissue Characterization and Stroke Risk Stratification in Machine Learning Framework
(Current Medicine Group LLC 1 info@phl.cursci.com, 2015) Sharma, A.M.; Gupta, A.; Kumar, P.K.; Rajan, J.; Saba, L.; Nobutaka, I.; Laird, J.R.; Nicolades, A.; Suri, J.S.
Cardiovascular diseases (including stroke and heart attack) are identified as the leading cause of death in today’s world. However, very little is understood about the arterial mechanics of plaque buildup, arterial fibrous cap rupture, and the role of abnormalities of the vasa vasorum. Recently, ultrasonic echogenicity characteristics and morphological characterization of carotid plaque types have been shown to have clinical utility in classification of stroke risks. Furthermore, this characterization supports aggressive and intensive medical therapy as well as procedures, including endarterectomy and stenting. This is the first state-of-the-art review to provide a comprehensive understanding of the field of ultrasonic vascular morphology tissue characterization. This paper presents fundamental and advanced ultrasonic tissue characterization and feature extraction methods for analyzing plaque. Additionally, the paper shows how the risk stratification is achieved using machine learning paradigms. More advanced methods need to be developed which can segment the carotid artery walls into multiple regions such as the bulb region and areas both proximal and distal to the bulb. Furthermore, multimodality imaging is needed for validation of such advanced methods for stroke and cardiovascular risk stratification. © 2015, Springer Science+Business Media New York.
A Review on Carotid Ultrasound Atherosclerotic Tissue Characterization and Stroke Risk Stratification in Machine Learning Framework
(Current Medicine Group LLC 1 info@phl.cursci.com, 2015) Sharma, A.M.; Gupta, A.; Kumar, P.K.; Rajan, J.; Saba, L.; Nobutaka, I.; Laird, J.R.; Nicolades, A.; Suri, J.S.
Cardiovascular diseases (including stroke and heart attack) are identified as the leading cause of death in todayâ€™s world. However, very little is understood about the arterial mechanics of plaque buildup, arterial fibrous cap rupture, and the role of abnormalities of the vasa vasorum. Recently, ultrasonic echogenicity characteristics and morphological characterization of carotid plaque types have been shown to have clinical utility in classification of stroke risks. Furthermore, this characterization supports aggressive and intensive medical therapy as well as procedures, including endarterectomy and stenting. This is the first state-of-the-art review to provide a comprehensive understanding of the field of ultrasonic vascular morphology tissue characterization. This paper presents fundamental and advanced ultrasonic tissue characterization and feature extraction methods for analyzing plaque. Additionally, the paper shows how the risk stratification is achieved using machine learning paradigms. More advanced methods need to be developed which can segment the carotid artery walls into multiple regions such as the bulb region and areas both proximal and distal to the bulb. Furthermore, multimodality imaging is needed for validation of such advanced methods for stroke and cardiovascular risk stratification. Â© 2015, Springer Science+Business Media New York.
Accurate lumen diameter measurement in curved vessels in carotid ultrasound: an iterative scale-space and spatial transformation approach
(2017) Krishna, Kumar, P.; Araki, T.; Rajan, J.; Saba, L.; Lavra, F.; Ikeda, N.; Sharma, A.M.; Shafique, S.; Nicolaides, A.; Laird, J.R.; Gupta, A.; Suri, J.S.
Monitoring of cerebrovascular diseases via carotid ultrasound has started to become a routine. The measurement of image-based lumen diameter (LD) or inter-adventitial diameter (IAD) is a promising approach for quantification of the degree of stenosis. The manual measurements of LD/IAD are not reliable, subjective and slow. The curvature associated with the vessels along with non-uniformity in the plaque growth poses further challenges. This study uses a novel and generalized approach for automated LD and IAD measurement based on a combination of spatial transformation and scale-space. In this iterative procedure, the scale-space is first used to get the lumen axis which is then used with spatial image transformation paradigm to get a transformed image. The scale-space is then reapplied to retrieve the lumen region and boundary in the transformed framework. Then, inverse transformation is applied to display the results in original image framework. Two hundred and two patients left and right common carotid artery (404 carotid images) B-mode ultrasound images were retrospectively analyzed. The validation of our algorithm has done against the two manual expert tracings. The coefficient of correlation between the two manual tracings for LD was 0.98 (p < 0.0001) and 0.99 (p < 0.0001), respectively. The precision of merit between the manual expert tracings and the automated system was 97.7 and 98.7%, respectively. The experimental analysis demonstrated superior performance of the proposed method over conventional approaches. Several statistical tests demonstrated the stability and reliability of the automated system. 2016, International Federation for Medical and Biological Engineering.
Accurate lumen diameter measurement in curved vessels in carotid ultrasound: an iterative scale-space and spatial transformation approach
(Springer Verlag service@springer.de, 2017) Krishna Kumar, P.; Araki, T.; Rajan, J.; Saba, L.; Lavra, F.; Ikeda, N.; Sharma, A.M.; Shafique, S.; Nicolaïdes, A.; Laird, J.R.; Gupta, A.; Suri, J.S.
Monitoring of cerebrovascular diseases via carotid ultrasound has started to become a routine. The measurement of image-based lumen diameter (LD) or inter-adventitial diameter (IAD) is a promising approach for quantification of the degree of stenosis. The manual measurements of LD/IAD are not reliable, subjective and slow. The curvature associated with the vessels along with non-uniformity in the plaque growth poses further challenges. This study uses a novel and generalized approach for automated LD and IAD measurement based on a combination of spatial transformation and scale-space. In this iterative procedure, the scale-space is first used to get the lumen axis which is then used with spatial image transformation paradigm to get a transformed image. The scale-space is then reapplied to retrieve the lumen region and boundary in the transformed framework. Then, inverse transformation is applied to display the results in original image framework. Two hundred and two patients’ left and right common carotid artery (404 carotid images) B-mode ultrasound images were retrospectively analyzed. The validation of our algorithm has done against the two manual expert tracings. The coefficient of correlation between the two manual tracings for LD was 0.98 (p < 0.0001) and 0.99 (p < 0.0001), respectively. The precision of merit between the manual expert tracings and the automated system was 97.7 and 98.7%, respectively. The experimental analysis demonstrated superior performance of the proposed method over conventional approaches. Several statistical tests demonstrated the stability and reliability of the automated system. © 2016, International Federation for Medical and Biological Engineering.
Carotid inter-adventitial diameter is more strongly related to plaque score than lumen diameter: An automated tool for stroke analysis
(2016) Saba, L.; Araki, T.; Krishna, Kumar, P.; Rajan, J.; Lavra, F.; Ikeda, N.; Sharma, A.M.; Shafique, S.; Nicolaides, A.; Laird, J.R.; Gupta, A.; Suri, J.S.
Purpose: To compare the strength of correlation between automatically measured carotid lumen diameter (LD) and interadventitial diameter (IAD) with plaque score (PS). Methods: Retrospective study on a database of 404 common carotid artery B-mode sonographic images from 202 diabetic patients. LD and IAD were computed automatically using an advanced computerized edge detection method and compared with two distinct manual measurements. PS was computed by adding the maximal thickness in millimeters of plaques in segments taken from the internal carotid artery, bulb, and common carotid artery on both sides. Results: The coefficient of correlation was 0.19 (p < 0.007) between LD and PS, and 0.25 (p < 0.0006) between IAD and PS. After excluding 10 outliers, coefficient of correlation was 0.25 (p < 0.0001) between LD and PS, and 0.38 (p < 0.0001) between IAD and PS. The precision of merit of automated versus the two manual measurements was 96.6% and 97.2% for LD, and 97.7% and 98.1%, for IAD, respectively. Conclusions: Our automated measurement system gave satisfying results in comparison with manual measurements. Carotid IAD was more strongly correlated to PS than carotid LD in this population sample of Japanese diabetic patients. 2016 Wiley Periodicals, Inc.
Carotid inter-adventitial diameter is more strongly related to plaque score than lumen diameter: An automated tool for stroke analysis
(John Wiley and Sons Inc. P.O.Box 18667 Newark NJ 07191-8667, 2016) Saba, L.; Araki, T.; Krishna Kumar, P.; Rajan, J.; Lavra, F.; Ikeda, N.; Sharma, A.M.; Shafique, S.; Nicolaïdes, A.; Laird, J.R.; Gupta, A.; Suri, J.S.
Purpose: To compare the strength of correlation between automatically measured carotid lumen diameter (LD) and interadventitial diameter (IAD) with plaque score (PS). Methods: Retrospective study on a database of 404 common carotid artery B-mode sonographic images from 202 diabetic patients. LD and IAD were computed automatically using an advanced computerized edge detection method and compared with two distinct manual measurements. PS was computed by adding the maximal thickness in millimeters of plaques in segments taken from the internal carotid artery, bulb, and common carotid artery on both sides. Results: The coefficient of correlation was 0.19 (p < 0.007) between LD and PS, and 0.25 (p < 0.0006) between IAD and PS. After excluding 10 outliers, coefficient of correlation was 0.25 (p < 0.0001) between LD and PS, and 0.38 (p < 0.0001) between IAD and PS. The precision of merit of automated versus the two manual measurements was 96.6% and 97.2% for LD, and 97.7% and 98.1%, for IAD, respectively. Conclusions: Our automated measurement system gave satisfying results in comparison with manual measurements. Carotid IAD was more strongly correlated to PS than carotid LD in this population sample of Japanese diabetic patients. © 2016 Wiley Periodicals, Inc.
Magnetic resonance image denoising using nonlocal maximum likelihood paradigm in DCT-framework
(2015) Kumar, P.K.; Darshan, P.; Kumar, S.; Ravindra, R.; Rajan, J.; Saba, L.; Suri, J.S.
The data acquired by magnetic resonance (MR) imaging system are inherently degraded by noise that has its origin in the thermal Brownian motion of electrons. Denoising can enhance the quality (by improving the SNR) of the acquired MR image, which is important for both visual analysis and other post processing operations. Recent works on maximum likelihood (ML) based denoising shows that ML methods are very effective in denoising MR images and has an edge over the other state-of-the-art methods for MRI denoising. Among the ML based approaches, the Nonlocal maximum likelihood (NLML) method is commonly used. In the conventional NLML method, the samples for the ML estimation of the unknown true pixel are chosen in a nonlocal fashion based on the intensity similarity of the pixel neighborhoods. Euclidean distance is generally used to measure this similarity. It has been recently shown that computing similarity measure is more robust in discrete cosine transform (DCT) subspace, compared with Euclidean image subspace. Motivated by this observation, we integrated DCT into NLML to produce an improved MRI filtration process. Other than improving the SNR, the time complexity of the conventional NLML can also be significantly reduced through the proposed approach. On synthetic MR brain image, an average improvement of 5% in PSNR and 86%reduction in execution time is achieved with a search window size of 91 91 after incorporating the improvements in the existing NLML method. On an experimental kiwi fruit image an improvement of 10% in PSNR is achieved. We did experiments on both simulated and real data sets to validate and to demonstrate the effectiveness of the proposed method. 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 256-264, 2015 2015 Wiley Periodicals, Inc.
Magnetic resonance image denoising using nonlocal maximum likelihood paradigm in DCT-framework
(John Wiley and Sons Inc, 2015) Kumar, P.K.; Darshan, P.; Kumar, S.; Ravindra, R.; Rajan, J.; Saba, L.; Suri, J.S.
The data acquired by magnetic resonance (MR) imaging system are inherently degraded by noise that has its origin in the thermal Brownian motion of electrons. Denoising can enhance the quality (by improving the SNR) of the acquired MR image, which is important for both visual analysis and other post processing operations. Recent works on maximum likelihood (ML) based denoising shows that ML methods are very effective in denoising MR images and has an edge over the other state-of-the-art methods for MRI denoising. Among the ML based approaches, the Nonlocal maximum likelihood (NLML) method is commonly used. In the conventional NLML method, the samples for the ML estimation of the unknown true pixel are chosen in a nonlocal fashion based on the intensity similarity of the pixel neighborhoods. Euclidean distance is generally used to measure this similarity. It has been recently shown that computing similarity measure is more robust in discrete cosine transform (DCT) subspace, compared with Euclidean image subspace. Motivated by this observation, we integrated DCT into NLML to produce an improved MRI filtration process. Other than improving the SNR, the time complexity of the conventional NLML can also be significantly reduced through the proposed approach. On synthetic MR brain image, an average improvement of 5% in PSNR and 86%reduction in execution time is achieved with a search window size of 91 × 91 after incorporating the improvements in the existing NLML method. On an experimental kiwi fruit image an improvement of 10% in PSNR is achieved. We did experiments on both simulated and real data sets to validate and to demonstrate the effectiveness of the proposed method. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 256-264, 2015 © 2015 Wiley Periodicals, Inc.
Numerical analysis of the effect of turbulence transition on the hemodynamic parameters in human coronary arteries
(2016) Mahalingam, A.; Gawandalkar, U.U.; Kini, G.; Buradi, A.; Araki, T.; Ikeda, N.; Nicolaides, A.; Laird, J.R.; Saba, L.; Suri, J.S.
Background: Local hemodynamics plays an important role in atherogenesis and the progression of coronary atherosclerosis disease (CAD). The primary biological effect due to blood turbulence is the change in wall shear stress (WSS) on the endothelial cell membrane, while the local oscillatory nature of the blood flow affects the physiological changes in the coronary artery. In coronary arteries, the blood flow Reynolds number ranges from few tens to several hundreds and hence it is generally assumed to be laminar while calculating the WSS calculations. However, the pulsatile blood flow through coronary arteries under stenotic condition could result in transition from laminar to turbulent flow condition. Methods: In the present work, the onset of turbulent transition during pulsatile flow through coronary arteries for varying degree of stenosis (i.e., 0%, 30%, 50% and 70%) is quantitatively analyzed by calculating the turbulent parameters distal to the stenosis. Also, the effect of turbulence transition on hemodynamic parameters such as WSS and oscillatory shear index (OSI) for varying degree of stenosis is quantified. The validated transitional shear stress transport (SST) k-? model used in the present investigation is the best suited Reynolds averaged Navier-Stokes turbulence model to capture the turbulent transition. The arterial wall is assumed to be rigid and the dynamic curvature effect due to myocardial contraction on the blood flow has been neglected. Results: Our observations shows that for stenosis 50% and above, the WSSavg, WSSmax and OSI calculated using turbulence model deviates from laminar by more than 10% and the flow disturbances seems to significantly increase only after 70% stenosis. Our model shows reliability and completely validated. Conclusions: Blood flow through stenosed coronary arteries seems to be turbulent in nature for area stenosis above 70% and the transition to turbulent flow begins from 50% stenosis. Cardiovascular Diagnosis and Therapy. All rights reserved.
Numerical analysis of the effect of turbulence transition on the hemodynamic parameters in human coronary arteries
(AME Publishing Company info@amepc.org, 2016) Mahalingam, A.; Gawandalkar, U.U.; Kini, G.; Buradi, A.; Araki, T.; Ikeda, N.; Nicolaïdes, A.; Laird, J.R.; Saba, L.; Suri, J.S.
Background: Local hemodynamics plays an important role in atherogenesis and the progression of coronary atherosclerosis disease (CAD). The primary biological effect due to blood turbulence is the change in wall shear stress (WSS) on the endothelial cell membrane, while the local oscillatory nature of the blood flow affects the physiological changes in the coronary artery. In coronary arteries, the blood flow Reynolds number ranges from few tens to several hundreds and hence it is generally assumed to be laminar while calculating the WSS calculations. However, the pulsatile blood flow through coronary arteries under stenotic condition could result in transition from laminar to turbulent flow condition. Methods: In the present work, the onset of turbulent transition during pulsatile flow through coronary arteries for varying degree of stenosis (i.e., 0%, 30%, 50% and 70%) is quantitatively analyzed by calculating the turbulent parameters distal to the stenosis. Also, the effect of turbulence transition on hemodynamic parameters such as WSS and oscillatory shear index (OSI) for varying degree of stenosis is quantified. The validated transitional shear stress transport (SST) k-? model used in the present investigation is the best suited Reynolds averaged Navier-Stokes turbulence model to capture the turbulent transition. The arterial wall is assumed to be rigid and the dynamic curvature effect due to myocardial contraction on the blood flow has been neglected. Results: Our observations shows that for stenosis 50% and above, the WSSavg, WSSmax and OSI calculated using turbulence model deviates from laminar by more than 10% and the flow disturbances seems to significantly increase only after 70% stenosis. Our model shows reliability and completely validated. Conclusions: Blood flow through stenosed coronary arteries seems to be turbulent in nature for area stenosis above 70% and the transition to turbulent flow begins from 50% stenosis. © Cardiovascular Diagnosis and Therapy. All rights reserved.
Speckle reduction in medical ultrasound images using an unbiased non-local means method
(2016) Sudeep, P.V.; Palanisamy, P.; Rajan, J.; Baradaran, H.; Saba, L.; Gupta, A.; Suri, J.S.
Enhancement of ultrasound (US) images is required for proper visual inspection and further pre-processing since US images are generally corrupted with speckle. In this paper, a new approach based on non-local means (NLM) method is proposed to remove the speckle noise in the US images. Since the interpolated final Cartesian image produced from uncompressed ultrasound data contaminated with fully developed speckle can be represented by a Gamma distribution, a Gamma model is incorporated in the proposed denoising procedure. In addition, the scale and shape parameters of the Gamma distribution are estimated using the maximum likelihood (ML) method. Bias due to speckle noise is expressed using these parameters and is removed from the NLM filtered output. The experiments on phantom images and real 2D ultrasound datasets show that the proposed method outperforms other related well-accepted methods, both in terms of objective and subjective evaluations. The results demonstrate that the proposed method has a better performance in both speckle reduction and preservation of structural features. 2016 Elsevier Ltd. All rights reserved.
Speckle reduction in medical ultrasound images using an unbiased non-local means method
(Elsevier Ltd, 2016) Sudeep, P.V.; Ponnusamy, P.; Rajan, J.; Baradaran, H.; Saba, L.; Gupta, A.; Suri, J.S.
Enhancement of ultrasound (US) images is required for proper visual inspection and further pre-processing since US images are generally corrupted with speckle. In this paper, a new approach based on non-local means (NLM) method is proposed to remove the speckle noise in the US images. Since the interpolated final Cartesian image produced from uncompressed ultrasound data contaminated with fully developed speckle can be represented by a Gamma distribution, a Gamma model is incorporated in the proposed denoising procedure. In addition, the scale and shape parameters of the Gamma distribution are estimated using the maximum likelihood (ML) method. Bias due to speckle noise is expressed using these parameters and is removed from the NLM filtered output. The experiments on phantom images and real 2D ultrasound datasets show that the proposed method outperforms other related well-accepted methods, both in terms of objective and subjective evaluations. The results demonstrate that the proposed method has a better performance in both speckle reduction and preservation of structural features. © 2016 Elsevier Ltd. All rights reserved.
Two Automated Techniques for Carotid Lumen Diameter Measurement: Regional versus Boundary Approaches
(2016) Araki, T.; Kumar, P.K.; Suri, H.S.; Ikeda, N.; Gupta, A.; Saba, L.; Rajan, J.; Lavra, F.; Sharma, A.M.; Shafique, S.; Nicolaides, A.; Laird, J.R.; Suri, J.S.
The degree of stenosis in the carotid artery can be predicted using automated carotid lumen diameter (LD) measured from B-mode ultrasound images. Systolic velocity-based methods for measurement of LD are subjective. With the advancement of high resolution imaging, image-based methods have started to emerge. However, they require robust image analysis for accurate LD measurement. This paper presents two different algorithms for automated segmentation of the lumen borders in carotid ultrasound images. Both algorithms are modeled as a two stage process. Stage one consists of a global-based model using scale-space framework for the extraction of the region of interest. This stage is common to both algorithms. Stage two is modeled using a local-based strategy that extracts the lumen interfaces. At this stage, the algorithm-1 is modeled as a region-based strategy using a classification framework, whereas the algorithm-2 is modeled as a boundary-based approach that uses the level set framework. Two sets of databases (DB), Japan DB (JDB) (202 patients, 404 images) and Hong Kong DB (HKDB) (50 patients, 300 images) were used in this study. Two trained neuroradiologists performed manual LD tracings. The mean automated LD measured was 6.35��0.95�mm for JDB and 6.20��1.35�mm for HKDB. The precision-of-merit was: 97.4�% and 98.0�% w.r.t to two manual tracings for JDB and 99.7�% and 97.9�% w.r.t to two manual tracings for HKDB. Statistical tests such as ANOVA, Chi-Squared, T-test, and Mann-Whitney test were conducted to show the stability and reliability of the automated techniques. � 2016, Springer Science+Business Media New York.
Two Automated Techniques for Carotid Lumen Diameter Measurement: Regional versus Boundary Approaches
(Springer New York LLC barbara.b.bertram@gsk.com, 2016) Araki, T.; Kumar, P.K.; Suri, H.S.; Ikeda, N.; Gupta, A.; Saba, L.; Rajan, J.; Lavra, F.; Sharma, A.M.; Shafique, S.; Nicolaïdes, A.; Laird, J.R.; Suri, J.S.
The degree of stenosis in the carotid artery can be predicted using automated carotid lumen diameter (LD) measured from B-mode ultrasound images. Systolic velocity-based methods for measurement of LD are subjective. With the advancement of high resolution imaging, image-based methods have started to emerge. However, they require robust image analysis for accurate LD measurement. This paper presents two different algorithms for automated segmentation of the lumen borders in carotid ultrasound images. Both algorithms are modeled as a two stage process. Stage one consists of a global-based model using scale-space framework for the extraction of the region of interest. This stage is common to both algorithms. Stage two is modeled using a local-based strategy that extracts the lumen interfaces. At this stage, the algorithm-1 is modeled as a region-based strategy using a classification framework, whereas the algorithm-2 is modeled as a boundary-based approach that uses the level set framework. Two sets of databases (DB), Japan DB (JDB) (202 patients, 404 images) and Hong Kong DB (HKDB) (50 patients, 300 images) were used in this study. Two trained neuroradiologists performed manual LD tracings. The mean automated LD measured was 6.35 ± 0.95 mm for JDB and 6.20 ± 1.35 mm for HKDB. The precision-of-merit was: 97.4 % and 98.0 % w.r.t to two manual tracings for JDB and 99.7 % and 97.9 % w.r.t to two manual tracings for HKDB. Statistical tests such as ANOVA, Chi-Squared, T-test, and Mann-Whitney test were conducted to show the stability and reliability of the automated techniques. © 2016, Springer Science+Business Media New York.
Ultrasound-based automated carotid lumen diameter/stenosis measurement and its validation system
(2016) Araki, T.; Kumar, A.M.; Kumar, P.K.; Gupta, A.; Saba, L.; Rajan, J.; Lavra, F.; Sharma, A.M.; Shafique, S.; Nicolaides, A.; Laird, J.R.; Suri, J.S.
Objective.�Degree of carotid stenosis is an important predictor to assess risk of stroke. Systolic velocity-based methods for lumen diameter and stenosis measurement are subjective. Image-based methods face a challenge because of low gradients in media and intima walls. Methods.�This article presents AtheroEdge� 2.0, a two-stage process for automated carotid lumen diameter measurement that combats the above challenges. Stage one uses spectral analysis based on the hypothesis that far-wall adventitia is brightest. Stage two uses lumen pixel region identification based on the assumption that blood flow has constant density. Using global and local processing, lumen boundaries are detected. This clinical system outputs lumen diameter along with stenosis severity index (SSI). Results.�Our database consists of institutional review board�approved 202 patients (males/ females: 155/47) left and right common carotid artery images (404 images, Toshiba scanner). Two trained neuro radiologists performed manual lumen border tracings using ImgTracer� software. The coefficient of correlation between automated and two manual readings was 0.91 and 0.92. Dice similarity and Jaccard index were 95.82%, 95.72% and 92.10%, 91.92%, respectively. The mean diameter error between automated and two manual readings was 0.27 � 0.26 and 0.26 � 0.28 mm, respectively. Precision of merit was 98.05% and 99.03% with respect to two readings. SSI showed 97% accuracy. Conclusions.�The image-based automated carotid lumen diameter and stenosis measurement system is fast, accurate, and reliable. � 2018, SAGE Publications Ltd. All rights reserved.
Wall shear stress and oscillatory shear index distribution in carotid artery with varying degree of stenosis: A hemodynamic study
(2017) Basavaraja, P.; Surendran, A.; Gupta, A.; Saba, L.; Laird, J.R.; Nicolaides, A.; Mtui, E.E.; Baradaran, H.; Lavra, F.; Suri, J.S.
A significant proportion of cerebral stroke is a consequence of the arterial stenotic plaque rupture causing local thrombosis or distal embolization. The formation and subsequent rupture of the plaque depends on wall shear stress (WSS) and oscillatory shear index (OSI). The purpose of the present study was to understand the effect of hemodynamics on the spatial and temporal variations of WSS and OSI using realistic models with varying degree of carotid artery stenosis (DOS). Multiple CT volumes were obtained from subjects in the carotid bifurcation zone and the 3D models were generated. A finite volume-based computational fluid dynamics (CFD) method was utilized to understand the hemodynamics in pulsatile flow conditions. It was observed that high stenosis models occupied a large value of normalized WSS in the internal carotid artery (ICA) whereas they had smaller values of normalized WSS in the common carotid artery (CCA). For clinical use, the authors recommend using the spatial average value of oscillatory shear rather than the maximum value for an accurate knowledge about the severity of stenosis. The resultant vorticity changes the direction of spin after the bifurcation zone. Additionally, we propose the use of limiting streamlines as a novel and convenient method to identify the disturbed flow regions that are prone to atherogenesis. � 2017 World Scientific Publishing Company.
Wall shear stress and oscillatory shear index distribution in carotid artery with varying degree of stenosis: A hemodynamic study
(World Scientific Publishing Co. Pte Ltd wspc@wspc.com.sg, 2017) Basavaraja, P.; Anish, S.; Gupta, A.; Saba, L.; Laird, J.R.; Nicolaïdes, A.; Mtui, E.E.; Baradaran, H.; Lavra, F.; Suri, J.S.
A significant proportion of cerebral stroke is a consequence of the arterial stenotic plaque rupture causing local thrombosis or distal embolization. The formation and subsequent rupture of the plaque depends on wall shear stress (WSS) and oscillatory shear index (OSI). The purpose of the present study was to understand the effect of hemodynamics on the spatial and temporal variations of WSS and OSI using realistic models with varying degree of carotid artery stenosis (DOS). Multiple CT volumes were obtained from subjects in the carotid bifurcation zone and the 3D models were generated. A finite volume-based computational fluid dynamics (CFD) method was utilized to understand the hemodynamics in pulsatile flow conditions. It was observed that high stenosis models occupied a large value of normalized WSS in the internal carotid artery (ICA) whereas they had smaller values of normalized WSS in the common carotid artery (CCA). For clinical use, the authors recommend using the spatial average value of oscillatory shear rather than the maximum value for an accurate knowledge about the severity of stenosis. The resultant vorticity changes the direction of spin after the bifurcation zone. Additionally, we propose the use of limiting streamlines as a novel and convenient method to identify the disturbed flow regions that are prone to atherogenesis. © 2017 World Scientific Publishing Company.