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Perinajová R, Álvarez-Cuevas CB, Juffermans J, Westenberg J, Lamb H, Kenjereš S. Influence of aortic aneurysm on the local distribution of NO and O 2 using image-based computational fluid dynamics. Comput Biol Med 2023; 160:106925. [PMID: 37141651 DOI: 10.1016/j.compbiomed.2023.106925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 04/04/2023] [Accepted: 04/13/2023] [Indexed: 05/06/2023]
Abstract
There is a pressing need to establish novel biomarkers to predict the progression of thoracic aortic aneurysm (TAA) dilatation. Aside from hemodynamics, the roles of oxygen (O2) and nitric oxide (NO) in TAA pathogenesis are potentially significant. As such, it is imperative to comprehend the relationship between aneurysm presence and species distribution in both the lumen and aortic wall. Given the limitations of existing imaging methods, we propose the use of patient-specific computational fluid dynamics (CFD) to explore this relationship. We have performed CFD simulations of O2 and NO mass transfer in the lumen and aortic wall for two cases: a healthy control (HC) and a patient with TAA, both acquired using 4D-flow magnetic resonance imaging (MRI). The mass transfer of O2 was based on active transport by hemoglobin, while the local variations of the wall shear stress (WSS) drove NO production. Comparing hemodynamic properties, the time-averaged WSS was considerably lower for TAA, while the oscillatory shear index and endothelial cell activation potential were notably elevated. O2 and NO showed a non-uniform distribution within the lumen and an inverse correlation between the two species. We identified several locations of hypoxic regions for both cases due to lumen-side mass transfer limitations. In the wall, NO varied spatially, with a clear distinction between TAA and HC. In conclusion, the hemodynamics and mass transfer of NO in the aorta exhibit the potential to serve as a diagnostic biomarker for TAA. Furthermore, hypoxia may provide additional insights into the onset of other aortic pathologies.
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Affiliation(s)
- Romana Perinajová
- Department of Chemical Engineering, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands; J.M. Burgerscentrum Research School for Fluid Mechanics, Delft, The Netherlands.
| | | | - Joe Juffermans
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Jos Westenberg
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Hildo Lamb
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Saša Kenjereš
- Department of Chemical Engineering, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands; J.M. Burgerscentrum Research School for Fluid Mechanics, Delft, The Netherlands
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Zhao YC, Zhang Y, Jiang F, Wu C, Wan B, Syeda R, Li Q, Shen B, Ju LA. A Novel Computational Biomechanics Framework to Model Vascular Mechanopropagation in Deep Bone Marrow. Adv Healthc Mater 2023; 12:e2201830. [PMID: 36521080 DOI: 10.1002/adhm.202201830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 12/05/2022] [Indexed: 12/23/2022]
Abstract
The mechanical stimuli generated by body exercise can be transmitted from cortical bone into the deep bone marrow (mechanopropagation). Excitingly, a mechanosensitive perivascular stem cell niche is recently identified within the bone marrow for osteogenesis and lymphopoiesis. Although it is long known that they are maintained by exercise-induced mechanical stimulation, the mechanopropagation from compact bone to deep bone marrow vasculature remains elusive of this fundamental mechanobiology field. No experimental system is available yet to directly understand such exercise-induced mechanopropagation at the bone-vessel interface. To this end, taking advantage of the revolutionary in vivo 3D deep bone imaging, an integrated computational biomechanics framework to quantitatively evaluate the mechanopropagation capabilities for bone marrow arterioles, arteries, and sinusoids is devised. As a highlight, the 3D geometries of blood vessels are smoothly reconstructed in the presence of vessel wall thickness and intravascular pulse pressure. By implementing the 5-parameter Mooney-Rivlin model that simulates the hyperelastic vessel properties, finite element analysis to thoroughly investigate the mechanical effects of exercise-induced intravascular vibratory stretching on bone marrow vasculature is performed. In addition, the blood pressure and cortical bone bending effects on vascular mechanoproperties are examined. For the first time, movement-induced mechanopropagation from the hard cortical bone to the soft vasculature in the bone marrow is numerically simulated. It is concluded that arterioles and arteries are much more efficient in propagating mechanical force than sinusoids due to their stiffness. In the future, this in-silico approach can be combined with other clinical imaging modalities for subject/patient-specific vascular reconstruction and biomechanical analysis, providing large-scale phenotypic data for personalized mechanobiology discovery.
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Affiliation(s)
- Yunduo Charles Zhao
- School of Biomedical Engineering, The University of Sydney, 2008, New South Wales, Darlington, Australia
- Charles Perkins Centre, The University of Sydney, 2006, New South Wales, Camperdown, Australia
- The University of Sydney Nano Institute (Sydney Nano), The University of Sydney, 2006, New South Wales, Camperdown, Australia
| | - Yingqi Zhang
- School of Biomedical Engineering, The University of Sydney, 2008, New South Wales, Darlington, Australia
- Charles Perkins Centre, The University of Sydney, 2006, New South Wales, Camperdown, Australia
- The University of Sydney Nano Institute (Sydney Nano), The University of Sydney, 2006, New South Wales, Camperdown, Australia
| | - Fengtao Jiang
- School of Biomedical Engineering, The University of Sydney, 2008, New South Wales, Darlington, Australia
- Charles Perkins Centre, The University of Sydney, 2006, New South Wales, Camperdown, Australia
- The University of Sydney Nano Institute (Sydney Nano), The University of Sydney, 2006, New South Wales, Camperdown, Australia
| | - Chi Wu
- School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, 2008, New South Wales, Darlington, Australia
| | - Boyang Wan
- School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, 2008, New South Wales, Darlington, Australia
| | - Ruhma Syeda
- Department of Neuroscience, University of Texas Southwestern Medical Center, 75235, TX, Dallas, USA
| | - Qing Li
- School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, 2008, New South Wales, Darlington, Australia
| | - Bo Shen
- National Institute of Biological Science, Zhongguancun Life Science Park, 102206, Beijing, China
- Tsinghua Institute of Multidisciplinary Biomedical Research, Tsinghua University, 102206, Beijing, China
| | - Lining Arnold Ju
- School of Biomedical Engineering, The University of Sydney, 2008, New South Wales, Darlington, Australia
- Charles Perkins Centre, The University of Sydney, 2006, New South Wales, Camperdown, Australia
- The University of Sydney Nano Institute (Sydney Nano), The University of Sydney, 2006, New South Wales, Camperdown, Australia
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Li X, Liu X, Deng X, Fan Y. Interplay between Artificial Intelligence and Biomechanics Modeling in the Cardiovascular Disease Prediction. Biomedicines 2022; 10:2157. [PMID: 36140258 PMCID: PMC9495955 DOI: 10.3390/biomedicines10092157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 08/26/2022] [Accepted: 08/28/2022] [Indexed: 11/16/2022] Open
Abstract
Cardiovascular disease (CVD) is the most common cause of morbidity and mortality worldwide, and early accurate diagnosis is the key point for improving and optimizing the prognosis of CVD. Recent progress in artificial intelligence (AI), especially machine learning (ML) technology, makes it possible to predict CVD. In this review, we first briefly introduced the overview development of artificial intelligence. Then we summarized some ML applications in cardiovascular diseases, including ML-based models to directly predict CVD based on risk factors or medical imaging findings and the ML-based hemodynamics with vascular geometries, equations, and methods for indirect assessment of CVD. We also discussed case studies where ML could be used as the surrogate for computational fluid dynamics in data-driven models and physics-driven models. ML models could be a surrogate for computational fluid dynamics, accelerate the process of disease prediction, and reduce manual intervention. Lastly, we briefly summarized the research difficulties and prospected the future development of AI technology in cardiovascular diseases.
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Affiliation(s)
- Xiaoyin Li
- Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry, School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, China
| | - Xiao Liu
- Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry, School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, China
| | - Xiaoyan Deng
- Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry, School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, China
| | - Yubo Fan
- Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry, School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, China
- School of Engineering Medicine, Beihang University, Beijing 100083, China
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Li X, Liu X, Liang Y, Deng X, Fan Y. Spatiotemporal changes of local hemodynamics and plaque components during atherosclerotic progression in rabbit. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 220:106814. [PMID: 35523025 DOI: 10.1016/j.cmpb.2022.106814] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 02/22/2022] [Accepted: 04/11/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND AND OBJECTIVE Recent evidence demonstrates that the atherogenic process is discontinuous. Our goal is to study changes of plaque components and local hemodynamics during atherosclerotic progression. METHODS The histological and immunohistochemical staining of high-fat diet rabbit aorta were evaluated at 0, 8, 10 and 12 weeks, respectively. In addition, the blood flow and LDL transport were simulated at the above four time points. RESULTS The plaque thickness at different characteristic regions increased at different rates. The collagen continued to increase, while the elastin, fibronectin, macrophages and smooth muscle cells increased first and then decreased. The relative surface LDL concentration decreased at 8 weeks, and then it increased first and decreased slightly. Meanwhile, the hemodynamic environment became better firstly at 8 weeks, then got slightly worse and lastly improved again. CONCLUSIONS The local hemodynamics and plaque components vary nonlinearly during atherosclerotic progression in rabbit aorta.
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Affiliation(s)
- Xiaoyin Li
- Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
| | - Xiao Liu
- Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China.
| | - Ye Liang
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing, China
| | - Xiaoyan Deng
- Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
| | - Yubo Fan
- Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China; School of Engineering Medicine, Beihang University, Beijing, China.
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Li Z, Jiang W, Diao J, Chen C, Xu K, Fan H, Yan F. Segmentary strategy in modeling of cardiovascular system with blood supply to regional skin. Biocybern Biomed Eng 2021. [DOI: 10.1016/j.bbe.2021.08.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Choudhury S, Anupindi K, Patnaik BSV. A study on the transport and interaction between blood flow and low-density-lipoprotein in near-wall regions of blood vessels. Comput Methods Biomech Biomed Engin 2021; 24:1473-1487. [PMID: 33966566 DOI: 10.1080/10255842.2021.1893311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Differences in the dynamics and transport of blood make certain regions of the arterial network the preferred sites for initiation and formation of arterial diseases like stenosis and aneurysms. Understanding of such arterial diseases is directly linked to critical hemodynamic parameters such as the wall shear stress (WSS). The present work generalises the influence of WSS on the concentration of LDL that was observed in an earlier study. To this end, a wide variety of simplified flow domain, inspired by the near-wall regions of aneurysms and stenosis, are constructed and analyzed. The effects of pulsatile inflow condition, rheology of blood and curvature of the wall on the correlation between WSS and LDL concentration are investigated. It is demonstrated that the time-scale of variation of lumen-surface-concentration (LSC) of LDL is larger than a single cardiac cycle. As a consequence, the time-average values of WSS are sufficient to locate the regions of higher LSC. This idea is strengthened by making use of simplified flow domain that generates moving stagnation point. Further, it was observed that the rheology of the blood and curvature of the wall does not affect the observed correlation between the WSS and LDL concentration.
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Affiliation(s)
- Satyajit Choudhury
- Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India
| | - Kameswararao Anupindi
- Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai, India
| | - B S V Patnaik
- Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India
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Fluid-structure interactions (FSI) based study of low-density lipoproteins (LDL) uptake in the left coronary artery. Sci Rep 2021; 11:4803. [PMID: 33637804 PMCID: PMC7910311 DOI: 10.1038/s41598-021-84155-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 02/12/2021] [Indexed: 11/08/2022] Open
Abstract
The purpose of this study is to compare the effect of the different physical factors on low-density lipoproteins (LDL) accumulation from flowing blood to the arterial wall of the left coronary arteries. The three-dimensional (3D) computational model of the left coronary arterial tree is reconstructed from a patient-specific computed tomography angiography (CTA) image. The endothelium of the coronary artery is represented by a shear stress dependent three-pore model. Fluid–structure interaction (\documentclass[12pt]{minimal}
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\begin{document}$$FSI$$\end{document}FSI) based numerical method is used to study the LDL transport from vascular lumen into the arterial wall. The results show that the high elastic property of the arterial wall decreases the complexity of the local flow field in the coronary bifurcation system. The places of high levels of LDL uptake coincide with the regions of low wall shear stress. In addition, hypertension promotes LDL uptake from flowing blood in the arterial wall, while the thickened arterial wall decreases this process. The present computer strategy combining the methods of coronary CTA image 3D reconstruction, \documentclass[12pt]{minimal}
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\begin{document}$$FSI$$\end{document}FSI simulation, and three-pore modeling was illustrated to be effective on the simulation of the distribution and the uptake of LDL. This may have great potential for the early prediction of the local atherosclerosis lesion in the human left coronary artery.
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He S, Liu W, Qu K, Yin T, Qiu J, Li Y, Yuan K, Zhang H, Wang G. Effects of different positions of intravascular stent implantation in stenosed vessels on in-stent restenosis: An experimental and numerical simulation study. J Biomech 2020; 113:110089. [PMID: 33181394 DOI: 10.1016/j.jbiomech.2020.110089] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2020] [Revised: 09/08/2020] [Accepted: 10/16/2020] [Indexed: 11/29/2022]
Abstract
Percutaneous coronary intervention (PCI) has been widely used in the treatment of atherosclerosis, while in-stent restenosis (ISR) has not been completely resolved. Studies have shown that changes in intravascular mechanical environment are related to ISR. Hence, an in-depth understanding of the effects of stent intervention on vascular mechanics is important for clinically optimizing stent implantation and relieving ISR. Nine rabbits with stenotic carotid artery were collected by balloon injury. Intravascular stents were implanted into different longitudinal positions (proximal, middle and distal relative to the stenotic area) of the stenotic vessels for numerical simulations. Optical coherence tomography (OCT) scanning was performed to reconstruct the three-dimensional configuration of the stented carotid artery and blood flow velocity waveforms were collected by Doppler ultrasound. The numerical simulations were performed through direct solution of Naiver-Stokes equation in ANSYS. Results showed that the distributions of time-averaged wall shear stress (TAWSS), oscillating shear index (OSI) and relative residual time (RRT) in near-end segment were distinctively different from other regions of the stent which considered to promote restenosis for all three models. Spearman rank-correlation analysis showed a significant correlation between hemodynamic descriptors and the stent longitudinal positions (rTAWSS = -0.718, rOSI = 0.898, rRRT = 0.818, p < 0.01). Histology results of the near-end segment showed neointima thickening deepened with the longitudinal positions of stent which was consistent with the numerical simulations. The results suggest that stent implantation can promote restenosis at the near-end segment. As the stenting position moves to distal end, the impact on ISR is more significant.
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Affiliation(s)
- Shicheng He
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, Bioengineering College of Chongqing University, Chongqing 400030, PR China; State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China
| | - Wanling Liu
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, Bioengineering College of Chongqing University, Chongqing 400030, PR China
| | - Kai Qu
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, Bioengineering College of Chongqing University, Chongqing 400030, PR China
| | - Tieying Yin
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, Bioengineering College of Chongqing University, Chongqing 400030, PR China
| | - Juhui Qiu
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, Bioengineering College of Chongqing University, Chongqing 400030, PR China.
| | - Yan Li
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, Bioengineering College of Chongqing University, Chongqing 400030, PR China
| | - Kunshan Yuan
- National United Engineering Laboratory for Biomedical Material Modification, Dezhou, Shandong 251100, PR China
| | - Haijun Zhang
- National United Engineering Laboratory for Biomedical Material Modification, Dezhou, Shandong 251100, PR China
| | - Guixue Wang
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, Bioengineering College of Chongqing University, Chongqing 400030, PR China.
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Cong M, Xu X, Qiu J, Dai S, Chen C, Qian X, Zhang H, Qin S, Zhao H. Influence of malformation of right coronary artery originating from the left sinus in hemodynamic environment. Biomed Eng Online 2020; 19:59. [PMID: 32727522 PMCID: PMC7392689 DOI: 10.1186/s12938-020-00804-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Accepted: 07/23/2020] [Indexed: 11/11/2022] Open
Abstract
Background The anomalous origin of the right coronary artery (RCA) from the left coronary artery sinus (AORL) is one of the abnormal origins of the coronary arteries. Most of these issues rarely have any effects on human health, but some individuals may exhibit symptoms, such as myocardial ischemia or even sudden death. Recently, researchers have investigated the AORL through clinical cases, but studies based on computational fluid dynamics (CFD) have rarely been reported. In this study, the hemodynamic changes between the normal origin of the RCA and the AORL are compared based on numerical simulation results. Methods Realistic three-dimensional (3D) models of the 16 normal right coronary arteries and 26 abnormal origins of the RCAs were constructed, respectively. The blood flow was numerically simulated using the ANSYS software. This study used a one-way fluid–solid coupling finite element model, wherein the blood is assumed to be an incompressible Newtonian fluid, and the vessel is assumed to be made of an isotropic linear elastic material. Results The cross-sectional area differences between the inlet of the normal group and that of the abnormal group were significant (P < 0.0001). Moreover, there were significant differences in the volumetric flow (P = 0.0001) and pressure (P = 0.0002). Positive correlation exists for the ratio of the cross-sectional area of the RCA to the inlet area of the ascending aorta (AAO), and the ratio of the inlet volumetric flow of the RCA to the volumetric flow of the AAO, in the normal (P = 0.0001, r = 0.8178) and abnormal (P = 0.0033, r = 0.6107) groups. Conclusion This study demonstrates that the cross-sectional area of the AORL inlet may cause ischemia symptoms. The results obtained by this study may contribute to the further understanding of the clinical symptoms of the AORL based on the hemodynamics.
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Affiliation(s)
- Mengyang Cong
- College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, 266590, China
| | - Xingming Xu
- Intelligent Equipment College, Shandong University of Science and Technology, Taian, 271016, China
| | - Jianfeng Qiu
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271016, China.,Center for Medical Engineer Technology Research, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271016, China
| | - Shun Dai
- Department of Radiology, Shanghai Tong Ren Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200120, China
| | - Chuanzhi Chen
- Department of Radiology, East Hospital, Tongji University School of Medicine, Shanghai, 200120, China
| | - Xiuqing Qian
- Department of Biomedical engineering, Capital Medical University, Beijing, 10060, China
| | - Hongbin Zhang
- College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, 266590, China
| | - Shengxue Qin
- College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, 266590, China.
| | - Huihui Zhao
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271016, China. .,Center for Medical Engineer Technology Research, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271016, China.
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Acuna A, Berman AG, Damen FW, Meyers BA, Adelsperger AR, Bayer KC, Brindise MC, Bungart B, Kiel AM, Morrison RA, Muskat JC, Wasilczuk KM, Wen Y, Zhang J, Zito P, Goergen CJ. Computational Fluid Dynamics of Vascular Disease in Animal Models. J Biomech Eng 2019; 140:2676341. [PMID: 29570754 DOI: 10.1115/1.4039678] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Indexed: 12/19/2022]
Abstract
Recent applications of computational fluid dynamics (CFD) applied to the cardiovascular system have demonstrated its power in investigating the impact of hemodynamics on disease initiation, progression, and treatment outcomes. Flow metrics such as pressure distributions, wall shear stresses (WSS), and blood velocity profiles can be quantified to provide insight into observed pathologies, assist with surgical planning, or even predict disease progression. While numerous studies have performed simulations on clinical human patient data, it often lacks prediagnosis information and can be subject to large intersubject variability, limiting the generalizability of findings. Thus, animal models are often used to identify and manipulate specific factors contributing to vascular disease because they provide a more controlled environment. In this review, we explore the use of CFD in animal models in recent studies to investigate the initiating mechanisms, progression, and intervention effects of various vascular diseases. The first section provides a brief overview of the CFD theory and tools that are commonly used to study blood flow. The following sections are separated by anatomical region, with the abdominal, thoracic, and cerebral areas specifically highlighted. We discuss the associated benefits and obstacles to performing CFD modeling in each location. Finally, we highlight animal CFD studies focusing on common surgical treatments, including arteriovenous fistulas (AVF) and pulmonary artery grafts. The studies included in this review demonstrate the value of combining CFD with animal imaging and should encourage further research to optimize and expand upon these techniques for the study of vascular disease.
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Affiliation(s)
- Andrea Acuna
- Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907 e-mail:
| | - Alycia G Berman
- Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907 e-mail:
| | - Frederick W Damen
- Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907 e-mail:
| | - Brett A Meyers
- School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN 47907 e-mail:
| | - Amelia R Adelsperger
- Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907 e-mail:
| | - Kelsey C Bayer
- Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907 e-mail:
| | - Melissa C Brindise
- School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN 47907 e-mail:
| | - Brittani Bungart
- Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907 e-mail:
| | - Alexander M Kiel
- Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907 e-mail:
| | - Rachel A Morrison
- Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907 e-mail:
| | - Joseph C Muskat
- Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907 e-mail:
| | - Kelsey M Wasilczuk
- Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907 e-mail:
| | - Yi Wen
- Department of Agricultural and Biological Engineering, Purdue University, 225 South University Street, West Lafayette, IN 47907 e-mail:
| | - Jiacheng Zhang
- School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN 47907 e-mail:
| | - Patrick Zito
- Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907 e-mail:
| | - Craig J Goergen
- ASME Membership Bioengineering Division, Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907 e-mail:
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11
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Li Z, Hu L, Chen C, Wang Z, Zhou Z, Chen Y. Hemodynamic Performance of Multilayer Stents in the Treatment of Aneurysms with a Branch Attached. Sci Rep 2019; 9:10193. [PMID: 31308428 PMCID: PMC6629690 DOI: 10.1038/s41598-019-46714-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Accepted: 07/04/2019] [Indexed: 11/09/2022] Open
Abstract
Although multilayer stents (MSs) can be used to treat aneurysm effectively, for some aneurysms with branches attached, the hemodynamic mechanisms are still unclear. In this work, we modeled five cases that involve 1-4-layer stents implanted in aneurysms with side branches, and the numerical approach was used. Case 1 corresponds to an aneurysm without a stent, and cases 2-5 represent 1-4-layer stents being employed within aneurysms, respectively. The results showed that the velocity within the sac declined dramatically and the eddies' intensity weakened with increased number of stent layers, time-averaged wall shear stress (TAWSS), and nitric oxide production rate (TARNO) dropped linearly with increase in stent porosity, and oscillatory shear index (OSI) and relative residence time (RRT) increased evidently with MS intervention. Moreover, the MSs had a slight effect on the patency of the side branch; its flow rate was still above the normal case than without aneurysm. It can be concluded that MSs are helpful in promoting the growth of thrombus within the aneurysm through an isolated hemodynamic environment and keeping the branch unobstructed, but more clinical evidences are required.
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Affiliation(s)
- Zhongyou Li
- Department of Applied Mechanics, Sichuan University, Chengdu, 610065, China
| | - Lijuan Hu
- Third Department of Internal Medicine, Friendship Hospital, Xi'an, 710072, China
| | - Chong Chen
- College of Manufacturing Science & Engineering, Sichuan University, Chengdu, 610065, China
| | - Zhenze Wang
- Key Laboratory of Rehabilitation Aids Technology and System of the Ministry of Civil Affairs & Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, 100176, China
| | - Zhihong Zhou
- Department of Applied Mechanics, Sichuan University, Chengdu, 610065, China.
| | - Yu Chen
- Department of Applied Mechanics, Sichuan University, Chengdu, 610065, China
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Numerical simulation of haemodynamics of the descending aorta in the non-diabetic and diabetic rabbits. J Biomech 2019; 91:140-150. [DOI: 10.1016/j.jbiomech.2019.05.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2018] [Revised: 05/06/2019] [Accepted: 05/13/2019] [Indexed: 12/12/2022]
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Gabriel SA, Ding Y, Feng Y. Modelling the period-average transport of species within pulsatile blood flow. J Theor Biol 2018; 457:258-269. [DOI: 10.1016/j.jtbi.2018.07.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Revised: 05/31/2018] [Accepted: 07/06/2018] [Indexed: 12/23/2022]
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De Nisco G, Zhang P, Calò K, Liu X, Ponzini R, Bignardi C, Rizzo G, Deng X, Gallo D, Morbiducci U. What is needed to make low-density lipoprotein transport in human aorta computational models suitable to explore links to atherosclerosis? Impact of initial and inflow boundary conditions. J Biomech 2018; 68:33-42. [DOI: 10.1016/j.jbiomech.2017.12.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Revised: 12/05/2017] [Accepted: 12/07/2017] [Indexed: 12/26/2022]
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