New Sights of Biomechanics and Mechanobiology in Cardiovascular and/or Neurovascular

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomedical Engineering and Biomaterials".

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 3913

Special Issue Editors


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Guest Editor
Department of Mechanical and Materials Engineering, Wright State University, Dayton, OH 45435, USA
Interests: hemodynamics; biomechanics; aneurysm; stenosis; In vitro experiment; computational fluid dynamics
Special Issues, Collections and Topics in MDPI journals
Department of Mechanical Engineering, North Dakota State University, Fargo, ND 58108, USA
Interests: Hemodynamics; biofluid mechanics; cardiovascular modeling; advanced flow diagnostics; experimental fluid dynamics and aerodynamics
Institute of Fluid Machinery and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Interests: Hemodynamics; biomechanics; biofluids; computational fluid dynamics and hydrodynamics
Department of Mechanical and Materials Engineering, Wright State University, Dayton, OH 45354, USA
Interests: Computational and experimental fluid dynamics; biofluidic and biomechanics; particle image velocimetry; multiphase flow modeling; fluid–solid interaction modeling; discrete phase models; non-Newtonian fluid modeling; fire models; machine learning and deep learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

According to the statistical report from the WHO, cardiovascular and neurovascular associated diseases have become one of the leading causes of death worldwide, and it is widely recognized that hemodynamic factors have a close relationship with the physiological and pathological conditions of such diseases. Physical forces and changes in cell mechanics, extracellular matrix structure, or mechanotransduction may contribute to the development of many vascular diseases. The recent progress of fundamentals and applications in in situ and/or in vivo and/or in vitro experiments, in silico-based numerical investigations, and machine-learning and/or deep-learning analysis based on big data obtained by medical images for the identification/quantification of vascular diseases has made significant contributions to transforming the current findings and innovations towards the facilitation of patient-specific clinical diagnosis and individualized surgical plans.

This Special Issue “New Sights of Biomechanics and Mechanobiology in Cardiovascular and/or Neurovascular” will publish original research and current review articles with new/better understanding of physiological and pathological fundamentals, cutting-edge findings, and innovative applications of biomechanics/mechanobiology in cardiovascular and neurovascular systems.

Dr. Zifeng Yang
Dr. Yan Zhang
Dr. Jun Yang
Dr. Hang Yi
Guest Editors

Manuscript Submission Information

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Keywords

  • mechanobiology
  • biomechanics
  • biofluids
  • cardiovascular
  • neurovascular
  • computational fluid dynamics
  • in vivo and/or in vitro experiments
  • transport phenomena in pre-/post-treatment
  • pathobiology
  • drug delivery
  • hemodynamics
  • machine learning
  • deep learning

Published Papers (3 papers)

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Research

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22 pages, 6565 KiB  
Article
Research on the Internal Flow Field of Left Atrial Appendage and Stroke Risk Assessment with Different Blood Models
by Jun Yang, Zitao Bai, Chentao Song, Huirong Ding, Mu Chen, Jian Sun and Xiaohua Liu
Bioengineering 2023, 10(8), 944; https://doi.org/10.3390/bioengineering10080944 - 8 Aug 2023
Cited by 1 | Viewed by 1000
Abstract
Extant clinical research has underscored that patients suffering from atrial fibrillation (AF) bear an elevated risk for stroke, predominantly driven by the formation of thrombus in the left atrial appendage (LAA). As such, accurately identifying those at an increased risk of thrombosis becomes [...] Read more.
Extant clinical research has underscored that patients suffering from atrial fibrillation (AF) bear an elevated risk for stroke, predominantly driven by the formation of thrombus in the left atrial appendage (LAA). As such, accurately identifying those at an increased risk of thrombosis becomes paramount to facilitate timely and effective treatment. This study was designed to shed light on the mechanisms underlying thrombus formation in the LAA by employing three-dimensional (3D) left atrium (LA) models of AF patients, which were constructed based on Computed Tomography (CT) imaging. The distinct benefits of Computational Fluid Dynamics (CFD) were leveraged to simulate the blood flow field within the LA, using three distinct blood flow models, both under AF and sinus rhythm (SR) conditions. The potential risk of thrombus formation was evaluated by analyzing the Relative Residence Time (RRT) and Endothelial Cell Activation Potential (ECAP) values. The results gleaned from this study affirm that all three blood flow models align with extant clinical guidelines, thereby enabling an effective prediction of thrombosis risk. However, noteworthy differences emerged when comparing the intricacies of the flow field and thrombosis risk across the three models. The single-phase non-Newtonian blood flow model resulted in comparatively lower residence times for blood within the LA and lower values for the Oscillatory Shear Index (OSI), RRT, and ECAP within the LAA. These findings suggest a reduced thrombosis risk. Conversely, the two-phase non-Newtonian blood flow model exhibited a higher residence time for blood and elevated RRT value within the LAA, suggesting an increased risk for thrombosis. Full article
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17 pages, 3984 KiB  
Article
The Influence of Aortic Valve Disease on Coronary Hemodynamics: A Computational Model-Based Study
by Xuanyu Li, Sergey Simakov, Youjun Liu, Taiwei Liu, Yue Wang and Fuyou Liang
Bioengineering 2023, 10(6), 709; https://doi.org/10.3390/bioengineering10060709 - 11 Jun 2023
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Abstract
Aortic valve disease (AVD) often coexists with coronary artery disease (CAD), but whether and how the two diseases are correlated remains poorly understood. In this study, a zero–three dimensional (0-3D) multi-scale modeling method was developed to integrate coronary artery hemodynamics, aortic valve dynamics, [...] Read more.
Aortic valve disease (AVD) often coexists with coronary artery disease (CAD), but whether and how the two diseases are correlated remains poorly understood. In this study, a zero–three dimensional (0-3D) multi-scale modeling method was developed to integrate coronary artery hemodynamics, aortic valve dynamics, coronary flow autoregulation mechanism, and systemic hemodynamics into a unique model system, thereby yielding a mathematical tool for quantifying the influences of aortic valve stenosis (AS) and aortic valve regurgitation (AR) on hemodynamics in large coronary arteries. The model was applied to simulate blood flows in six patient-specific left anterior descending coronary arteries (LADs) under various aortic valve conditions (i.e., control (free of AVD), AS, and AR). Obtained results showed that the space-averaged oscillatory shear index (SA-OSI) was significantly higher under the AS condition but lower under the AR condition in comparison with the control condition. Relatively, the overall magnitude of wall shear stress was less affected by AVD. Further data analysis revealed that AS induced the increase in OSI in LADs mainly through its role in augmenting the low-frequency components of coronary flow waveform. These findings imply that AS might increase the risk or progression of CAD by deteriorating the hemodynamic environment in coronary arteries. Full article
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17 pages, 1397 KiB  
Systematic Review
Evidence in Clinical Studies for the Role of Wall Thickness in Ascending Thoracic Aortic Aneurysms: A Scoping Review
by Gijs P. Debeij, Shaiv Parikh, Tammo Delhaas, Elham Bidar and Koen D. Reesink
Bioengineering 2023, 10(8), 882; https://doi.org/10.3390/bioengineering10080882 - 25 Jul 2023
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Abstract
Background: Ascending thoracic aortic aneurysm is a chronic degenerative pathology characterized by dilatation of this segment of the aorta. Clinical guidelines use aortic diameter and growth rate as predictors of rupture and dissection. However, these guidelines neglect the effects of tissue remodeling, which [...] Read more.
Background: Ascending thoracic aortic aneurysm is a chronic degenerative pathology characterized by dilatation of this segment of the aorta. Clinical guidelines use aortic diameter and growth rate as predictors of rupture and dissection. However, these guidelines neglect the effects of tissue remodeling, which may affect wall thickness. The present study aims to systematically review observational studies to examine to what extent wall thickness is considered and measured in clinical practice. Methods: Using PubMed and Web of Science, studies were identified with data on ascending aortic wall thickness, morphology, aortic diameter, and measurement techniques. Results: 15 included studies report several methods by which wall thickness is measured. No association was observed between wall thickness and aortic diameter across included studies. Wall thickness values appear not materially different between aneurysmatic aortas and non-aneurysmal aortas. Conclusions: The effects on and consequences of wall thickness changes during ATAA formation are ill-defined. Wall thickness values for aneurysmatic aortas can be similar to aortas with normal diameters. Given the existing notion that wall thickness is a determinant of mechanical stress homeostasis, our review exposes a clear need for consistent as well as clinically applicable methods and studies to quantify wall thickness in ascending aortic aneurysm research. Full article
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