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Bioengineering
Special Issues
Computational Biofluid Dynamics
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Computational Biofluid Dynamics

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".

Deadline for manuscript submissions: 31 August 2025 | Viewed by 1693

Special Issue Editors

Prof. Dr. Tinghui Zheng

E-Mail Website
Guest Editor
Department of Mechanics, Sichuan University, Chengdu, China
Interests: hemodynamics; biomechanics; artificial pump lung; ECMO; mechanical assist device; thrombosis; blood damage
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Peng Wu

E-Mail Website
Guest Editor
Department of Medical Equipment, School of Mechanical Engineering, Southeast University, Nanjing, China
Interests: hemodynamics; CFD; blood pumps; modeling of blood damage; design and optimization of blood contacting devices
Special Issues, Collections and Topics in MDPI journals
Dr. Jun Wen

E-Mail Website
Guest Editor
Department of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, China
Interests: hemodynamics; computational fluid dynamics; deep learning in medical applications; medical device development; medical image segmentation and analysis

Special Issue Information

Dear Colleagues,

In the realm of healthcare and biomedical research, understanding the complex behaviors of biofluids—such as blood, respiratory gasses, and cellular fluids—is critical. Computational biofluid dynamics is an interdisciplinary field that combines computational fluid dynamics with biological insights and computational science, providing a powerful tool to simulate and predict fluid behavior across various biological systems. This integration is essential for advancing our knowledge in physiology and pathophysiology, particularly in the design and evaluation of medical therapies and devices.

This Special Issue seeks to highlight cutting-edge research in computational biofluid dynamics. We aim to explore how these computational techniques can be applied to real-world medical challenges, enhancing diagnostic accuracy, treatment efficacy, and device innovation.

The scope of this issue includes, but is not limited to, the following:

  • The development of computational models for diverse biofluid applications in cardiovascular and pulmonary systems.
  • The utilization of advanced computational fluid dynamics to study fluid behavior under normal and pathological conditions.
  • The application of machine learning to improve the predictions of fluid dynamics models and their implications in clinical settings.
  • Detailed investigations connecting computational findings to molecular biology and molecular imaging, thereby influencing the development of therapeutic strategies and clinical practices.

Contributions should demonstrate a blend of theoretical innovation and practical relevance, aiming to bridge the gap between computational simulations and clinical applications in critical care and beyond.

Prof. Dr. Tinghui Zheng
Prof. Dr. Peng Wu
Dr. Jun Wen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biofluids
  • cardiovascular and pulmonary systems
  • machine learning
  • critical care

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

17 pages, 2417 KiB  
Article
Virtual Therapy Planning of Aortic Valve Replacement for Preventing Patient-Prosthesis Mismatch
by Marie Schafstedde, Florian Hellmeier, Jackie Grünert, Bianca Materne, Titus Kuehne, Leonid Goubergrits and Sarah Nordmeyer
Bioengineering 2025, 12(4), 328; https://doi.org/10.3390/bioengineering12040328 - 21 Mar 2025
Viewed by 148
Abstract
Background: Recent studies suggest that any degree of patient-prosthesis mismatch (PPM) increases morbidity and mortality after surgical aortic valve replacement (SAVR). We used computational fluid dynamics simulations to test the influence of prosthesis size and physical activity after SAVR. Methods: In 10 patients [...] Read more.
Background: Recent studies suggest that any degree of patient-prosthesis mismatch (PPM) increases morbidity and mortality after surgical aortic valve replacement (SAVR). We used computational fluid dynamics simulations to test the influence of prosthesis size and physical activity after SAVR. Methods: In 10 patients with aortic valve stenosis, virtual SAVR was performed. Left ventricular outflow tract stroke volume and flow direction information (4D Flow) were used, and an increase in stroke volume of 25% was chosen for simulating physical activity. Pressure gradients (DP max) across the aortic valve and blood flow profiles in the ascending aorta were calculated and predicted for three different valve sizes at rest and under stress in every patient. Results: Gradients across the aortic valve were significantly lower using larger valves; however, they were not normalized after SAVR (DP max [mmHg] norm/smaller/reference/larger valve = 6/14/12/9 mmHg, <0.01 compared to norm). Physical activity simulation increased DP max in all patients and across all valve sizes (DP max [mmHg] rest versus stress for the smaller/reference/larger valve = 14 vs. 23, 12 vs. 18, 9 vs. 14). Blood flow profiles did not normalize after SAVR and remained unaffected by physical activity. Gradients differed between mild and moderate stenosis between different therapy options and even showed moderate to severe stenosis under simulated physical activity. Conclusions: Prosthesis size and physical activity simulation have a significant influence on gradients across the aortic valve. Virtual therapy planning using patient-specific data might help to improve outcomes after SAVR in the future. Full article
(This article belongs to the Special Issue Computational Biofluid Dynamics)
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14 pages, 21397 KiB  
Article
Nitric Oxide Distribution Correlates with Intraluminal Thrombus in Abdominal Aortic Aneurysm: A Computational Study
by Siting Li, Shiyi Yang, Xiaoning Sun, Tianxiang Ma, Yuehong Zheng and Xiao Liu
Bioengineering 2025, 12(2), 191; https://doi.org/10.3390/bioengineering12020191 - 17 Feb 2025
Viewed by 326
Abstract
Intraluminal thrombus (ILT) in the abdominal aortic aneurysm (AAA) is associated with disease progression and complications. This study investigates the relationship between nitric oxide (NO) concentration and ILT in AAA patients using patient-specific computational fluid dynamics (CFD) models. Four AAA patients with ILT [...] Read more.
Intraluminal thrombus (ILT) in the abdominal aortic aneurysm (AAA) is associated with disease progression and complications. This study investigates the relationship between nitric oxide (NO) concentration and ILT in AAA patients using patient-specific computational fluid dynamics (CFD) models. Four AAA patients with ILT were enrolled. Patient-specific models of the aorta and branch arteries were constructed followed by CFD simulations. NO concentration was modeled based on endothelial shear stress response and its transport within the arterial lumen and wall. Hemodynamic parameters, including wall shear stress (WSS) and its derivatives, were analyzed alongside NO distribution. ILT accumulation was primarily located in the infrarenal abdominal aorta. Regions of decreased NO concentration correlated with ILT accumulated areas, whereas regions with decreased TAWSS and increased OSI were less consistent with ILT accumulation. A negative correlation was observed between the thrombus area and NO concentration, with p values of less than 0.001 for four patients. The time-average area NO concentration values of lumen area with ILT were lower than those of non-ILT sections. Spatially, NO was unevenly distributed, with thicker thrombus in regions of lower NO concentration. NO distribution could serve as a better potential personalized marker for thrombosis prediction in AAA compared to WSS-derived parameters. Full article
(This article belongs to the Special Issue Computational Biofluid Dynamics)
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15 pages, 4331 KiB  
Article
The Association Between the Hemodynamics in Anomalous Origins of Coronary Arteries and Atherosclerosis: A Preliminary Case Study Based on Computational Fluid Dynamics
by Yuhao Wei, Haoyao Cao and Tinghui Zheng
Bioengineering 2024, 11(12), 1196; https://doi.org/10.3390/bioengineering11121196 - 26 Nov 2024
Viewed by 739
Abstract
Patients with anomalous coronary artery origins (AOCA) exhibit a higher risk of atherosclerosis, where even minimal stenosis may lead to adverse cardiovascular events. However, the factors contributing to this heightened risk in AOCA patients remain unclear. This study aimed to investigate whether an [...] Read more.
Patients with anomalous coronary artery origins (AOCA) exhibit a higher risk of atherosclerosis, where even minimal stenosis may lead to adverse cardiovascular events. However, the factors contributing to this heightened risk in AOCA patients remain unclear. This study aimed to investigate whether an AOCA patient is more prone to stenosis occurrence and its progression in view of hemodynamics. A patient whose left circumflex artery originated from the right coronary sinus with a mild stenosis in the left anterior descending (LAD) artery and a healthy individual were included in this study. Two additional models were developed by removing stenosis from the patient model and adding a corresponding stenosis to the healthy model. Additionally, the inlet flow waveforms for the left and right coronary arteries were swapped in both the patient and healthy models. Results indicated that the AOCA patient without stenosis demonstrated higher wall pressure (LAD: 95.57 ± 0.73 vs. 93.86 ± 0.50 mmHg; LCX: 94.97 ± 0.98 vs. 93.47 ± 0.56 mmHg; RCA: 96.23 ± 0.30 vs. 93.86 ± 0.46 mmHg) and TAWSS (LAD: 24.41 ± 19.53 vs. 13.82 ± 9.87 dyne/cm2, p < 0.0001; LCX: 27.21 ± 14.51 vs. 19.33 ± 8.78 dyne/cm2) compared to the healthy individual, with similar trends also observed in stenotic conditions. Significant changes in the LCX flow distribution were also noted under varying pulsatile conditions (LCX: 18.28% vs. 9.16%) compared to the healthy individual. The high-pressure, high-shear hemodynamic environment in AOCA patients predisposes them to atherosclerosis, and the unique geometry exacerbates hemodynamic abnormalities when stenosis occurs. Clinicians should closely monitor AOCA patients with stenosis to prevent adverse cardiovascular events. Full article
(This article belongs to the Special Issue Computational Biofluid Dynamics)
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