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Trends and Prospects of Numerical Modelling in Bioengineering
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Trends and Prospects of Numerical Modelling in Bioengineering

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Computational and Applied Mathematics".

Deadline for manuscript submissions: 10 July 2025 | Viewed by 5030

Special Issue Editors

Prof. Dr. Claudio De Lazzari

E-Mail Website
Guest Editor
Institute of Clinical Physiology (CNR), University Geomedi LLC, Tbilisi, Georgia
Interests: cardiovascular and respiratory system numerical/hybrid modelling; e-learning and medical simulation training; numerical stem cell therapy
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Sivia Marconi

E-Mail Website
Guest Editor
Department of Basic and Applied Sciences for Engineering, Sapienza University of Rome, Via Antonio Scarpa, 16, 00161 Rome, RM, Italy
Interests: mathematical modeling of stem cell therapy for myocardial regeneration therapy; mathematical modeling of cardiovascular and respiratory systems; mathematical models and simulations in biomedical research; signal analysis; image processing and analysis
Beatrice De Lazzari

E-Mail Website
Guest Editor Assistant
Department of Human Motor and Health Science – University of Rome “Foro Italico”, Rome 600135, Italy
Interests: numerical/hybrid modelling

Special Issue Information

Dear Colleagues,

Biomedical engineering, which combines the knowledge of several aspects of medical and engineering fields, has received great attention from the scientific research and medical community in recent decades. Many clinicians have considered new simulation software to understand its use for the purposes of treatment optimisation and outcome prediction based on a patient-specific modelling approach. 

Specific clinical applications include the understanding of human pathologies and diseases; the advancement of medical healthcare; and the improvement of diagnosis, therapies, and clinical outcomes. Other applications are related to the sport field. The performance of athletes can be studied and improved using different numerical simulators. 

The development of numerical or hybrid (numerical-hydraulic) models may also help to reduce the number of tests in animals and possibly contribute to the improvement of their wellbeing. Finally, numerical models have been developed to study biological problems, such as stem cell therapy, treatment of tumours, wound healing and microfluidics and diffusion processes.

The use of simulation software based on numerical/hybrid models describing organ or cell behaviour is becoming more popular for educational purposes.

This Special Issue is focused on the numerical modelling of the complex problems in the field of biomechanical and biomedical engineering, which include but are not limited to:

  • Cardiovascular mechanics;
  • Interaction between the cardiovascular system and mechanical assist devices and/or mechanical ventilation;
  • Computational biofluid dynamics;
  • Clinical application of novel numerical algorithms to the biomedical engineering;
  • The use of numerical simulation in education;
  • Tissue and cell mechanics;
  • Numerical methods applied to biomechanics;
  • Computer-assisted surgery and fluid dynamics;
  • Multiscale flow modelling (3D, 1D, and 0D models);
  • Biomechanics in athletics;
  • Movement analysis and biomechanics for endurance sports;
  • Application and impact of numerical models for decision making in sport;
  • Molecular and cell therapies.

As such, high-quality original research papers are welcome.

Prof. Dr. Claudio De Lazzari
Prof. Dr. Sivia Marconi
Guest Editors

Beatrice De Lazzari
Guest Editor Assistant

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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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

  • numerical model
  • numerical software
  • e-learning
  • 0D, 1D, and 3D model
  • clinical environment
  • hybrid model
  • athletic performance
  • biomechanics in athletics
  • movement analysis
  • computer assist surgery

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Published Papers (4 papers)

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Research

15 pages, 1393 KiB  
Article
Some Numerical Results on Chemotactic Phenomena in Stem Cell Therapy for Cardiac Regeneration
by Daniele Andreucci, Alberto M. Bersani, Enrico Bersani, Paolo Caressa, Miguel Dumett, Francisco James Leon Trujillo, Silvia Marconi, Obidio Rubio and Yessica E. Zarate-Pedrera
Mathematics 2024, 12(13), 1937; https://doi.org/10.3390/math12131937 - 22 Jun 2024
Viewed by 683
Abstract
Biological models for cardiac regeneration and remodeling, along with the effects of cytokines or chemokines during the therapy with mesenchymal stem cells after a myocardial infarction, are of crucial importance for understanding the complex underlying mechanisms. This paper presents a mathematical model composed [...] Read more.
Biological models for cardiac regeneration and remodeling, along with the effects of cytokines or chemokines during the therapy with mesenchymal stem cells after a myocardial infarction, are of crucial importance for understanding the complex underlying mechanisms. This paper presents a mathematical model composed of three coupled partial differential equations that describes the dynamics of stem cells, nutrients and chemokines, highlighting the fundamental role of the chemokines during the myocardial tissue regeneration process. The system is solved numerically using mimetic difference operators and the MOLE library for MATLAB. The results show the tissue regeneration process in the necrotic part closest to the cell implantation area. Full article
(This article belongs to the Special Issue Trends and Prospects of Numerical Modelling in Bioengineering)
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30 pages, 3077 KiB  
Article
Wearable Sensors for Athletic Performance: A Comparison of Discrete and Continuous Feature-Extraction Methods for Prediction Models
by Mark White, Beatrice De Lazzari, Neil Bezodis and Valentina Camomilla
Mathematics 2024, 12(12), 1853; https://doi.org/10.3390/math12121853 - 14 Jun 2024
Viewed by 1025
Abstract
Wearable sensors have become increasingly popular for assessing athletic performance, but the optimal methods for processing and analyzing the data remain unclear. This study investigates the efficacy of discrete and continuous feature-extraction methods, separately and in combination, for modeling countermovement jump performance using [...] Read more.
Wearable sensors have become increasingly popular for assessing athletic performance, but the optimal methods for processing and analyzing the data remain unclear. This study investigates the efficacy of discrete and continuous feature-extraction methods, separately and in combination, for modeling countermovement jump performance using wearable sensor data. We demonstrate that continuous features, particularly those derived from Functional Principal Component Analysis, outperform discrete features in terms of model performance, robustness to variations in data distribution and volume, and consistency across different datasets. Our findings underscore the importance of methodological choices, such as signal type, alignment methods, and model selection, in developing accurate and generalizable predictive models. We also highlight the potential pitfalls of relying solely on domain knowledge for feature selection and the benefits of data-driven approaches. Furthermore, we discuss the implications of our findings for the broader field of sports biomechanics and provide practical recommendations for researchers and practitioners aiming to leverage wearable sensor data for athletic performance assessment. Our results contribute to the development of more reliable and widely applicable predictive models, facilitating the use of wearable technology for optimizing training and enhancing athletic outcomes across various sports disciplines. Full article
(This article belongs to the Special Issue Trends and Prospects of Numerical Modelling in Bioengineering)
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7 pages, 1391 KiB  
Article
Blood Gas Parameters and Acid–Base Balance during Extracorporeal Lung Support with Oxygenators: Semi-Empirical Evaluation
by Lal Babu Khadka, Foivos Leonidas Mouzakis, Ali Kashefi, Flutura Hima, Jan Wilhelm Spillner and Khosrow Mottaghy
Mathematics 2023, 11(19), 4088; https://doi.org/10.3390/math11194088 - 27 Sep 2023
Viewed by 888
Abstract
Membrane artificial lungs (oxygenators) are used in cardiopulmonary surgery as well as, in some cases, in severe lung disease to support the natural lung by means of ECMO (extracorporeal membrane oxygenation). The oxygen and carbon dioxide transfer rates of any oxygenator are usually [...] Read more.
Membrane artificial lungs (oxygenators) are used in cardiopulmonary surgery as well as, in some cases, in severe lung disease to support the natural lung by means of ECMO (extracorporeal membrane oxygenation). The oxygen and carbon dioxide transfer rates of any oxygenator are usually assessed by considering several blood gas parameters, such as oxygen saturation, hemoglobin concentration, partial pressure of oxygen and carbon dioxide, bicarbonate concentration, and pH. Here, we report a set of semi-empirical equations that calculate such parameters directly from their partial pressures and assess the acid–base balance during ECMO. The implementation of this equation set permits the evaluation of any oxygenator, existing or prototypes in development, as well as the development of clinical decision-making tools for predicting the blood gas state and acid–base balance during surgical interventions and ECMO. The predicted results are then compared with experimental data obtained from in vitro gas exchange investigations with a commercial oxygenator using fresh porcine blood. The high correlation, R2>0.95, between the predicted and the experimental data suggests a possibility of using such empirical equations in the simulation of gas transfer in a cardiopulmonary system with an oxygenator for any venous inlet blood gas data and also for estimating the acid–base balance during such therapy. Full article
(This article belongs to the Special Issue Trends and Prospects of Numerical Modelling in Bioengineering)
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17 pages, 4761 KiB  
Article
Computational Evaluation of IABP, Impella 2.5, TandemHeart and Combined IABP and Impella 2.5 Support in Cardiogenic Shock
by Rahmi Alkan, Beatrice De Lazzari, Massimo Capoccia, Claudio De Lazzari and Selim Bozkurt
Mathematics 2023, 11(16), 3606; https://doi.org/10.3390/math11163606 - 21 Aug 2023
Cited by 2 | Viewed by 1599
Abstract
Cardiogenic shock is a life-threatening condition consisting of low cardiac output status leading to end-organ hypoperfusion following either acute left or right ventricular failure or decompensation of chronic heart failure. Partial or failed response to inotropic support in the acute phase may require [...] Read more.
Cardiogenic shock is a life-threatening condition consisting of low cardiac output status leading to end-organ hypoperfusion following either acute left or right ventricular failure or decompensation of chronic heart failure. Partial or failed response to inotropic support in the acute phase may require the use of mechanical circulatory support. Although patients supported with different devices such as an IABP, Impella 2.5, or TandemHeart experience stability in the short term, the haemodynamic benefits of each device remain unclear. The aim of this study is to present a direct comparison of an IABP, Impella 2.5, TandemHeart, and combined IABP and Impella 2.5 support in cardiogenic shock to evaluate haemodynamic variables and left ventricular unloading using cardiovascular system modelling and simulation in terms of cardiac function, systemic, pulmonary, cardiac, and cerebral circulations. The simulation results showed that the IABP had a relatively low effect on the haemodynamic variables. Although both Impella 2.5 and TandemHeart improved the total blood flow rates, as well as coronary and cerebral perfusion with the increasing pump operating speed, TandemHeart had a more profound effect on the haemodynamic variables. Combining the IABP and Impella 2.5 also improved the haemodynamics, although at the expense of reverse blood flow in the cerebral circulation. Simulation results showed that TandemHeart support might have a more beneficial effect on the haemodynamics and left ventricular energetics in comparison to the IABP and Impella 2.5. Nevertheless, the combined use of the IABP and Impella 2.5 for short-term support may be considered an appropriate alternative. Full article
(This article belongs to the Special Issue Trends and Prospects of Numerical Modelling in Bioengineering)
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