The mammalian cardiovascular system (CVS) comprises the heart, blood and blood vessels, which, through coordinated action, ensures the transport of oxygen, nutrients, hormones and enzymes to every cell in the body, while collecting toxic wastes for elimination from the same. Because of its complex and multi-component nature, malfunctioning of the CVS often results in multiscale problems that pose major challenges to targeted therapy. This is because abnormalities occurring at the molecular level can lead to defective electrical or mechanical activities at the organ level, thereby inhibiting the identification of the true source of the problem. To overcome this challenge, an interdisciplinary approach is warranted. In recent years, mathematical modeling has found synergistic use alongside in vitro, ex vivo or in vivo research, providing useful mechanistic insights through simulations, where experimental capabilities are limited.
Inspired by new experimental data and supported by high-performance computing, mathematical modeling is increasingly applied in the CVS to understand mechanisms of abnormal processes and test potential therapeutic strategies. To this end, computer models are developed that can be used to simulate the state of the art in technology that can be tested prior to experimentation on animal systems. This research topic focuses on the current state of the art in cardiovascular system modeling, and addresses the fundamental challenges.
Research articles and reviews, including mathematical and numerical modeling and their applications in the cardiovascular system, are welcome. We welcome submissions on the following subtopics, but are not limited to:
• Cardiac electrophysiology: Electrical wave propagation through the heart, Abnormal electrical activity, Arrhythmias.
• Mechanics: Heart modeling, Rheometry and constitutive model of the cardiac muscle tissue and arterial wall.
• Haemodynamics: Modeling of red blood cells and blood flow.
• General: Image-based reconstruction of the heart, Applications of marchine learning and AI, Advanced numerical methods etc.
The mammalian cardiovascular system (CVS) comprises the heart, blood and blood vessels, which, through coordinated action, ensures the transport of oxygen, nutrients, hormones and enzymes to every cell in the body, while collecting toxic wastes for elimination from the same. Because of its complex and multi-component nature, malfunctioning of the CVS often results in multiscale problems that pose major challenges to targeted therapy. This is because abnormalities occurring at the molecular level can lead to defective electrical or mechanical activities at the organ level, thereby inhibiting the identification of the true source of the problem. To overcome this challenge, an interdisciplinary approach is warranted. In recent years, mathematical modeling has found synergistic use alongside in vitro, ex vivo or in vivo research, providing useful mechanistic insights through simulations, where experimental capabilities are limited.
Inspired by new experimental data and supported by high-performance computing, mathematical modeling is increasingly applied in the CVS to understand mechanisms of abnormal processes and test potential therapeutic strategies. To this end, computer models are developed that can be used to simulate the state of the art in technology that can be tested prior to experimentation on animal systems. This research topic focuses on the current state of the art in cardiovascular system modeling, and addresses the fundamental challenges.
Research articles and reviews, including mathematical and numerical modeling and their applications in the cardiovascular system, are welcome. We welcome submissions on the following subtopics, but are not limited to:
• Cardiac electrophysiology: Electrical wave propagation through the heart, Abnormal electrical activity, Arrhythmias.
• Mechanics: Heart modeling, Rheometry and constitutive model of the cardiac muscle tissue and arterial wall.
• Haemodynamics: Modeling of red blood cells and blood flow.
• General: Image-based reconstruction of the heart, Applications of marchine learning and AI, Advanced numerical methods etc.