Personalized Computational Hemodynamics

Personalized Computational Hemodynamics

Models, Methods, and Applications for Vascular Surgery and Antitumor Therapy

1st Edition - April 16, 2020

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  • Authors: Yuri Vassilevsky, Maxim Olshanskii, Sergey Simakov, Andrey Kolobov, Alexander Danilov
  • Paperback ISBN: 9780128156537
  • eBook ISBN: 9780128156544

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Description

Personalized Computational Hemodynamics: Models, Methods, and Applications for Vascular Surgery and Antitumor Therapy offers practices and advances surrounding the multiscale modeling of hemodynamics and their personalization with conventional clinical data. Focusing on three physiological disciplines, readers will learn how to derive a suitable mathematical model and personalize its parameters to account for pathologies and diseases. Written by leading experts, this book mirrors the top trends in mathematical modeling with clinical applications. In addition, the book features the major results of the "Research group in simulation of blood flow and vascular pathologies" at the Institute of Numerical Mathematics of the Russian Academy of Sciences. Two important features distinguish this book from other monographs on numerical methods for biomedical applications. First, the variety of medical disciplines targeted by the mathematical modeling and computer simulations, including cardiology, vascular neurology and oncology. Second, for all mathematical models, the authors consider extensions and parameter tuning that account for vascular pathologies.

Key Features

  • Examines a variety of medical disciplines targeted by mathematical modeling and computer simulation
  • Discusses how the results of numerical simulations are used to support clinical decision-making
  • Covers hemodynamics relating to various subject areas, including vascular surgery and oncological tumor treatments

Readership

Graduate students and researchers focusing on mathematical modeling in biomedicine, computational biology

Table of Contents

  • 1. Introduction
    1.1 Rationale
    1.2 Objectives
    1.3 Structure and overview of the book

    2. Basic facts about a human cardiovascular system
    2.1 Introduction
    2.2 Heart as a pump
    2.3 Vasculature
    2.4 Microvasculature
    2.5 Vascular physiology
    2.6 Vascular pathologies
    2.7 Conclusions

    3. Patient-specific geometric modelling
    3.1 Introduction
    3.2 Basics about medical imaging (modalities and data)
    3.3 Heart segmentation
    3.4 Blood vessels segmentation
    3.5 Generation of computational meshes
    3.6 Conclusions

    4. General equations of motion
    4.1 Introduction
    4.2 Navier-Stokes equations for incompressible fluid
    4.3 Elastic and hyperelastic materials
    4.4 Fluid-structure interaction
    4.5 Conclusions

    5. 3D vascular and heart hemodynamics
    5.1 Introduction
    5.2 Simulation of blood flow in vessel with non-deformable walls
    5.3 Simulation of blood flow in vessel with compliant walls
    5.4 Simulation of blood flow in the heart
    5.5 Simulation of blood flow in heart valves
    5.6 Systems of algebraic equations and complexity issues
    5.7 Conclusions

    6. 0D lumped models
    6.1 Introduction
    6.2 Electric circuit ODEs
    6.3 Elastic sphere ODEs
    6.4 Numerical methods
    6.5 Accounting for physiological phenomena
    6.6 Accounting for pathologies
    6.7 Conclusions

    7. 1D vascular hemodynamics
    7.1 Introduction
    7.2 Derivation of equations
    7.3 Numerical solution of equations
    7.4 Geometrical multiscale methods (0D-1D-3D)
    7.5 Accounting for physiological phenomena
    7.6 Accounting for pathologies
    7.7 Conclusions

    8. Hemodynamics in capillary networks and angiogenesis
    8.1 Introduction
    8.2 Generation of capillary networks
    8.3 Pathologic capillary networks
    8.4 Hydraulic network equations
    8.5 Transport in capillary networks
    8.6 Conclusions

    9. Applications in vascular surgery
    9.1 Introduction
    9.2 Cava-filter placement
    9.3 Stenting of leg arteries
    9.4 Stenting of coronary arteries and FFR
    9.5 Stenting of cerebral arteries
    9.6 Decision support software
    9.7 Conclusions

    10. Applications in antitumor therapy
    10.1 Introduction
    10.2 Tumor growth model
    10.3 Tumor growth and capillary transport
    10.4 Optimization of tumor medical treatment
    10.5 Conclusions

    11.Summary
    11.1 Major contributions
    11.2 Future directions
    11.3 Acknowledgments

Product details

  • No. of pages: 280
  • Language: English
  • Copyright: © Academic Press 2020
  • Published: April 16, 2020
  • Imprint: Academic Press
  • Paperback ISBN: 9780128156537
  • eBook ISBN: 9780128156544

About the Authors

Yuri Vassilevsky

Professor, corresponding member of Russian Academy of Sciences Yuri Vassilevski is the deputy director of Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, the head of Laboratory of mathematical modelling in medicine of Sechenov University, the head of the department of computational technologies and modelling in geophysics and biomathematics at Moscow Institute of Physics and Technology and the head of the department of mathematics, mechanics and mathematical modelling at Sechenov University. He received his PhD Degree from Institute of Numerical Mathematics, Russian Academy of Science (1993) and second doctorate (Habilitation) in Mathematics at the same institute (2006). His research interests are in adaptive meshing, numerical analysis, mathematical modelling and scientific computing with applications in geophysics and biomedical engineering. From 2013 he serves as the Managing Editor of the Russian Journal of Numerical Analysis and Mathematical Modelling.

Affiliations and Expertise

Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow Institute of Technology, Sechenov University

Maxim Olshanskii

Maxim Olshanskii is currently professor of Mathematics at the University of Houston. He also holds adjunct professorships at Department of Mathematics and Computer Science at Emory University. He was previously professor at the Department of Mathematics and Mechanics at Moscow State University. He received his PhD degree from Moscow State University (1997) and second doctorate (Habilitation) in Mathematics from the Institute of Numerical Mathematics, Russian Academy of Sciences (2006). His research interests are in numerical analysis and scientific computing, with applications to fluid problems, interface and free boundary problems, geometric PDEs, and cardiovascular models. He is a recipient of research awards by multiple agencies in USA, Russia and Germany as well as the Prize of the European Academy for Russian young scientists (2001). From 2014 he serves as the Managing Editor of the Journal of Numerical Mathematics.

Affiliations and Expertise

Professor, University of Houston, Texas, USA

Sergey Simakov

Sergey Simakov is the deputy chair of the department of computational physics, at Moscow Institute of Physics and Technology, associated professor of the department of computational physics at Moscow Institute of Physics and Technology, senior researcher of Laboratory of human physiology of Moscow Institute of Physics and Technology, senior researcher of Laboratory of mathematical modelling in medicine of Sechenov University and associated professor of the department of mathematics, mechanics and mathematical modelling at Sechenov University. He received his PhD degree from Moscow Institute of Physics and Technology (2006) in Mathematics. His research interests are in numerical methods, wave processes in a network, biological flows including cardiovascular and respiratory systems, biomedical engineering.

Affiliations and Expertise

Moscow Institute of Physics and Technology, Sechenov University

Andrey Kolobov

PhD Andrey Kolobov is the scientific secretary of Lebedev Physical Institute of the Russian Academy of Sciences, senior scientist in Laboratory of Nonlinear Dynamics and Theoretical Biophysics He received his PhD Degree from Lomonosov Moscow State University in 2004. His research interests are mathematical modeling in oncology with account of tumor associated angiogenesis, nonlinear dynamics of complex systems, study of combustion processes such as flame ignition and deflagration. Andrey Kolobov works closely with Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences and Peoples' Friendship University of Russia.

Affiliations and Expertise

Lebedev Physical Institute of the Russian Academy of Sciences

Alexander Danilov

Alexander Danilov is the senior researcher at Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, Laboratory of mathematical modelling in medicine of Sechenov University, and Laboratory of human physiology at Moscow Institute of Physics and Technology. He received his PhD Degree from Institute of Numerical Mathematics, Russian Academy of Sciences in 2010. He is a laureate of Russian academy of sciences medal with prizes for young scientists of Russian academy of sciences, other agencies and organizations of Russia for best work in 2011. His research interests are in mesh generation, image segmentation, mathematical modelling and scientific computing in biomedical engineering.

Affiliations and Expertise

Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow Institute of Physics and Technology, Sechenov University

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