Computational Modeling in Tissue Engineering

  • Liesbet Geris

Part of the Studies in Mechanobiology, Tissue Engineering and Biomaterials book series (SMTEB, volume 10)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Meir Israelowitz, Birgit Weyand, Syed W. H. Rizvi, Christoph Gille, Herbert P. von Schroeder
    Pages 19-45
  3. Ali Nekouzadeh, Guy M. Genin
    Pages 47-83
  4. Dennis Lambrechts, Jan Schrooten, Tom Van de Putte, Hans Van Oosterwyck
    Pages 85-105
  5. Andy L. Olivares, Damien Lacroix
    Pages 107-126
  6. Jörg Galle, Martin Hoffmann, Axel Krinner
    Pages 183-205
  7. Hiroto Sasaki, Fumiko Matsuoka, Wakana Yamamoto, Kenji Kojima, Hiroyuki Honda, Ryuji Kato
    Pages 207-226
  8. RD O’Dea, HM Byrne, SL Waters
    Pages 229-266
  9. Manuela Teresa Raimondi, Paola Causin, Matteo Laganà, Paolo Zunino, Riccardo Sacco
    Pages 267-285
  10. Jason W. Bjork, Anton M. Safonov, Robert T. Tranquillo
    Pages 287-306
  11. Paul N. Watton, Huifeng Huang, Yiannis Ventikos
    Pages 309-339
  12. Esther Reina-Romo, Clara Valero, Carlos Borau, Rafael Rey, Etelvina Javierre, María José Gómez-Benito et al.
    Pages 379-404
  13. Greg Lemon, John R. King, Paolo Macchiarini
    Pages 405-439
  14. Back Matter
    Pages 441-442

About this book


One of the major challenges in tissue engineering is the translation of biological knowledge on complex cell and tissue behavior into a predictive and robust engineering process. Mastering this complexity is an essential step towards clinical applications of tissue engineering. This volume discusses computational modeling tools that allow studying the biological complexity in a more quantitative way. More specifically, computational tools can help in:

 (i) quantifying and optimizing the tissue engineering product, e.g. by adapting scaffold design to optimize micro-environmental signals or by adapting selection criteria to improve homogeneity of the selected cell population;

(ii) quantifying and optimizing the tissue engineering process, e.g. by adapting bioreactor design to improve quality and quantity of the final product; and

(iii) assessing the influence of the in vivo environment on the behavior of the tissue engineering product, e.g. by investigating vascular ingrowth.

The book presents examples of each of the above mentioned areas of computational modeling.  The underlying tissue engineering applications will vary from blood vessels over trachea to cartilage and bone.  For the chapters describing examples of the first two areas, the main focus is on (the optimization of) mechanical signals, mass transport and fluid flow encountered by the cells in scaffolds and bioreactors as well as on the optimization of the cell population itself.  In the chapters describing modeling contributions in the third area, the focus will shift towards the biology, the complex interactions between biology and the micro-environmental signals and the ways in which modeling might be able to assist in investigating and mastering this complexity. The chapters cover issues related to (multiscale/multiphysics) model building, training and validation, but also discuss recent advances in scientific computing techniques that are needed to implement these models as well as new tools that can be used to experimentally validate the computational results.


Biological Response Biological Substitutes Bioreactor Design Bone Tissue Modeling Cartilage Tissue Modeling Heart Tissue Modeling Liver Tissue Modeling Micro-Environmental Signals

Editors and affiliations

  • Liesbet Geris
    • 1
  1. 1., Biomechanics Research UnitUniversity of LiègeLiège 1Belgium

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-32562-5
  • Online ISBN 978-3-642-32563-2
  • Series Print ISSN 1868-2006
  • Series Online ISSN 1868-2014
  • Buy this book on publisher's site
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