Modellierung und Simulation von Wachstum in weichen Biomaterialien

• Antragsteller: Professor Dr.-Ing. Paul Steinmann
• Fachliche Zuordnung: Mechanik ; Angewandte Mechanik, Statik und Dynamik
• Förderung: Förderung von 2014 bis 2021
• Projektkennung: Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 241697724

• Erstellungsjahr: 2021

Zusammenfassung der Projektergebnisse

Brain tissue is not only one of the most important but also arguably the most complex and compliant tissue in the human body. While long underestimated, increasing evidence confirms that mechanics plays a critical role in modulating brain function and dysfunction. Computational simulations based on the field equations of nonlinear continuum mechanics can provide important insights into the underlying mechanisms of brain development, injury and disease that go beyond the possibilities of traditional diagnostic tools. Realistic numerical predictions, however, require mechanical models that are capable of capturing the complex and unique characteristics of this ultrasoft, heterogeneous, and active tissue. In recent years, contradictory experimental results have caused confusion and hindered rapid progress. In this project, we have experimentally characterized the mechanical behavior of brain tissue behavior using different testing modalities, and have developed constitutive models that are capable of capturing the tissue response under multiple loading conditions and in different brain regions. We have demonstrated that is is important to choose the constitutive model and corresponding model parameters depending on the application of interest. These results are highly valuable for the future design of new experiments and the guided selection of appropriate constitutive models for specific applications. Mechanical models that capture the complex behavior of nervous tissues and are accurately calibrated with reliable and comprehensive experimental data are key to performing reliable predictive simulations. We have further demonstrated that a mechanical model of brain growth can significantly advance our understanding of the underlying mechanisms of cortical folding during brain development. Ultimately, mathematical modeling and computational simulations of the brain are useful for both biomedical and clinical communities, and cover a wide range of applications ranging from predicting disease progression, estimating injury risk, or planning surgical procedures. Taken together, the project resulted in 21 peer-reviewed journal publications, numerous talks at international meetings, and a dissertation that has received multiple Awards, including the Bertha Benz-Prize by the Daimler and Benz Foundation and the ECCOMAS Best PhD Award by the European Community on Computational Methods in Applied Sciences.

Projektbezogene Publikationen (Auswahl)

• Mechanical characterization of human brain tissue. Acta Biomater. 48 (2017): 319-340
  S. Budday, G. Sommer, C. Birkl, C. Langkammer, J. Haybaeck, J. Kohnert, M. Bauer, F. Paulsen, P. Steinmann, E. Kuhl, and G. A. Holzapfel
  
• Rheological characterization of human brain tissue. Acta Biomater. 60 (2017): 315-329
  S. Budday, G. Sommer, J. Haybaeck, P. Steinmann, G. A. Holzapfel, and E. Kuhl
  
• Viscoelastic parameter identification of human brain tissue. J. Mech. Behav. Biomed. Mater. 74 (2017): 463-476
  S. Budday, G. Sommer, P. Steinmann, G. A. Holzapfel, and E. Kuhl
  
• Fifty Shades of Brain: A Review on the Mechanical Testing and Modeling of Brain Tissue. Arch. Comput. Methods Eng. 27 (2020): 1187-1230
  S. Budday, T. C. Ovaert, G. A. Holzapfel, P. Steinmann, and E. Kuhl