A Novel Medical Image Data-Based Multi-Physics Simulation Platform for Computational Life Sciences

Esra Neufeld, Dominik Szczerba, Nicolas Chavannes, and Niels Kuster, Interface Focus, Volume 3, Issue 3, April 2013, online February 21, 2013

Modeling complex biological systems in computational life sciences requires specialized tools that can perform medical-image-data-based simulations and can handle complex and realistic anatomical models. The required solvers must be optimized for modeling living tissue and high-performance-computing-enabled to cope with the frequently large numerical problems. A multi-physics platform that satisfies these requirements has been implemented and used to investigate a wide variety of relevant applications, some of which are presented in this paper. The simulation platform consists of detailed, parameterized anatomical models, a segmentation and meshing tool, a wide range of solvers and optimizers, a framework for the rapid development of specialized and parallelized finite element method solvers, a toolkit-based visualization engine, a PYTHON scripting interface for customized applications, a coupling framework, and more.

The scientific impact of this study can be summarized as:

  • A multi-physics simulation platform has been developed that can be employed to support device development and optimization, safety assessment, basic research, and treatment planning.
  • The platform includes novel, high-performance-computing-enhanced solvers optimized for modeling living tissue.
  • The platform has been applied to relevant topics such as hyperthermia cancer treatment planning, tumor growth modeling, evaluation of the magneto-haemodynamic effect as a biomarker, and physics-based morphing of anatomical models.
  • The platform offers a flexible, powerful environment in which to perform realistic simulations of physical, physiological, and biological effects in living tissue and complex anatomies.
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