Abstract
We discuss the components and main requirements of the interactive visualization and simulation system intended for better understanding the dynamics of solid tumor proliferation. The heterogeneous Complex Automata, discrete-continuum model is used as the simulation engine. It combines Cellular Automata paradigm, particle dynamics and continuum approaches to model mechanical interactions of tumor with the rest of tissue. We show that to provide interactivity, the system has to be efficiently implemented on workstations with multiple cores CPUs controlled by OpenMP interface and/or empowered by GPGPU accelerators. Currently, the computational power of modern CPU and GPU processors enable to simulate the tumors of a few millimeters in diameter in its both avascular and angiogenic phases. To validate the results of simulation with real tumors, we plan to integrate the tumor modeling simulator with the Graph Investigator tool. Then one can validate the simulation results on the base of topological similarity between the tumor vascular networks obtained from its direct observation and simulation. The interactive visualization system can have both educational and research aspects. It can be used as a tool for clinicians and oncologists for educational purposes and, in the nearest future, in medical in silico labs doing research in anticancer drug design and/or in planning cancer treatment.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 607-637 |
| Number of pages | 31 |
| Journal | Lecture Notes in Earth System Sciences |
| Volume | 0 |
| Issue number | 9783642164040 |
| DOIs | |
| State | Published - 2013 |
Bibliographical note
Funding Information:Acknowledgments This research is financed by the Polish Ministry of Higher Education and Science, project N519 579338 and partially by AGH grant No. 11.11.120.777. We would like to thank Nvidia Company for support and donating Authors with Tesla C1060 GPU. The Authors are also very grateful to Professor Dr Arkadiusz Dudek MD PhD from University of Minnesota Medical School, Division of Hematology, Oncology, and Transplantation, Department of Medicine, and Mr Piotr Pawliczek from AGH Institute of Computer Science for cooperation in designing algorithms and preparing timings on GPU processors.
Funding Information:
This research is financed by the Polish Ministry of Higher Education and Science, project N519 579338 and partially by AGH grant No. 11.11.120.777. We would like to thank Nvidia Company for support and donating Authors with Tesla C1060 GPU. The Authors are also very grateful to Professor Dr Arkadiusz Dudek MD PhD from University of Minnesota Medical School, Division of Hematology, Oncology, and Transplantation, Department of Medicine, and Mr Piotr Pawliczek from AGH Institute of Computer Science for cooperation in designing algorithms and preparing timings on GPU processors.
Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2013.
Keywords
- CPU vs. GPGPU
- Complex automata model
- Complex networks
- Interactive visualization
- Parallel computations
- Tumor growth
