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Aspects of modelling and simulating tumor growth and treatment

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Summary

The proliferation of malignant cells and tumor growth can be studied at various levels and from different viewpoints in the field of tumor biology and oncology. The aim of this paper is to outline how control theory and computer science can pave the way to new approaches to interpreting tumor growth and treatment. The present development is based on the hypothesis that the proliferation of malignant cells may be simulated by an unstable closed-loop control circuit. This type of model only describes the number of cells as a function of time. Therefore, an extended model permitting the study of the spatial structure of tumor growth is chosen. This approach leads to three-dimensional models simulating tumor growth in a vascularized tissue segment and opens the possibility of determining optimized chemotherapeutic tumor-treatment schedules. In the future it may become possible to perform computer simulations of different kinds of tumor treatment prior to clinical therapy.

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References

  • Braun AC (1977) The story of cancer. Addison-Wesley, Reading, MA

    Google Scholar 

  • Düchting W (1976) Computer simulation of abnormal erythropoiesis — an example of cell renewal regulating systems. Biomed 21:34–43

    Google Scholar 

  • Düchting W, Dehl G (1980) Spatial growth of tumors, a simulation study. In: Fedina L, Kanyár B, Kocsis B, Kollai M (eds) Mathematical and computational methods in physiology. Pergamon Press, Akadémiai Kiadó, Budapest (Advances in Physiological Science, vol 34. pp 123–131)

    Google Scholar 

  • Düchting W, Vogelsaenger T (1981) Three-dimensional pattern generation applied to spheroidal tumor growth in a nutrient medium. Int J Biomed Comput 12:377–392

    Google Scholar 

  • Düchting W, Vogelsaenger T (1982) Modelling and simulation as a tool for optimizing the treatment of tumor diseases. In: Proceedings of the 10th IMACS world congress on system simulation and scientific computation, Montreal (vol 3, pp 77–80)

  • Eisen M (1979) Mathematical models in cell biology and cancer. Springer, Berlin Heidelberg New York

    Google Scholar 

  • Folkman J, Hochberg M (1973) Self-regulation of growth in three dimensions. J Exp Med 138:745–753

    Google Scholar 

  • Rajewsky MF (1966) Zellproliferation in normalen und malignen Geweben: 3H-Thymidin-Einbau in vitro unter Standardbedingungen. Biophysik 3:65–93

    Google Scholar 

  • Rajewsky MF (1974) Proliferative properties of malignant cell systems. In: Altman HW et al. (eds) Handbuch der Allgemeinen Pathologie: Tumors I, VI/5. Springer, Berlin Heidelberg New York, pp 289–325

    Google Scholar 

  • Taylor S, Folkman J (1982) Protamine is an inhibitor of angiogenesis. Nature 297:307–312

    Google Scholar 

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The “Journal of Cancer Research and Clinical Oncology” publishes in loose succession “Editorials” and “Guest Editorials” on current and/or controversial problems in experimental and clinical oncology. These contributions represent exclusively the personal opinion of the author.

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Düchting, W., Vogelsaenger, T. Aspects of modelling and simulating tumor growth and treatment. J Cancer Res Clin Oncol 105, 1–12 (1983). https://doi.org/10.1007/BF00391824

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  • DOI: https://doi.org/10.1007/BF00391824

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