Paper
1 January 1998 Computer simulation model of tumor treatment: fractionated irradiation
Alexei A. Ivankov
Author Affiliations +
Proceedings Volume 3345, International Workshop on New Approaches to High-Tech Materials: Nondestructive Testing and Computer Simulations in Materials Science and Engineering; (1998) https://doi.org/10.1117/12.299617
Event: International Workshop on New Approaches to High Tech Materials: Nondestructive Testing and Computer Simulations in Materials Science and Engineering, 1997, St. Petersburg, Russian Federation
Abstract
A new stochastic model of tumor growth is developed. The main goal of the investigation is to get some estimates of observable and unobservable parameters of tumor growth process under given assumptions of malignant cell behavior. The model allows to come over some difficulties encountered in reaching the above-mentioned goal by methods of stochastic branching processes theory, i.e. if the independence hypothesis is not valid. The principal phenomena of cellular level were taken into account to simulate cell population development: cell proliferation, reproduction, reproductive type of cell death and apoptosis. The model allows as well to simulate tumor treatment: radiotherapy and/or drug administration. The treatment is considered as a stochastic process of damage accumulation and reparation into malignant cell. This approach to biological phenomena modeling is extremely fruitful to test statistical hypothesis on the nature and mechanisms of tumor growth, in particular, on tumor growth latency.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alexei A. Ivankov "Computer simulation model of tumor treatment: fractionated irradiation", Proc. SPIE 3345, International Workshop on New Approaches to High-Tech Materials: Nondestructive Testing and Computer Simulations in Materials Science and Engineering, (1 January 1998); https://doi.org/10.1117/12.299617
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KEYWORDS
Tumor growth modeling

Stochastic processes

Performance modeling

Computer simulations

Tumors

Radiotherapy

Cell death

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