Simulator of radiation biological effects in tumor in order to determinate the tumor control probability

Background: Currently, tumor control probability (TCP) can be determined through experiments and observations, which enable deriving its values and construction of phenomenological and mechanistic TCP models. However, there are few experiments and observations extent; for this reason the development...

Full description

Bibliographic Details
Main Authors: Terman Frometa-Castillo, Anil Pyakuryal, Raul Piseaux-Aillon
Format: Article
Language:English
Published: Elsevier 2019-01-01
Series:Informatics in Medicine Unlocked
Online Access:http://www.sciencedirect.com/science/article/pii/S2352914819301546
Description
Summary:Background: Currently, tumor control probability (TCP) can be determined through experiments and observations, which enable deriving its values and construction of phenomenological and mechanistic TCP models. However, there are few experiments and observations extent; for this reason the development of virtual simulations is an interesting option for the determination of TCP. Method: Probabilistic descriptions were made of three kinds of cells, and the effects of radiation interaction with each tumor cell was investigated. For a homogeneously irradiated tumor with a dose d, the “TumorRBEf” simulator determines the TCP using simulations of a fractioned treatment, based on the tumor cell ratio sensitivities (cell kill and cell sublethal damage), tumor volume, cell density, and number of fractions. Results: In this study, a simulator was developed to estimate the TCP using a new methodology. The TCP was calculated from a fractioned treatment as a ratio of simulations, with 100% of killed cells and total of simulations. This technique may be useful for determining optimal treatment schedules, and as a teaching tool. Conclusions: Despite that the first version of this simulator neglected tumor cellular processes, such as cell repair and cell repopulation, the current version provides hypothesis-generating results. The simulator has whole probabilistic foundations, using probabilities, such as the probability of meeting a killed cell, of killing an undamaged cell, and of killing a sublethal damage cell. Keywords: Simulation, TCP, Probability, Stochastic process
ISSN:2352-9148