Computational simulator that calculates tumor control probability in a tumor heterogeneously irradiated for fractionated radiation oncology treatments. (April 2022)

• Record Type: Journal Article
• Authors: Frometa-Castillo, Terman; Pyakuryal, Anil; Narayanasamy, Ganesh; Wals-Zurita, Amadeo; Piseaux-Aillon, Raul; Mesbahi, Asghar
• Is Part Of: Simulation. Volume 98:Number 4(2022)
• Page Start: 285
• Page End: 294
• Publication Date: 2022-04
• Subjects: Tumor control probability (TCP) -- Poisson distribution -- computational simulation -- Monte Carlo method -- linear-quadratic model -- biologically effective dose (BED); Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/00375497211039460
• Languages: English
• ISSNs: 0037-5497

Abstract

Although in the ionizing radiation field many concepts and processes are currently recognized as radiobiological, there are also probabilistic ones, and a probabilistic treatment makes a better understanding about them. The purpose of this study is to develop a new radiobiological simulator that calculates the tumor control probability (TCP) for a tumor heterogeneously irradiated from a fractioned treatment. The three possible types of cells and the results of interactions of ionizing radiation with each cell of a determined volume are analyzed. For an irradiated region with a dose per fraction d, the simulator determines the radiation biological effects using the cell kill ( K ) and cell sub-lethal damage, volume, cell density, cell repair of damaged cells during the interfractions, and number of fractions. K is determined from its probabilistic complement, the cell survival ( S ), described with the linear-quadratic (LQ) S(d) model as K = 1 − LQ S ( d ). TCP is calculated from computational simulations as in the ratio of simulations with K = 100% and their total. This application opens new avenues for theoretical and experimental investigations concerning simulations of radiation treatments, and methodologies for therapy optimizations. Our simulator represents a novel methodology as TCP is calculated without analytical formulas, but based on its own probabilistic definition.