Computational simulator that calculates tumor control probability in a tumor heterogeneously irradiated for fractionated radiation oncology treatments

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.

The use of the normal tissue non-complication probability (NTCP0) methodology as a new alternative of assessing side-effects in brachytherapy treatments

“…Some previously discussed aspects and others of [ 7 ] are probabilistic foundations of our NTCP0 applications, and show why its validation is a priori. The validation of the NTCP0 methodologies is a priori because these are wholly based on strong probabilistic foundations, such as the normal complications of the specific radiation oncology treatments, as stochastic processes of more than outcome, have their own NTCP(x i ) DPDs, where NTCP0 = NTCP(0).…”

“…Nowadays, as described in [10], [17] and [24], the NTCP studies have been focused on separated OARs, or the principal late complications of a radiation treatment of an OAR; however, these treatments have various normal tissue complications; in other words, they have their own associated NTCP(x i ) DPDs. Some previously discussed aspects and others of [7] are probabilistic foundations of our NTCP0 applications, and show why its validation is a priori. The validation of the NTCP0 methodologies is a priori because these are wholly based on strong probabilistic foundations, such as the normal complications of the specific radiation oncology treatments, as stochastic processes of more than outcome, have their own NTCP(x i ) DPDs, where NTCP0 = NTCP(0).…”

“…The tumor control probability (TCP) is a metric related to cell kill in a determined tumor tissue. For this reason, one can estimate its value using a computational simulation based on its own probabilistic concept, as has been developed in [ 7 ]. Contrary to simulated TCP calculations, nowadays, the determination of NTCP0 by means of mathematical models or computational simulations for treatments with few or no data is very complicated or almost impossible.…”

Combination of anti-PD-L1 and radiotherapy in hepatocellular carcinoma: a mathematical model with uncertain parameters

“…The new methodology of the model without any analytical formulation was developed to calculate tumor control probability by applying RT. 37 In our study, a compartmental set of differential equations was used to simulate the delayed effect of RT on cancer death in a deterministic manner. Our deterministic model defined the DNA-double strand breaks and consequently cancer cell death as a result of RT.…”