A novel dose-volume metric for optimizing therapeutic ratio through fractionation: Retrospective analysis of lung cancer treatments

Abstract

The bifurcation numbers are strongly consistent with prescribed clinical fractionation protocols for NSCLC treatments. Due to their scale-free property the B-numbers may assist in the selection of an appropriate fractionation once the dose distribution has been optimized.

The emergence of nonuniform spatiotemporal fractionation schemes within the standard BED model

“…(1) on fractionation decisions have been studied. The publications [3][4][5] consider the dependence of fractionation schemes on the spatial dose distribution in the normal tissue. Other authors have considered extensions to incorporate effects from repopulation, the overall treatment time, and incomplete repair.…”

A radiobiological model of reoxygenation and fractionation effects

“…It is common in the literature, however, to ignore one or both of these effects when performing modeling studies that compare or optimize different fractionation schedules. [1][2][3][4]9,12 Brenner et al 13 proposed a formula for including reoxygenation/ resensitization in the LQ model assuming a distribution of values of a, but the model was designed to describe surviving fraction changes with time between two fractions separated by a few hours rather than different fractionation schedules. Our model is different in that it neglects inter/intra patient variations among the LQ parameters a and b and assumes that a certain fraction of existing hypoxic cells take part in the TABLE II.…”

“…Many clinical implementations of BED modeling based on the linear-quadratic (LQ) model explicitly include the effect of tumor cell repopulation 1,2 while others ignore the effect. 3,4 However, none of these works address the potential impact of tumor hypoxia or the effect of tumor cell reoxygenation. While it is known that hypoxia is an important factor that can limit tumor control and that the reoxygenation effect can favor fractionation schedules with larger number of fractions, there is no simple way to include these effects in BED expressions of different fractionation schedules.…”

Optimization of the fractionated irradiation scheme considering physical doses to tumor and organ at risk based on dose–volume histograms

“…Recently, Mizuta et al have proposed a mathematical method to select a fractionation regimen based on physical dose distribution, 18 and relevant investigations into this have been reported subsequently. [19][20][21][22] Following the paper, 18 the authors also presented a graphical method using a "TO plot" to determine the appropriate fractionation regimen based on the relation between radiation effects on the tumor and an organ at risk (OAR). 23 These studies have shown explicit criteria for selecting better fractionation methods, which are determined by the physical dose distribution and the α/ β value in the linear-quadratic (LQ) model.…”