Dose-Response Relations for Tumors and Normal Tissues

The clinical implementation of radiobiological models is a prerequisite for an accurate optimization of radiotherapy. However, to achieve this goal, a number of factors have to be considered and procedural steps to be taken. This chapter examines methods for extracting dose–response relations for tumor and normal tissues from clinical patient data. In order to demonstrate the practical aspects of those methods, different clinical examples are employed such as that of anal sphincter regarding determination of the dose–response relations for the end points of fecal leakage and blood or phlegm in stools. One aspect of the quality assurance of radiobiological treatment plan optimization is the validation of the determined dose–response relations. In the literature, different statistical methods have been utilized for this purpose (e.g., maximum likelihood method, Pearson’s test, and receiver operating characteristic curves), which are demonstrated here for validating the dose–response relations of the lung regarding the end point of radiation pneumonitis. Apart from the methodology by which the radiobiological parameters are determined, the predictive strength of the different models depends on their inherent structure to account for the relevant biological factors that are related to the treatment outcome. Such factors that are examined here are (a) volume effect, (b) different fractionation correction approaches, (c) the generalization of the normalized dose–response gradient to nonuniform dose delivery and multiple target volumes and normal tissues, (d) factors affecting the clinically observed patient radiosensitivity variation, and (e) the impact of inter- and intrapatient radiosensitivity variation on treatment plan evaluation and radiotherapy optimization.