<p>The present thesis is focused on the development and application of dose response models for radiation therapy. Radiobiological models of tissue response to radiation are an integral part of the radiotherapeutic process and a powerful tool to optimize tumor control and minimize damage to healthy tissues for use in clinical trials. Ideally, the models could work as a historical control arm of a clinical trial eliminating the need to randomize patents to suboptimal therapies. In the thesis overview part, some of the basic properties of the dose response relation are reviewed and the most common radiobiological dose-response models are compared with regard to their ability to describe experimental dose response data for rat spinal cord using the maximum likelihood method. For vascular damage the relative seriality model was clearly superior to the other models, whereas for white matter necrosis all models were quite good except possibly the inverse tumor and critical element models. The radiation sensitivity, seriality and steepness of the dose-response relation of the spinal cord is found to vary considerably along its length. The cervical region is more radiation sensitive, more parallel, expressing much steeper dose-response relation and more volume dependent probability of inducing radiation myelitis than the thoracic part. The higher number of functional subunits (FSUs) consistent with a higher amount of white matter close to the brain may be responsible for these phenomena. With strongly heterogeneous dose delivery and due to the random location of FSUs, the effective size of the FSU and the mean dose deposited in it are of key importance and the radiation sensitivity distribution of the FSU may be an even better descriptor for the response of the organ. An individual optimization of a radiation treatment has the potential to increase the therapeutic window and improve cure for a subgroup of patients.</p>

The present thesis is focused on the development and application of dose response models for radiation therapy. Radiobiological models of tissue response to radiation are an integral part of the radiotherapeutic process and a powerful tool to optimize tumor control and minimize damage to healthy tissues for use in clinical trials. Ideally, the models could work as a historical control arm of a clinical trial eliminating the need to randomize patents to suboptimal therapies. In the thesis overview part, some of the basic properties of the dose response relation are reviewed and the most common radiobiological dose-response models are compared with regard to their ability to describe experimental dose response data for rat spinal cord using the maximum likelihood method. For vascular damage the relative seriality model was clearly superior to the other models, whereas for white matter necrosis all models were quite good except possibly the inverse tumor and critical element models. The radiation sensitivity, seriality and steepness of the dose-response relation of the spinal cord is found to vary considerably along its length. The cervical region is more radiation sensitive, more parallel, expressing much steeper dose-response relation and more volume dependent probability of inducing radiation myelitis than the thoracic part. The higher number of functional subunits (FSUs) consistent with a higher amount of white matter close to the brain may be responsible for these phenomena. With strongly heterogeneous dose delivery and due to the random location of FSUs, the effective size of the FSU and the mean dose deposited in it are of key importance and the radiation sensitivity distribution of the FSU may be an even better descriptor for the response of the organ. An individual optimization of a radiation treatment has the potential to increase the therapeutic window and improve cure for a subgroup of patients.

A set of mathematical models, known as radiobiological Dose-Response models, have been developed, to model the biological effects and complications that arise following irradiation. The overall objective is to be able to apply these in clinical practice with confidence, and ensure more successful treatments are given to patients. This investigation serves to assess these models and their predictive power of NTCP following irradiation of the lung. Clinical data, from patients treated for inoperable stage III non-small cell lung cancer is obtained and the consequent biological effect (severity of pneumonitis) observed as a result of this radiation treatment is assessed by the models. By gaining more knowledge about the 3D dose-distribution and the incidence of radiation pneumonitis through the evaluation of the models, the main treatment goal, which is to maximise TCP and minimise NTCP can be achieved. Post treatment data is obtained regarding the clinical outcome or clinical endpoint for each patient, considered to be Radiation Pneumonitis. The clinical endpoint is a specific biological effect that may or may not have occurred,after a certain period, following irradiation. The models are assessed on their ability to predict a NTCP value that corresponds to the resulting clinical endpoint following treatment. Furthermore a software tool for the calculation of NTCP’s by the models is developed, in an attempt to provide an important tool for optimization of radiotherapy treatment planning. With our findings from this study, our aim is to further strengthen, support and challenge already existing literature on dose-response modelling. / -