Purpose. To determine the dose response parameters and the fractionation sensitivity of prostate tumours from clinical results of patients treated with external beam radiotherapy. Material and methods. The study was based on five-year biochemical results from 14 168 patients treated with external beam radiotherapy. Treatment data from 11 330 patients treated with conventional fractionation have been corrected for overall treatment time and fitted with a logit equation. The results have been used to determine the optimum α/β values that minimise differences in predictions from 2838 patients treated with hypofractionated schedules. Results. Conventional fractionation data yielded logit dose response parameters for all risk groups and for all definitions of biochemical failures. The analysis of hypofractionation data led to very low α/β values (1–1.7 Gy) in all mentioned cases. Neglecting the correction for overall treatment time has little impact on the derivation of α/β values for prostate cancers. Conclusions. These results indicate that the high fractionation sensitivity is an intrinsic property of prostate carcinomas and they support the use of hypofractionation to increase the therapeutic gain for these tumours.

The tumour microenvironment is considered to be responsible for the outcome of cancer treatment and therefore it is extremely important to characterize and quantify it. Unfortunately, most of the experimental techniques available now are invasive and generally it is not known how this influences the results. Non-invasive methods on the other hand have a geometrical resolution that is not always suited for the modelling of the tumour response. Theoretical simulation of the microenvironment may be an alternative method that can provide quantitative data for accurately describing tumour tissues. This paper presents a computerized model that allows the simulation of the tumour oxygenation. The model simulates numerically the fundamental physical processes of oxygen diffusion and consumption in a two-dimensional geometry in order to study the influence of the different parameters describing the tissue geometry. The paper also presents a novel method to simulate the effects of diffusion-limited (chronic) hypoxia and perfusion-limited (acute) hypoxia. The results show that all the parameters describing tissue vasculature are important for describing tissue oxygenation. Assuming that vascular structure is described by a distribution of inter-vessel distances, both the average and the width of the distribution are needed in order to fully characterize the tissue oxygenation. Incomplete data, such as distributions measured in a non-representative region of the tissue, may not give relevant tissue oxygenation. Theoretical modelling of tumour oxygenation also allows the separation between acutely and chronically hypoxic cells, a distinction that cannot always be seen with other methods. It was observed that the fraction of acutely hypoxic cells depends not only on the fraction of collapsed blood vessels at any particular moment, but also on the distribution of vessels in space as well. All these suggest that theoretical modelling of tissue oxygenation starting from the basic principles is a robust method that can be used to quantify the tissue oxygenation and to provide input parameters for other simulations.

Theoretical predictions of cancer risk from radiotherapy may be used as a complementary criterion for the selection of successful treatment plans together with the classical approach of estimating the possible deterministic effects. However, any such attempts must take into consideration the specific features of radiation treatment. This paper explores several possible methods for estimating the risk of cancer following radiotherapy in order to investigate the influences of the fractionation and the non-uniformity of the dose to the irradiated organ. The results indicate that dose inhomogeneity plays an important role in predicting the risk for secondary cancer and therefore for predictive purposes it must be taken into account through the use of the dose volume histograms. They also suggest that the competition between cell killing and the induction of carcinogenic mutations has to be taken into consideration for more realistic risk estimations. Furthermore, more realistic parameters could be obtained if this competition is also included in analyses of epidemiological data from radiotherapy applications.

Purpose:: Currently in proton radiation therapy, a constant relative biological effectiveness (RBE) equal to 1.1 is assumed. The purpose of this study is to evaluate the impact of disregarding variations in RBE on the comparison of proton and photon treatment plans.Methods:: Intensity modulated treatment plans using photons and protons were created for three brain tumor cases with the target situated close to organs at risk. The proton plans were optimized assuming a standard RBE equal to 1.1, and the resulting linear energy transfer (LET) distribution for the plans was calculated. In the plan evaluation, the effect of a variable RBE was studied. The RBE model used considers the RBE variation with dose, LET, and the tissue specific parameter α/β of photons. The plan comparison was based on dose distributions, DVHs and normal tissue complication probabilities (NTCPs).Results:: Under the assumption of RBE = 1.1, higher doses to the tumor and lower doses to the normal tissues were obtained for the proton plans compared to the photon plans. In contrast, when accounting for RBE variations, the comparison showed lower doses to the tumor and hot spots in organs at risk in the proton plans. These hot spots resulted in higher estimated NTCPs in the proton plans compared to the photon plans.Conclusions:: Disregarding RBE variations might lead to suboptimal proton plans giving lower effect in the tumor and higher effect in normal tissues than expected. For cases where the target is situated close to structures sensitive to hot spot doses, this trend may lead to bias in favor of proton plans in treatment plan comparisons.

Purpose. The study presents the implementation of a novel method for incorporating hypoxia information from PET-CT imaging into treatment planning and estimates the efficiency of various optimization approaches. Its focuses on the feasibility of optimizing treatment plans based on the non-linear conversion of PET hypoxia images into radiosensitivity maps from the uptake properties of the tracers used. Material and methods. PET hypoxia images of seven head-and-neck cancer patients were used to determine optimal dose distributions needed to counteract the radiation resistance associated with tumor hypoxia assuming various scenarios regarding the evolution of the hypoxic compartment during the treatment. A research planning system for advanced studies has been used to optimize IMRT plans based on hypoxia information from patient PET images. These resulting plans were compared in terms of target coverage for the same fulfilled constraints regarding the organs at risk. Results. The results of a planning study indicated the clinical feasibility of the proposed method for treatment planning based on PET hypoxia. Antihypoxic strategies would lead to small improvements in all the patients, but higher effects are expected for the fraction of patients with hypoxic tumors. For these, individualization of the treatment based on hypoxia PET imaging could lead to improved treatment outcome while creating the premises for limiting the irradiation of the surrounding normal tissues. Conclusions. The proposed approach offers the possibility of improved treatment results as it takes into consideration the heterogeneity and the dynamics of the hypoxic regions. It also provides early identification of the clinical cases that might benefit from dose escalation as well as the cases that could benefit from other counter-hypoxic measures.

Light-ion radiation therapy against hypoxic tumors is highly curative due to reduced dependence on the presence of oxygen in the tumor at elevated linear energy transfer (LET) towards the Bragg peak. Clinical ion beams using spread-out Bragg peak (SOBP) are characterized by a wide spectrum of LET values. Accurate treatment optimization requires a method that can account for influence of the variation in response for a broad range of tumor hypoxia, absorbed doses and LETs. This paper presents a parameterization of the Repairable Conditionally-Repairable (RCR) cell survival model that can describe the survival of oxic and hypoxic cells over a wide range of LET values, and investigates the relationship between hypoxic radiation resistance and LET. The biological response model was tested by fitting cell survival data under oxic and anoxic conditions for V79 cells irradiated with LETs within the range of 30–500 keV/µm. The model provides good agreement with experimental cell survival data for the range of LET investigated, confirming the robustness of the parameterization method. This new version of the RCR model is suitable for describing the biological response of mixed populations of oxic and hypoxic cells and at the same time taking into account the distribution of doses and LETs in the incident beam and its variation with depth in tissue. The model offers a versatile tool for the selection of LET and dose required in the optimization of the therapeutic effect, without severely affecting normal tissue in realistic tumors presenting highly heterogeneous oxic and hypoxic regions.