ESTRO 2020 Abstract book

S226 ESTRO 2020

SP-0391 TCP modelling for better radiotherapy plans I. Toma-Dasu 1 1 Karolinska Institutet and Stockholm University, Medical Radiation Physics, Stockholm, Sweden Abstract text Modern radiotherapy employs radiobiological models for calculating tumour control probability (TCP) and normal tissue complication probability (NTCP) at different points starting from treatment planning optimisation to treatment outcome evaluation. The modelling of the probability of controlling the tumour relies on the assumption that all the cells in the tumour need to be eradicated in order to prevent the local recurrence. Mathematically this assumption could be expressed as a function of the initial number of clonogenic cells in the tumour and the probability they will survive a certain radiation therapy regimen. There are, however, many challenges to overcome in order to adequately account for the different degrees of complexity of the tumour biology and physiology as well as for the complexity of the treatment in order to use a TCP model for a certain clinical application. This presentation aims to make a review of the TCP models accounting for the various levels of complexity and to illustrate their applications in modern radiotherapy. The modelling of TCP for a population of patients as well as for individual patients will be considered. Particular emphasis will be put on the latter in light of the increased interest in the clinical community for individualised radiotherapy going beyond dose conformity. One of the current trends in radiotherapy planning involves the use of heterogeneous target dose distributions. They might be the result of an optimised plan involving high modulation of the intensity of the beams, hence highly heterogeneous fluence distributions, aiming at increasing conformity of the prescribed high doses to targets of complex shape or in close vicinity of the organs at risk. The heterogeneous dose distributions might also be intentionally planned since the classic paradigm of homogeneous dose prescription to the target has been challenged and novel dose prescription approaches accounting for the spatial distribution of subvolumes consisting of cells with different sensitivities to radiation have been proposed. Thus, accounting for the heterogeneity of the dose distribution over the target is a prerequisite of any TCP model. The new trends on going beyond the heterogeneity in dose in characterising the energy deposition events leading to biological effects will be also discussed. In addition to the heterogeneity in the physical factors, one has to account in the modelling of TCP for the heterogeneity in the biological factors affecting the sensitivity to radiation and the overall tumour response, including the heterogeneity in the density of clonogenic cells and in the factors related to the complex tumour microenvironment. Tumours are dynamic systems with respect to their radiosensitivity and therefore modelling TCP should consider both the spatial and the temporal variations of the radiotherapy factors influencing the outcome. The applicability of TCP models for biological optimisation of the treatment plans is limited by the availability of their parameters. The overall accuracy as well as the sensitivity and specificity of the prediction of the outcome based on TCP models are also highly dependent on the model parameters. The parameters describing the dose-response in terms of probability of controlling the target could be empirically derived based on the response of a population

of patients, but their applicability for predicting the response of individual patients is highly questionable. Different approaches could therefore be considered for deriving the parameters for the TCP models. The increasing role of functional imaging in conjunction with preclinical assays for the assessment of TCP model parameters will be discussed. Finally, the role of radiobiological modelling in planning evaluation and patient selection for different treatment modalities will be presented. The limitations as well as the potential of the models for TCP will be acknowledged. The modelling of the tumour control probability together with the a priory toxicity predictions could help guiding the treatment planning process towards individualised approaches to the great benefit of the patients. SP-0392 The role of functional imaging in radiotherapy planning D. Sloth Møller 1 1 Aarhus University Hospital, Department Of Medical Physics, Aarhus C, Denmark Abstract text In radiotherapy of tumors with a high risk of local recurrence, higher radiation dose levels may be required. In many tumor sites there is evidence that the site of recurrence correlates with areas with high uptake of functional markers such as 18F-FDG (metabolism) or 18F- FMISO (hypoxia) used for PET-CT imaging [1,2]. This suggests that functional imaging before or during the radiotherapy treatment may be used to define areas of the tumor that are more resistant to radiotherapy than others. However, to date there exist no predictive evidence that selectively escalating the dose to areas with high functional uptake will lead to improved local control. During the past decades the definition and stability of the high uptake areas has been studied intensely with dose escalation in mind. The extension and shape of the high uptake areas depends on scanner hardware, scanning protocols, reconstruction and segmentation algorithms. Further, for some tumor types the areas of high uptake have been shown to vary from day to day, while 18F-FDG has proved quite stable for lung cancer. If uptake is stable, dose escalation areas may be defined as dose escalation volumes (dose painting by volume) with various delineation/segmentation methods or by uptake intensity on a voxel basis (dose painting by numbers). The voxel based approach is more loyal to the functional signal but, it may be more sensitive to the mentioned uncertainties than the volume based approach making it less reliable. In clinical practice, the geometric uncertainties and anatomical changes during radiotherapy treatment delivery often deteriorates the dose distribution, blurring the effect of dose escalation for both methods.