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Increasing the power of tumour control and normal tissue complication probability modelling in radiotherapy: recent trends and current issues

	author = {Francesco Tommasino and Alan Nahum and Laura Cella},
	title = {Increasing the power of tumour control and normal tissue complication probability modelling in radiotherapy: recent trends and current issues},
	journal = {Translational Cancer Research},
	volume = {6},
	number = {S5},
	year = {2017},
	keywords = {},
	abstract = {The release of a homogeneous high dose to the tumour region has been one of the cornerstones of radiotherapy (RT) treatment since its early days. According to the organ type and to the cancer histology, different doses are required in order to inactivate malignant cells, thus stopping proliferation. However, radiation-induced cell killing is a stochastic process. Tumour control probability (TCP) models have been developed in order to assign a success rate to a given RT treatment. At the same time, there is the need to keep the risks of normal tissue toxicity at an acceptable level. Normal tissue complication probability (NTCP) models provide a means of doing this. Traditionally, TCP and NTCP models combine clinical outcomes with dosimetric information in terms of dose-volume histograms (DVH). Model parameters are derived by mathematical fits to clinical observations and are subsequently used to estimate the risk of tumour relapse or toxicity. In both types of models, all of the patient dosimetric information is condensed into the DVHs, which represents a potential limitation on their descriptive and predictive power. This choice, related to historical and practical reasons, does not allow the full complexity of the 3D dose distribution in the patient to be taken into account. Neglecting these aspects might be relevant in a modern RT setting, which often includes the presence of high dose gradient regions. This has motivated research on ‘advanced’ TCP and NTCP models, able to tackle the problem by looking at a different scale, e.g. in tumour sub-regions or at the single voxel level. This is relevant not only from the purely dosimetric point of view. Increasing evidence is reported on the heterogeneity of cancer tissues, suggesting that non-uniform dose distributions could result in improved survival, for instance if targeted to take into account sub volumes with high clonogen density or hypoxic radioresistant regions. Similarly, radiation-induced side effects are part of a complex biological response, which depends not only on cell killing, but also on the inflammatory response and in some cases on the interplay among different organs. Obviously, conventional NTCP models cannot describe this scenario, and the development of more advanced mathematical tools is needed. This review will be focused on the discussion of recent studies showing possible directions for moving the field of TCP and NTCP modelling forward. Without diminishing the role and usefulness of available models, the aim is to shed light on the benefits that might be achieved by ‘enhanced’ modelling. This could represent an important step in the gradual transition of radiation therapy towards a form of precision medicine.},
	issn = {2219-6803},	url = {}