In radiotherapy, hypoxia is a known negative factor, occurring especially in solid malignant tumours. Nitroimidazole-based positron emission tomography (PET) tracers, due to their selective binding to hypoxic cells, could be used as surrogates to image and quantify the underlying oxygen distributions in tissues. The spatial resolution of a clinical PET image, however, is much larger than the cellular spatial scale where hypoxia occurs. A question therefore arises regarding the possibility of quantifying different hypoxia levels based on PET images, and the aim of the present study is the prescription of corresponding therapeutic doses and its exploration.A tumour oxygenation model was created consisting of two concentric spheres with different oxygen partial pressure (pO2) distributions. In order to mimic a PET image of the simulated tumour, given the relation between uptake and pO2, fundamental effects that limit spatial resolution in a PET imaging system were considered: the uptake distribution was processed with a Gaussian 3D filter, and a re-binning to reach a typical PET image voxel size was performed. Prescription doses to overcome tumour hypoxia and predicted tumour control probability (TCP) were calculated based on the processed images for several fractionation schemes. Knowing the underlying oxygenation at microscopic scale, the actual TCP expected after the delivery of the calculated prescription doses was evaluated. Results are presented for three different dose painting strategies: by numbers, by contours and by using a voxel grouping-based approach.The differences between predicted TCP and evaluated TCP indicate that careful consideration must be taken on the dose prescription strategy and the selection of the number of fractions, depending on the severity of hypoxia.
Keywords: Dose painting; Hypoxia; Mathematical modelling; PET; TCP.