Dose Rate and Dose Painting

Abstract

Tumor heterogeneity is one of the most important factors in tumor progression and recurrence after therapy. In this situation, delivery of a non-uniform dose would be optimum. Dose painting as a nonuniform dose distribution is a feasible strategy in radiation oncology. It requires imaging biomarkers to determine treatment sites which should receive higher doses. There are two main strategies for dose painting: by numbers (DPBN) and by contours (DPBC). In DPBC, tumour sub volumes receive a boosted dose, whilst DPBN is a voxel based issue and each voxel of tumour volume receives an individual dose prescription [1]. Based on molecular imaging data, dose painting involves four distinct steps including: “determination of the correlation between the underlying tumour biology and molecular imaging; determination of dose prescription function based on molecular imaging data; planning of the treatment and dose delivery; and assessment of the clinical outcomes in comparison with standard treatments” [2]. Molecular imaging (more PET) plays a rigorous role to find more accurate target volume, called biological target volume (BTV). Bentzen et al. mentioned there are three evidence based causes of treatment failure in radiation oncology including tumor burden, tumor cell proliferation, and hypoxia. They concluded that molecular imaging of those phenotypes using specific PET tracer can lead to find ideal painted dose distribution [3]. In the other hand, by introduction of cancer stem cells (CSCs) hypothesis and their highly radiation resistance, the mentioned triplet treatment failure (tumor burden, proliferation, and hypoxia) can be correlated to CSCs. Also, the main heterogeneity of tumors is due to CSCs theoretically. Multiple studies have shown that CSCs are highly radioresistance because they are hypoxic, have strong DNA repair and radical scavenging systems and they repopulate by a fast manner [4].