Radiotherapy is one of the most widely used types of cancer treatment, and typically half of all cancer patients receive radiotherapy as a part of their treatment. Proton therapy has been established as a new alternative to traditional X-ray therapy with potential to improve the treatment significantly and two proton therapy facilities are currently under construction in Norway. The main benefit of protons is their ability to concentrate the dose in the tumor, limiting the dose received by healthy tissue. This is of high importance as the risk of side effects from the treatment is closely related to the dose received by healthy tissues.
Proton therapy has an increased biological effect compared to X-ray therapy, meaning that protons produce more damage to the tumor than photons for the same dose. This difference is referred to as the relative biological effectiveness (RBE) and is accounted for clinically by applying a constant dose-scaling factor of 1.1. Thus, the current clinical practice assumes protons to be 10% more efficient than X-rays. However, it is known that this effect varies between different cancer patient groups and also depends on additional factors. This simple scaling factor is therefore limiting the quality of the proton therapy treatment. In this project we aim to develop a better model for the biological effect of protons and apply this to improve proton therapy by introducing biological treatment optimization, taking into account the variations in biological effectiveness of protons for different tumors and patient groups. Through this, the project aims to reduce the risk of side effects from the treatment and overall improve proton therapy treatments given at Norwegian proton therapy facilities and abroad.
Proton therapy has been established internationally as an important radiotherapy modality and two facilities are planned to open in Norway within four years. The main benefit of protons is the superior dose distribution compared to conventional radiotherapy: A high radiation dose can be delivered to the tumor while minimal dose is deposited distal to the tumor volume since the proton beam stops in the tumor. However, proton therapy has an increased biological effect compared to photon therapy, i.e. protons produce more damage than photons for the same physical dose. A simplistic dose scaling factor, RBE (relative biological effectiveness), of 1.1 is today used clinically, although in vitro, in vivo and recent clinical data show that the RBE effect can be significantly higher and therefore lead to unforeseen toxicity.
Our objective is to reduce the risk of toxicity in cancer patients through development, validation and application of a novel biological optimization system for proton therapy, including the different RBE dependencies in the treatment planning process.
Clinical use of biological optimization is hindered by uncertainties regarding translation of preclinical results to the clinic, but recent in vivo and clinical data on the proton RBE opens the way to bring RBE modelling forward. We therefore aim to reach our objectives through: i) Using recent clinical and in vivo data to improve and validate in vitro based RBE models for proton therapy. Since recent data demonstrate particularly strong clinical evidence for enhanced RBE in normal brain tissue, we will also focus especially on validating RBE models for application in the treatment of brain tumors. ii) Develop a complete Monte Carlo based computational system for biological optimization, and iii) Apply biological optimization in silico to quantify the potential reduction in risk of toxicity, and identify patient groups eligible for clinical trials with biological optimization.