Clinical Applications of Relative Biological Effectiveness in Carbon Ion Radiation Therapy: Current Status and...

The exploitation of the high relative biological effectiveness (RBE) of carbon ions is one of the major rationales for their use as a radiation therapy modality. As the RBE depends on many physical and biological factors, biophysical models are used to compute it for the complex radiation fields used in clinical settings. However, the models currently applied in clinics or used to interpret clinical results make different RBE predictions. This creates difficulties for direct comparability of RBE-weighted doses delivered and reported within different approaches. Additional conventions on how these models are applied also differ and further complicate the comparison. Consequently, it is crucial to understand the impact of RBE modeling on the delivered absorbed doses and the reported RBE-weighted doses. Translation concepts between dose prescription systems, that is, the models and the context in which they are used, are needed to exchange treatment protocols between centers with different planning methods and to establish joint clinical studies or meta-studies. Although many of these problems are solved for specific cases, a broad perspective is lacking on how to transparently proceed with multiple RBE models and corresponding concepts of RBE-weighted dose. The present publication is a product of an initiative within the subcommittee on Guidelines in Carbon Ion Radiation Therapy of the Particle Therapy Co-operative group (PTCOG). It aims to (1) raise awareness of the problem; (2) demonstrate the impact of different models used for RBE predictions; (3) provide information on how RBE is currently accounted for; and (4) give an overview of approaches toward the translation of doses. Along this route, we provide several expert consensus statements agreed on by all authors, which provide insights into the complexity of understanding and comparing different dose prescription systems. Despite this complexity, transforming treatment plans between any 2 systems is feasible, opening up novel planning strategies that consider multiple models and paving the way for multi-institutional clinical studies .