Proton (p) and carbon (C) ion beams are in clinical use for cancer treatment, although other particles such as He, Be, and B ions have more recently gained attention. Identification of the most optimal ion beam for radiotherapy is a challenging task involving, among others, radiobiological characterization of a beam, which is depth-, energy-, and cell type- dependent. This study uses the FLUKA and MCDS Monte Carlo codes in order to estimate the relative biological effectiveness (RBE) for several ions of potential clinical interest such as p, He, Li, Be, B, and C forming a spread-out Bragg peak (SOBP). More specifically, an energy spectrum of the projectiles corresponding to a 5-cm SOBP at a depth of 8 cm was used. All secondary particles produced by the projectiles were considered and RBE was determined based on radiation-induced Double Strand Breaks (DSBs), as calculated by MCDS. In an attempt to identify the most optimal ion beam, using the latter data, biological optimization was performed and the obtained depth-dose distributions were inter-compared. The results showed that C ions are more effective inside the SOBP region, which comes at the expense of higher dose values at the tail (i.e., after the SOBP). In contrast, p beams exhibit a higher DSOPB/DEntrance ratio, if physical doses are considered. By performing a biological optimization in order to obtain a homogeneous biological dose (i.e., dose × RBE) in the SOBP, the corresponding advantages of p and C ions are moderated. Li ions conveniently combine a considerably lower dose tail and a DSOPB/DEntrance ratio similar to C. This work contributes towards identification of the most optimal ion beam for cancer therapy. The overall results of this work suggest that Li ions are of potential interest, although more studies are needed to demonstrate the relevant advantages. Future work will focus on studying more complex beam configurations.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9864401 | PMC |
http://dx.doi.org/10.3390/jpm13010023 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!