Speaker
Description
-INTRODUCTION-
Protontherapy has firmly established itself as a complement to conventional radiotherapy for certain tumor and patient profiles. Its primary benefit lies in its remarkable precision, which enables the preservation of a greater amount of the healthy tissue surrounding the tumor. Moreover, protons cause a larger biological effect than photons. Apart from the particles' deposited energy, the linear energy transfer (LET) is thought to play a major role in determining such effect [1-2].
In previous studies, we used the definitions appearing in [3] to calculate track-averaged LET (LETt) and dose-averaged LET (LETd) on-axis distributions for proton pincel beams. These definitions provide a clear and simple way to calculate LETt and LETd on surfaces. However, this is limited when investigating more complex spatial behaviours.
In this communication, we have calculated LETt and LETd in water using the definitions in [4-5] with the Monte Carlo code PENELOPE [6] and PENH (its extension including protons and neutrons). These definitions are volumetric, which facilitates obtaining results using 3D voxelization.
-MATERIALS & METHODS-
We conduct a comparative analysis of the results obtained through both methods and explain their differences. We also evaluate our new implementation against the Monte Carlo codes FLUKA [7] and TOPAS [8]. Additionally, a comparison with the LETt and LETd analytical models described in [3] has been carried out.
We first use monoenergetic proton pencil beams to calibrate the new implementation. A broader variety of beam types has been used to replicate other Monte Carlo studies present in the literature.
-RESULTS AND CONCLUSIONS-
LETt and LETd on-axis distributions are presented for all three codes. The values obtained for LETt are more stable, offering a higher uniformity between codes and definitions than those of LETd. Both are compatible in the majority of the phantom. The appearing discrepancies are addressed.
-REFERENCES-
[1] Paganetti, "Relative biological effectiveness (RBE) values for proton beam therapy. Variations as a function of biological endpoint, dose, and linear energy transfer". Phys Med Biol. 2014 Nov 21;59(22):R419-72.
[2] Kalholm, F., Grzanka, L., Traneus, E., & Bassler, N. "A systematic review on the usage of averaged LET in radiation biology for particle therapy". In Radiotherapy and Oncology (Vol. 161, pp. 211–221). Elsevier BV, (2021).
[3] Wilkens and Oelfke, "Analytical linear energy transfer calculations for proton therapy". Med Phys. 2003 May;30(5):806-15.
[4] D. A. Granville and G. O. Sawakuchi, "Comparison of linear energy transfer scoring techniques in Monte Carlo simulations of proton beams" 2015 Phys. Med. Biol. 60 N283.
[5] M. A. Cortés-Giraldo and A. Carabe, "A critical study of different Monte Carlo scoring methods of dose average linear-energy-transfer maps calculated in voxelized geometries irradiated with clinical proton beams" 2015 Phys. Med. Biol. 60 2645
[6] F. Salvat, J.M. Fernández-Varea and J. Sempau, "Penelope 2018: a code system for Monte Carlo simulation of electron and photon transport", Nuclear Energy Agency, Barcelona 2018; F. Salvat and J. M. Quesada, Nucl. Ins. Meth. Phys. Res. B 475 (2020) 49.
[7] G. Batistone, "The FLUKA code", Annals of Nuclear Energy 82 (2015) 10.
[8] J. Perl et al, "TOPAS: an innovative proton Monte Carlo platform for research and clinical applications", Med. Phys. 39 (2012) 6818.
(+) Corresponding Author: danipuerta@ugr.es
