# Commissioning of a Monte Carlo‐based scanning proton beam for breast cancer: Incorporating LETd calculations and variable RBE models

## TL;DR

This study develops a proton therapy model that improves dose calculations for breast cancer by using variable RBE models and LETd calculations.

## Contribution

The paper introduces a Monte Carlo model integrating variable RBE and LETd calculations for more accurate proton therapy dose estimation in breast cancer.

## Key findings

- The FLUKA-MC model showed good agreement with clinical TPS and measurements, with proton range deviations within ±0.1 mm.
- Variable RBE models predicted higher RBE-weighted doses in fracture and pneumonitis cases compared to non-fracture cases.
- All variable RBE models showed elevated RBE-weighted doses in distal proton beam regions across patient cases.

## Abstract

Using a constant relative biological effectiveness (RBE = 1.1) in proton therapy may underestimate the RBE‐weighted dose in high linear energy transfer (LET) regions at the distal end of the beam, thereby limiting the ability to accurately predict clinical outcomes.

To commission and validate a Monte Carlo (MC) model incorporating variable RBE for breast cancer proton therapy, enabling improved RBE‐weighted dose calculation.

A FLUKA‐based MC model of a raster scanning proton beamline was commissioned and benchmarked against the clinically employed treatment planning system (TPS) (Siemens Syngo) and physical measurements. Dose‐averaged LET (LETd) and variable RBE‐weighted dose distributions were computed using McMahon (McM), McNamara (McN), and Wedenberg (Wed) models. Treatment plans for four representative breast cancer cases were recalculated to compare TPS and MC results using dose‐volume histograms (DVH) and three‐dimensional gamma (γ) analysis. LETd‐volume histograms (LVH) and variable RBE‐weighted dose distributions were analyzed to compare cases without adverse effects versus those presenting rib fractures or radiation pneumonitis.

The FLUKA‐MC model showed good agreement with both the TPS results and the measured data, exhibiting proton range deviations within ±0.1 mm. The γ pass rates for the four patients are 94.0%, 92.2%, 92.6%, and 86.7%, respectively. LETd analysis of 0.5 cm3 volumes of rib revealed numerical differences (fracture cases: 11.1 and 10.8 keV/µm; non‐fracture: 9.2 and 10.0 keV/µm). The RBE‐weighted dose to 0.5 cm3 of the ribs was consistently elevated in fracture cases across all models (RBE = 1.1: 46.2–49.0 Gy; McM: 54.6–56.5 Gy; McN: 51.0–53.3 Gy; Wed: 50.6–52.5 Gy) versus non‐fracture cases (RBE = 1.1: 44.0–45.3 Gy; McM: 52.2–53.8 Gy; McN: 48.6–50.1 Gy; Wed: 48.3–49.8 Gy). The estimated RBE values in the rib region were 1.60 (McM), 1.38 (McN), and 1.44 (Wed), which were derived from the mean LETd within 0.5 cm3 rib volumes. The RBE‐weighted lung V20 was elevated in pneumonitis patients across all models. All variable RBE models predicted elevated RBE‐weighted doses in distal proton beam regions across cases.

The commissioned MC framework demonstrated the feasibility of integrating multiple variable RBE models for RBE‐weighted dose estimation in proton therapy.