A comprehensive dosimetric study of Monte Carlo and pencil-beam algorithms on intensity-modulated proton therapy for breast cancer

Abstract

PB algorithms are commonly used for proton therapy. Previously reported limitations of the PB algorithm for proton therapy are mainly focused on high-density gradients and small-field dosimetry, the effect of PB algorithms on intensity-modulated proton therapy (IMPT) for breast cancer has yet to be illuminated. In this study, we examined 20 patients with breast cancer and systematically investigated the dosimetric impact of MC and PB algorithms on IMPT. Four plans were generated for each patient: (a) a PB plan that optimized and computed the final dose using a PB algorithm; (b) a MC-recomputed plan that recomputed the final dose of the PB plan using a MC algorithm; (c) a MC-renormalized plan that renormalized the MC-recomputed plan to restore the target coverage; and (d) a MC-optimized plan that optimized and computed the final dose using a MC algorithm. The DVH on CTVs and on organ-at-risks (OARs) from each plan were studied. The Mann–Whitney U-test was used for testing the differences between any two types of plans. We found that PB algorithms significantly overestimated the target dose in breast IMPT plans. The median value of the CTV D99%, D95%, and Dmean dropped by 3.7%, 3.4%, and 2.1%, respectively, of the prescription dose in the MC-recomputed plans compared with the PB plans. The magnitude of the target dose overestimation by the PB algorithm was higher for the breast CTV than for the chest wall CTV. In the MC-renormalized plans, the target dose coverage was comparable with the original PB plans, but renormalization led to a significant increase in target hot spots as well as skin dose. The MC-optimized plans led to sufficient target dose coverage, acceptable target hot spots, and good sparing of skin and other OARs. Utilizing the MC algorithm for both plan optimization and final dose computation in breast IMPT treatment planning is therefore desirable.