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Advanced proton beam dosimetry part II: Monte Carlo vs. pencil beam-based planning for lung cancer.
Maes, Dominic; Saini, Jatinder; Zeng, Jing; Rengan, Ramesh; Wong, Tony; Bowen, Stephen R.
Afiliação
  • Maes D; Seattle Cancer Care Alliance Proton Therapy Center, Seattle, WA, USA.
  • Saini J; Seattle Cancer Care Alliance Proton Therapy Center, Seattle, WA, USA.
  • Zeng J; Department of Radiation Oncology, University of Washington School of Medicine, Seattle, WA, USA.
  • Rengan R; Department of Radiation Oncology, University of Washington School of Medicine, Seattle, WA, USA.
  • Wong T; Seattle Cancer Care Alliance Proton Therapy Center, Seattle, WA, USA.
  • Bowen SR; Department of Radiation Oncology, University of Washington School of Medicine, Seattle, WA, USA.
Transl Lung Cancer Res ; 7(2): 114-121, 2018 Apr.
Article em En | MEDLINE | ID: mdl-29876310
BACKGROUND: Proton pencil beam (PB) dose calculation algorithms have limited accuracy within heterogeneous tissues of lung cancer patients, which may be addressed by modern commercial Monte Carlo (MC) algorithms. We investigated clinical pencil beam scanning (PBS) dose differences between PB and MC-based treatment planning for lung cancer patients. METHODS: With IRB approval, a comparative dosimetric analysis between RayStation MC and PB dose engines was performed on ten patient plans. PBS gantry plans were generated using single-field optimization technique to maintain target coverage under range and setup uncertainties. Dose differences between PB-optimized (PBopt), MC-recalculated (MCrecalc), and MC-optimized (MCopt) plans were recorded for the following region-of-interest metrics: clinical target volume (CTV) V95, CTV homogeneity index (HI), total lung V20, total lung VRX (relative lung volume receiving prescribed dose or higher), and global maximum dose. The impact of PB-based and MC-based planning on robustness to systematic perturbation of range (±3% density) and setup (±3 mm isotropic) was assessed. Pairwise differences in dose parameters were evaluated through non-parametric Friedman and Wilcoxon sign-rank testing. RESULTS: In this ten-patient sample, CTV V95 decreased significantly from 99-100% for PBopt to 77-94% for MCrecalc and recovered to 99-100% for MCopt (P<10-5). The median CTV HI (D95/D5) decreased from 0.98 for PBopt to 0.91 for MCrecalc and increased to 0.95 for MCopt (P<10-3). CTV D95 robustness to range and setup errors improved under MCopt (ΔD95 =-1%) compared to MCrecalc (ΔD95 =-6%, P=0.006). No changes in lung dosimetry were observed for large volumes receiving low to intermediate doses (e.g., V20), while differences between PB-based and MC-based planning were noted for small volumes receiving high doses (e.g., VRX). Global maximum patient dose increased from 106% for PBopt to 109% for MCrecalc and 112% for MCopt (P<10-3). CONCLUSIONS: MC dosimetry revealed a reduction in target dose coverage under PB-based planning that was regained under MC-based planning along with improved plan robustness. MC-based optimization and dose calculation should be integrated into clinical planning workflows of lung cancer patients receiving actively scanned proton therapy.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Transl Lung Cancer Res Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Transl Lung Cancer Res Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: China