Literature DB >> 26840945

Analytical calculation of proton linear energy transfer in voxelized geometries including secondary protons.

D Sanchez-Parcerisa1, M A Cortés-Giraldo, D Dolney, M Kondrla, M Fager, A Carabe.   

Abstract

In order to integrate radiobiological modelling with clinical treatment planning for proton radiotherapy, we extended our in-house treatment planning system FoCa with a 3D analytical algorithm to calculate linear energy transfer (LET) in voxelized patient geometries. Both active scanning and passive scattering delivery modalities are supported. The analytical calculation is much faster than the Monte-Carlo (MC) method and it can be implemented in the inverse treatment planning optimization suite, allowing us to create LET-based objectives in inverse planning. The LET was calculated by combining a 1D analytical approach including a novel correction for secondary protons with pencil-beam type LET-kernels. Then, these LET kernels were inserted into the proton-convolution-superposition algorithm in FoCa. The analytical LET distributions were benchmarked against MC simulations carried out in Geant4. A cohort of simple phantom and patient plans representing a wide variety of sites (prostate, lung, brain, head and neck) was selected. The calculation algorithm was able to reproduce the MC LET to within 6% (1 standard deviation) for low-LET areas (under 1.7 keV μm(-1)) and within 22% for the high-LET areas above that threshold. The dose and LET distributions can be further extended, using radiobiological models, to include radiobiological effectiveness (RBE) calculations in the treatment planning system. This implementation also allows for radiobiological optimization of treatments by including RBE-weighted dose constraints in the inverse treatment planning process.

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Year:  2016        PMID: 26840945     DOI: 10.1088/0031-9155/61/4/1705

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  7 in total

1.  Robust intensity-modulated proton therapy to reduce high linear energy transfer in organs at risk.

Authors:  Yu An; Jie Shan; Samir H Patel; William Wong; Steven E Schild; Xiaoning Ding; Martin Bues; Wei Liu
Journal:  Med Phys       Date:  2017-10-26       Impact factor: 4.071

2.  Increased risk of pseudoprogression among pediatric low-grade glioma patients treated with proton versus photon radiotherapy.

Authors:  Ethan B Ludmir; Anita Mahajan; Arnold C Paulino; Jeremy Y Jones; Leena M Ketonen; Jack M Su; David R Grosshans; Mary Frances McAleer; Susan L McGovern; Yasmin A Lassen-Ramshad; Adekunle M Adesina; Robert C Dauser; Jeffrey S Weinberg; Murali M Chintagumpala
Journal:  Neuro Oncol       Date:  2019-05-06       Impact factor: 12.300

3.  Linear energy transfer weighted beam orientation optimization for intensity-modulated proton therapy.

Authors:  Wenbo Gu; Dan Ruan; Wei Zou; Lei Dong; Ke Sheng
Journal:  Med Phys       Date:  2020-07-13       Impact factor: 4.071

4.  Dual-storage phosphor proton therapy dosimetry: Simultaneous quantification of dose and linear energy transfer.

Authors:  Jufri Setianegara; Thomas R Mazur; Deshan Yang; H Harold Li
Journal:  Med Phys       Date:  2021-02-19       Impact factor: 4.071

5.  The impact of proton LET/RBE modeling and robustness analysis on base-of-skull and pediatric craniopharyngioma proton plans relative to VMAT.

Authors:  A Gutierrez; V Rompokos; K Li; C Gillies; D D'Souza; F Solda; N Fersht; Y-C Chang; G Royle; R A Amos; T Underwood
Journal:  Acta Oncol       Date:  2019-08-20       Impact factor: 4.089

6.  An approximate analytical solution of the Bethe equation for charged particles in the radiotherapeutic energy range.

Authors:  David Robert Grimes; Daniel R Warren; Mike Partridge
Journal:  Sci Rep       Date:  2017-08-29       Impact factor: 4.379

7.  Teaching treatment planning for protons with educational open-source software: experience with FoCa and matRad.

Authors:  Daniel Sanchez-Parcerisa; Jose Udías
Journal:  J Appl Clin Med Phys       Date:  2018-05-12       Impact factor: 2.102

  7 in total

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