Literature DB >> 23514837

A Monte Carlo-based treatment planning tool for proton therapy.

A Mairani1, T T Böhlen, A Schiavi, T Tessonnier, S Molinelli, S Brons, G Battistoni, K Parodi, V Patera.   

Abstract

In the field of radiotherapy, Monte Carlo (MC) particle transport calculations are recognized for their superior accuracy in predicting dose and fluence distributions in patient geometries compared to analytical algorithms which are generally used for treatment planning due to their shorter execution times. In this work, a newly developed MC-based treatment planning (MCTP) tool for proton therapy is proposed to support treatment planning studies and research applications. It allows for single-field and simultaneous multiple-field optimization in realistic treatment scenarios and is based on the MC code FLUKA. Relative biological effectiveness (RBE)-weighted dose is optimized either with the common approach using a constant RBE of 1.1 or using a variable RBE according to radiobiological input tables. A validated reimplementation of the local effect model was used in this work to generate radiobiological input tables. Examples of treatment plans in water phantoms and in patient-CT geometries together with an experimental dosimetric validation of the plans are presented for clinical treatment parameters as used at the Italian National Center for Oncological Hadron Therapy. To conclude, a versatile MCTP tool for proton therapy was developed and validated for realistic patient treatment scenarios against dosimetric measurements and commercial analytical TP calculations. It is aimed to be used in future for research and to support treatment planning at state-of-the-art ion beam therapy facilities.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 23514837     DOI: 10.1088/0031-9155/58/8/2471

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


  18 in total

1.  A new approach to integrate GPU-based Monte Carlo simulation into inverse treatment plan optimization for proton therapy.

Authors:  Yongbao Li; Zhen Tian; Ting Song; Zhaoxia Wu; Yaqiang Liu; Steve Jiang; Xun Jia
Journal:  Phys Med Biol       Date:  2016-12-17       Impact factor: 3.609

Review 2.  The physics of proton therapy.

Authors:  Wayne D Newhauser; Rui Zhang
Journal:  Phys Med Biol       Date:  2015-03-24       Impact factor: 3.609

3.  Full Monte Carlo-Based Biologic Treatment Plan Optimization System for Intensity Modulated Carbon Ion Therapy on Graphics Processing Unit.

Authors:  Nan Qin; Chenyang Shen; Min-Yu Tsai; Marco Pinto; Zhen Tian; Georgios Dedes; Arnold Pompos; Steve B Jiang; Katia Parodi; Xun Jia
Journal:  Int J Radiat Oncol Biol Phys       Date:  2017-09-12       Impact factor: 7.038

4.  A Monte Carlo-based treatment-planning tool for ion beam therapy.

Authors:  T T Böhlen; J Bauer; M Dosanjh; A Ferrari; T Haberer; K Parodi; V Patera; A Mairani
Journal:  J Radiat Res       Date:  2013-07       Impact factor: 2.724

5.  A simplified Monte Carlo algorithm considering large-angle scattering for fast and accurate calculation of proton dose.

Authors:  Taisuke Takayanagi; Shusuke Hirayama; Shinichiro Fujitaka; Rintaro Fujimoto
Journal:  J Appl Clin Med Phys       Date:  2017-11-27       Impact factor: 2.102

6.  Proton and helium ion radiotherapy for meningioma tumors: a Monte Carlo-based treatment planning comparison.

Authors:  Thomas Tessonnier; Andrea Mairani; Wenjing Chen; Paola Sala; Francesco Cerutti; Alfredo Ferrari; Thomas Haberer; Jürgen Debus; Katia Parodi
Journal:  Radiat Oncol       Date:  2018-01-09       Impact factor: 3.481

7.  A benchmarking method to evaluate the accuracy of a commercial proton monte carlo pencil beam scanning treatment planning system.

Authors:  Liyong Lin; Sheng Huang; Minglei Kang; Petri Hiltunen; Reynald Vanderstraeten; Jari Lindberg; Sami Siljamaki; Todd Wareing; Ian Davis; Allen Barnett; John McGhee; Charles B Simone; Timothy D Solberg; James E McDonough; Christopher Ainsley
Journal:  J Appl Clin Med Phys       Date:  2017-02-02       Impact factor: 2.102

8.  Variable RBE in proton therapy: comparison of different model predictions and their influence on clinical-like scenarios.

Authors:  Giulia Giovannini; Till Böhlen; Gonzalo Cabal; Julia Bauer; Thomas Tessonnier; Kathrin Frey; Jürgen Debus; Andrea Mairani; Katia Parodi
Journal:  Radiat Oncol       Date:  2016-05-17       Impact factor: 3.481

9.  Monte Carlo Calculations Supporting Patient Plan Verification in Proton Therapy.

Authors:  Thiago V M Lima; Manjit Dosanjh; Alfredo Ferrari; Silvia Molineli; Mario Ciocca; Andrea Mairani
Journal:  Front Oncol       Date:  2016-03-18       Impact factor: 6.244

10.  Phase Space Generation for Proton and Carbon Ion Beams for External Users' Applications at the Heidelberg Ion Therapy Center.

Authors:  Thomas Tessonnier; Tiago Marcelos; Andrea Mairani; Stephan Brons; Katia Parodi
Journal:  Front Oncol       Date:  2016-01-11       Impact factor: 6.244

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.