Technical note: In silico benchmarking of the linear energy transfer-based functionalities for carbon ion beams in a commercial treatment planning system.
GATE/Geant4 Monte Carlo simulations
carbon ion radiotherapy
linear energy transfer
Journal
Medical physics
ISSN: 2473-4209
Titre abrégé: Med Phys
Pays: United States
ID NLM: 0425746
Informations de publication
Date de publication:
Mar 2023
Mar 2023
Historique:
revised:
04
12
2022
received:
02
08
2022
accepted:
04
12
2022
pubmed:
20
12
2022
medline:
22
3
2023
entrez:
19
12
2022
Statut:
ppublish
Résumé
The increasing number of studies dealing with linear energy transfer (LET)-based evaluation and optimization in the field of carbon ion radiotherapy (CIRT) indicates the rising demand for LET implementation in commercial treatment planning systems (TPS). Benchmarking studies could play a key role in detecting (and thus preventing) computation errors prior implementing such functionalities in a TPS. This in silico study was conducted to benchmark the following two LET-related functionalities in a commercial TPS against Monte Carlo simulations: (1) dose averaged LET (LET The LET For all setups (homogeneous and heterogeneous), the mean absolute (and relative) LET No computation error was found in the tested functionalities except for LET
Sections du résumé
BACKGROUND
BACKGROUND
The increasing number of studies dealing with linear energy transfer (LET)-based evaluation and optimization in the field of carbon ion radiotherapy (CIRT) indicates the rising demand for LET implementation in commercial treatment planning systems (TPS). Benchmarking studies could play a key role in detecting (and thus preventing) computation errors prior implementing such functionalities in a TPS.
PURPOSE
OBJECTIVE
This in silico study was conducted to benchmark the following two LET-related functionalities in a commercial TPS against Monte Carlo simulations: (1) dose averaged LET (LET
METHODS
METHODS
The LET
RESULTS
RESULTS
For all setups (homogeneous and heterogeneous), the mean absolute (and relative) LET
CONCLUSIONS
CONCLUSIONS
No computation error was found in the tested functionalities except for LET
Substances chimiques
Carbon
7440-44-0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1871-1878Informations de copyright
© 2022 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.
Références
Tinganelli W, Durante M. Carbon ion radiobiology. Cancers. 2020;12:3022. https://doi.org/10.3390/cancers12103022
Mein S, Klein C, Kopp B, et al. Assessment of RBE-weighted dose models for carbon ion therapy toward modernization of clinical practice at HIT: in vitro, in vivo, and in patients. Int J Radiat Oncol Biol Phys. 2020;108:779-791. https://doi.org/10.1016/j.ijrobp.2020.05.041
Scholz M, Kellerer AM, Kraft-Weyrather W, Kraft G. Computation of cell survival in heavy ion beams for therapy. Radiat Environ Biophys. 1997;36:59-66. https://doi.org/10.1007/s004110050055
Inaniwa T, Furukawa T, Kase Y, et al. Treatment planning for a scanned carbon beam with a modified microdosimetric kinetic model. Phys Med Biol. 2010;55:6721-6737. https://doi.org/10.1088/0031-9155/55/22/008
Fossati P, Matsufuji N, Kamada T, Karger CP. Radiobiological issues in prospective carbon ion therapy trials. Med Phys. 2018;45:e1096-e1110. https://doi.org/10.1002/mp.12506
Karger CP, Glowa C, Peschke P, Kraft-Weyrather W. The RBE in ion beam radiotherapy: in vivo studies and clinical application. Z Med Phys. 2021;31:105-121. https://doi.org/10.1016/j.zemedi.2020.12.001
ICRU. Report 85: Fundamental quantities and units for ionizing radiation. J ICRU. 2011;11:1-31.
Krämer M, Weyrather WK, Scholz M. The increased biological effectiveness of heavy charged particles: from radiobiology to treatment planning. Technol Cancer Res Treat. 2003;2:427-436. https://doi.org/10.1177/153303460300200507
Kalholm F, Grzanka L, Traneus E, Bassler N. A systematic review on the usage of averaged LET in radiation biology for particle therapy. Radiother Oncol. 2021;161:211-221. https://doi.org/10.1016/j.radonc.2021.04.007
Guan F, Peeler C, Bronk L, et al. Analysis of the track- and dose-averaged LET and LET spectra in proton therapy using the geant4 Monte Carlo code. Med Phys. 2015;42:6234-6247. https://doi.org/10.1118/1.4932217
Cortés-Giraldo M, Carabe A. A critical study of different Monte Carlo scoring methods of dose average linear-energy-transfer maps calculated in voxelized geometries irradiated with clinical proton beams. Phys Med Biol. 2015;60:2645-2669. https://doi.org/10.1088/0031-9155/60/7/2645
Bassler N, Jäkel O, Søndergaard CS, Petersen JB. Dose- and LET-painting with particle therapy. Acta Oncol. 2010;49:1170-1176. https://doi.org/10.3109/0284186X.2010.510640
Bassler N, Toftegaard J, Lühr A, et al. LET-painting increases tumour control probability in hypoxic tumours. Acta Oncol. 2013;53:25-32. https://doi.org/10.3109/0284186X.2013.832835
Malinen E, Søvik Å. Dose or ‘LET’ painting-what is optimal in particle therapy of hypoxic tumors? Acta Oncol. 2015;54:1614-1622. https://doi.org/10.3109/0284186X.2015.1062540
Tinganelli W, Durante M, Hirayama R, et al. Kill-painting of hypoxic tumours in charged particle therapy. Sci Rep. 2015;5. https://doi.org/10.1038/srep17016
Hagiwara Y, Bhattacharyya T, Matsufuji N, et al. Influence of dose-averaged linear energy transfer on tumour control after carbon-ion radiation therapy for pancreatic cancer. Clin Transl Radiat Oncol. 2020;21:19-24. https://doi.org/10.1016/j.ctro.2019.11.002
Matsumoto S, Lee SH, Imai R, et al. Unresectable chondrosarcomas treated with carbon ion radiotherapy: relationship between dose-averaged linear energy transfer and local recurrence. Anticancer Res. 2020;40:6429-6435. https://doi.org/10.21873/anticanres.14664
Molinelli S, Magro G, Mairani A, et al. How LEM-based RBE and dose-averaged LET affected clinical outcomes of sacral chordoma patients treated with carbon ion radiotherapy. Radiother Oncol. 2021;163:209-214. https://doi.org/10.1016/j.radonc.2021.08.024
Petringa G, Pandola L, Agosteo S, et al. Monte Carlo implementation of new algorithms for the evaluation of averaged-dose and -track linear energy transfers in 62 MeV clinical proton beams. Phys Med Biol. 2020;65:235043. https://doi.org/10.1088/1361-6560/abaeb9
Ruangchan S, Palmans H, Knäusl B, Georg D, Clausen M. Dose calculation accuracy in particle therapy: comparing carbon ions with protons. Med Phys. 2021;48:7333-7345. https://doi.org/10.1002/mp.15209
Ferrari A, Sala PR, Fasso A, Ranft J. FLUKA: A Multi-particle Transport Code. CERN Yellow Rep. INFN TC 05/11, SLAC-R-773. 2005. Accessed December 23, 2021. https://cds.cern.ch/record/898301/files/CERN-2005-010.pdf
Böhlen T, Cerutti F, Chin M, et al. The FLUKA code: developments and challenges for high energy and medical applications. Nucl Data Sheets. 2014;120:211-214. https://doi.org/10.1016/j.nds.2014.07.049
Battistoni G, Bauer J, Boehlen TT, et al. The FLUKA code: an accurate simulation tool for particle therapy. Front Oncol. 2016;6. https://doi.org/10.3389/fonc.2016.00116
Resch AF, Schafasand M, Lackner N, et al. Impact of beamline-specific particle energy spectra on clinical plans in carbon ion beam therapy. Med Phys. 2022;49:4092-4098. https://doi.org/10.1002/mp.15652
Böhlen T, Cerutti F, Dosanjh M, et al. Benchmarking nuclear models of FLUKA and GEANT4 for carbon ion therapy. Phys Med Biol. 2010;55:5833-5847. https://doi.org/10.1088/0031-9155/55/19/014
Grevillot L, Boersma DJ, Fuchs H, et al. The GATE-RTion/IDEAL independent dose calculation system for light ion beam therapy. Front Phys. 2021;9. https://doi.org/10.3389/fphy.2021.704760
Fuchs H, Elia A, Resch AF, et al. Computer-assisted beam modeling for particle therapy. Med Phys. 2020;48:841-851. https://doi.org/10.1002/mp.14647
Grevillot L, Boersma DJ, Fuchs H, et al. Technical note: GATE-RTion: a GATE/Geant4 release for clinical applications in scanned ion beam therapy. Med Phys. 2020;47:3675-3681. https://doi.org/10.1002/mp.14242
Arce P, Bolst D, Bordage M-C, et al. Report on G4-Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group. Med Phys. 2020;48:19-56. https://doi.org/10.1002/mp.14226
Allison J, Amako K, Apostolakis J, et al. Recent developments in Geant4. Nucl Instrum Methods Phys Res Sect A. 2016;835:186-225. https://doi.org/10.1016/j.nima.2016.06.125
Inaniwa T, Kanematsu N. A trichrome beam model for biological dose calculation in scanned carbon-ion radiotherapy treatment planning. Phys Med Biol. 2015;60:437-451. https://doi.org/10.1088/0031-9155/60/1/437
Wagenaar D, Tran LT, Meijers A, et al. Validation of linear energy transfer computed in a Monte Carlo dose engine of a commercial treatment planning system. Phys Med Biol. 2020;65:25006. https://doi.org/10.1088/1361-6560/ab5e97
Choi K, Mein S, Kopp B, et al. FRoG-a new calculation engine for clinical investigations with proton and carbon ion beams at CNAO. Cancers. 2018;10:395. https://doi.org/10.1016/j.ijrobp.2019.10.008
Dudouet J, Cussol D, Durand D, Labalme M. Benchmarking geant4 nuclear models for hadron therapy with 95 MeV/nucleon carbon ions. Phys Rev C. 2014;89:54616. https://journals.aps.org/prc/abstract/10.1103/PhysRevC.89.054616