Impact of range uncertainty on clinical distributions of linear energy transfer and biological effectiveness in proton therapy.
biological effectiveness
linear energy transfer (LET)
proton therapy
range uncertainty
Journal
Medical physics
ISSN: 2473-4209
Titre abrégé: Med Phys
Pays: United States
ID NLM: 0425746
Informations de publication
Date de publication:
Dec 2020
Dec 2020
Historique:
received:
24
07
2020
revised:
01
10
2020
accepted:
20
10
2020
pubmed:
30
10
2020
medline:
15
5
2021
entrez:
29
10
2020
Statut:
ppublish
Résumé
Increased radiation response after proton irradiation, such as late radiation-induced toxicity, is determined by high dose and elevated linear energy transfer (LET). Steep dose-averaged LET (LET For each of six cancer patients (two brain, head-and-neck, and prostate), two nominal treatment plans were robustly dose optimized using single- and multi-field optimization, respectively. For each plan, two additional scenarios with ±3.5% range deviation relative to the nominal plan were derived by global rescaling of stopping-power ratios. Dose and LET The optimization technique (single- vs multi-field) had a negligible impact on the LET Robust dose optimization generates LET
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
6151-6162Subventions
Organisme : European Social Fund
Informations de copyright
© 2020 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.
Références
International Commission on Radiation Units and Measurements Report 78: Prescribing, Recording and Reporting Proton-Beam Therapy. International Commission on Radiation Units and Measurements; 2007.
Paganetti H, Blakely E, Carabe-Fernandez A, et al. Report of the AAPM TG-256 on the relative biological effectiveness of proton beams in radiation therapy. Med Phys. 2019;46:e53-e78.
Wedenberg M, Lind BK, Hårdemark B. A model for the relative biological effectiveness of protons: the tissue specific parameter α/β of photons is a predictor for the sensitivity to LET changes. Acta Oncol. 2013;52:580-588.
McNamara AL, Schuemann J, Paganetti H. A phenomenological relative biological effectiveness (RBE) model for proton therapy based on all published in vitro cell survival data. Phys Med Biol. 2015;60:8399-8416.
Tilly N, Johansson J, Isacsson U, et al. The influence of RBE variations in a clinical proton treatment plan for a hypopharynx cancer. Phys Med Biol. 2005;50:2765-2777.
Frese MC, Wilkens JJ, Huber PE, Jensen AD, Oelfke U, Taheri-Kadkhoda Z. Application of constant vs. variable relative biological effectiveness in treatment planning of intensity-modulated proton therapy. Int J Radiat Oncol Biol Phys. 2011;79:80-88.
Carabe A, España S, Grassberger C, Paganetti H. Clinical consequences of relative biological effectiveness variations in proton radiotherapy of the prostate, brain and liver. Phys Med Biol. 2013;58:2103-2117.
Wedenberg M, Toma-Dasu I. Disregarding RBE variation in treatment plan comparison may lead to bias in favor of proton plans. Med Phys. 2014;41:091706.
Ödén J, Eriksson K, Toma-Dasu I. Inclusion of a variable RBE into proton and photon plan comparison for various fractionation schedules in prostate radiation therapy. Med Phys. 2017;44:810-822.
Dasu A, Toma-Dasu I. What is the clinically relevant relative biologic effectiveness? A warning for fractionated treatments with high linear energy transfer radiation. Int J Radiat Oncol Biol Phys. 2008;70:867-874.
Peeler CR, Mirkovic D, Titt U, et al. Clinical evidence of variable proton biological effectiveness in pediatric patients treated for ependymoma. Radiother Oncol. 2016;121:395-401.
Underwood TSA, Grassberger C, Bass R, et al. Asymptomatic late-phase radiographic changes among chest-wall patients are associated with a proton rbe exceeding 1.1. Int J Radiat Oncol Biol Phys. 2018;101:809-819.
Lühr A, von Neubeck C, Pawelke J, et al. “Radiobiology of proton therapy”: results of an international expert workshop. Radiother Oncol. 2018;128:56-67.
Eulitz J, Troost EGC, Raschke F, et al. Predicting late magnetic resonance image changes in glioma patients after proton therapy. Acta Oncol. 2019;58:1536-1539.
Bahn E, Bauer J, Harrabi S, Herfarth K, Debus J, Alber M. Late contrast enhancing brain lesions in proton treated low-grade glioma patients: clinical evidence for increased periventricular sensitivity and variable RBE. Int J Radiat Oncol. 2020;107:571-578.
Ödén J, Eriksson K, Toma-Dasu I. Incorporation of relative biological effectiveness uncertainties into proton plan robustness evaluation. Acta Oncol. 2017;56:769-778.
Ödén J, Toma-Dasu I, Eriksson K, Flejmer AM, Dasu A. The influence of breathing motion and a variable relative biological effectiveness in proton therapy of left-sided breast cancer. Acta Oncol. 2017;56:1428-1436.
Ödén J, Toma-Dasu I, Nyström PW, Traneus E, Dasu A. Spatial correlation of linear energy transfer and relative biological effectiveness with suspected treatment-related toxicities following proton therapy for intracranial tumors. Med Phys. 2019;47:342-351.
Albertini F, Hug EB, Lomax AJ. Is it necessary to plan with safety margins for actively scanned proton therapy? Phys Med Biol. 2011;56:4399-4413.
Bai X, Lim G, Wieser H-P, et al. Robust optimization to reduce the impact of biological effect variation from physical uncertainties in intensity-modulated proton therapy. Phys Med Biol. 2019;64:025004.
Taasti VT, Bäumer C, Dahlgren CV, et al. Inter-centre variability of CT-based stopping-power prediction in particle therapy: survey-based evaluation. Phys Imaging Radiat Oncol. 2018;6:25-30.
Wohlfahrt P, Möhler C, Stützer K, Greilich S, Richter C. Dual-energy CT based proton range prediction in head and pelvic tumor patients. Radiother Oncol. 2017;125:526-533.
Wohlfahrt P, Möhler C, Hietschold V, et al. Clinical implementation of dual-energy CT for proton treatment planning on pseudo-monoenergetic CT scans. Int J Radiat Oncol Biol Phys. 2017;97:427-434.
Wohlfahrt P, Möhler C, Richter C, Greilich S. Evaluation of stopping-power prediction by dual- and single-energy computed tomography in an anthropomorphic ground-truth phantom. Int J Radiat Oncol Biol Phys. 2018;100:244-253.
Wohlfahrt P, Möhler C, Enghardt W, et al. Refinement of the Hounsfield look-up table by retrospective application of patient-specific direct proton stopping-power prediction from dual-energy CT. Med Phys. 2020;47:1796-1806.
Fredriksson A, Forsgren A, Hårdemark B. Minimax optimization for handling range and setup uncertainties in proton therapy. Med Phys. 2011;38:1672-1684.
Bortfeld T. An analytical approximation of the Bragg curve for therapeutic proton beams. Med Phys. 1997;24:2024-2033.
Cortés-Giraldo MA, 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.
Traneus E, Ödén J. Introducing proton track-end objectives in intensity modulated proton therapy optimization to reduce linear energy transfer and relative biological effectiveness in critical structures. Int J Radiat Oncol Biol Phys. 2019;103:747-757.
Stuschke M, Thames HD. Fractionation sensitivities and dose-control relations of head and neck carcinomas: analysis of the randomized hyperfractionation trials. Radiother Oncol. 1999;51:113-121.
Qi XS, Schultz CJ, Li XA. An estimation of radiobiologic parameters from clinical outcomes for radiation treatment planning of brain tumor. Int J Radiat Oncol Biol Phys. 2006;64:1570-1580.
Dasu A, Toma-Dasu I. Prostate alpha/beta revisited an analysis of clinical results from 14 168 patients. Acta Oncol. 2012;51:963-974.
Grün R, Friedrich T, Krämer M, Zink K, Durante M, Engenhart-cabillic R. Physical and biological factors determining the effective proton range. Med Phys. 2013;40:1-10.
Giovannini G, Böhlen T, Cabal G, et al. Variable RBE in proton therapy: comparison of different model predictions and their influence on clinical-like scenarios. Radiat Oncol. 2016;11:1-16.
Unkelbach J, Paganetti H. Robust proton treatment planning: physical and biological optimization. Semin Radiat Oncol. 2018;28:88-96.
Fjaera LF, Li Z, Ytre-Hauge KS, et al. Linear energy transfer distributions in the brainstem depending on tumour location in intensity-modulated proton therapy of paediatric cancer. Acta Oncol. 2017;56:763-768.
Resch AF, Landry G, Kamp F, et al. Quantification of the uncertainties of a biological model and their impact on variable RBE proton treatment plan optimization. Phys Medica. 2017;36:91-102.
Paganetti H. Relative biological effectiveness (RBE) values for proton beam therapy. Variations as a function of biological endpoint, dose, and linear energy transfer. Phys Med Biol. 2014;59:R419-R472.
Marteinsdottir M, Schuemann J, Paganetti H. Impact of uncertainties in range and RBE on small field proton therapy. Phys Med Biol. 2019;64:205005.
Grassberger C, Paganetti H. Elevated LET components in clinical proton beams. Phys Med Biol. 2011;56:6677-6691.
Mairani A, Dokic I, Magro G, et al. A phenomenological relative biological effectiveness approach for proton therapy based on an improved description of the mixed radiation field. Phys Med Biol. 2017;62:1378-1395.
Grzanka L, Ardenfors O, Bassler N. Monte Carlo simulations of spatial LET distributions in clinical proton beams. Radiat Prot Dosimetry. 2018;180:296-299.
Giantsoudi D, Sethi RV, Yeap BY, et al. Incidence of CNS injury for a cohort of 111 patients treated with proton therapy for medulloblastoma: LET and RBE associations for areas of injury. Int J Radiat Oncol Biol Phys. 2016;95:287-296.
Paganetti H. Range uncertainties in proton therapy and the role of Monte Carlo simulations. Phys Med Biol. 2012;57:R99-R117.
Lowe M, Albertini F, Aitkenhead A, Lomax AJ, Mackay RI. Incorporating the effect of fractionation in the evaluation of proton plan robustness to setup errors. Phys Med Biol. 2015;61:413-429.
Sánchez-Parcerisa D, López-Aguirre M, Dolcet Llerena A, Udías JM. MultiRBE: treatment planning for protons with selective radiobiological effectiveness. Med Phys. 2019;46:4276-4284.