Simulation of consequences of using nonideal detectors during beam data commissioning measurements.
beam data commissioning
detectors
dosimetry
Journal
Medical physics
ISSN: 2473-4209
Titre abrégé: Med Phys
Pays: United States
ID NLM: 0425746
Informations de publication
Date de publication:
Dec 2023
Dec 2023
Historique:
revised:
03
07
2023
received:
22
12
2021
accepted:
19
07
2023
medline:
6
12
2023
pubmed:
30
8
2023
entrez:
30
8
2023
Statut:
ppublish
Résumé
Beam data commissioning is a core task of radiotherapy physicists. Despite multiple detectors available, a feasible measurement program compromises between detector properties and time constraints. Therefore, it is important to understand how nonideal measurement data propagates into patient dose calculation. We simulated the effects of realistic errors, due to beam commissioning with presumably nonoptimal detectors, on the resulting patient dose distributions. Additionally, the detectability of such beam commissioning errors during patient plan quality assurance (QA) was evaluated. A clinically used beam model was re-commissioned introducing changes to depth dose curves, output factors, profiles or combinations of those. Seventeen altered beam models with incremental changes of the modelling parameters were created to analyze dose changes on simplified anatomical phantoms. Additionally, fourteen altered models incorporate changes in the order of signal differences reported for typically used detectors. Eighteen treatment plans of different types were recalculated on patient CT data sets using the altered beam models. For the majority of clinical plans, dose distributions in the target volume recalculated on the patient computed tomography data were similar between the original and the modified beam models, yielding global 2%/2 mm gamma pass rates above 98.9%. Larger changes were observed for certain combinations of beam modelling errors and anatomical sites, most extreme for output factor changes in a small target volume plan with a pass rate of 80.6%. Modelling an enlarged penumbra as if measured with a 0.125 cm While the simulated errors during beam modelling had little effect on most plans, in some cases changes were considerable. High-quality penumbra and small field output factor should be a main focus of commissioning measurements. Detecting modelling issues using standard patient QA phantoms is unlikely. Verification of a beam model should be performed especially for plans with high modulation and in different depths or geometries representing the variety of situations expected clinically.
Sections du résumé
BACKGROUND
BACKGROUND
Beam data commissioning is a core task of radiotherapy physicists. Despite multiple detectors available, a feasible measurement program compromises between detector properties and time constraints. Therefore, it is important to understand how nonideal measurement data propagates into patient dose calculation.
PURPOSE
OBJECTIVE
We simulated the effects of realistic errors, due to beam commissioning with presumably nonoptimal detectors, on the resulting patient dose distributions. Additionally, the detectability of such beam commissioning errors during patient plan quality assurance (QA) was evaluated.
METHODS
METHODS
A clinically used beam model was re-commissioned introducing changes to depth dose curves, output factors, profiles or combinations of those. Seventeen altered beam models with incremental changes of the modelling parameters were created to analyze dose changes on simplified anatomical phantoms. Additionally, fourteen altered models incorporate changes in the order of signal differences reported for typically used detectors. Eighteen treatment plans of different types were recalculated on patient CT data sets using the altered beam models.
RESULTS
RESULTS
For the majority of clinical plans, dose distributions in the target volume recalculated on the patient computed tomography data were similar between the original and the modified beam models, yielding global 2%/2 mm gamma pass rates above 98.9%. Larger changes were observed for certain combinations of beam modelling errors and anatomical sites, most extreme for output factor changes in a small target volume plan with a pass rate of 80.6%. Modelling an enlarged penumbra as if measured with a 0.125 cm
CONCLUSION
CONCLUSIONS
While the simulated errors during beam modelling had little effect on most plans, in some cases changes were considerable. High-quality penumbra and small field output factor should be a main focus of commissioning measurements. Detecting modelling issues using standard patient QA phantoms is unlikely. Verification of a beam model should be performed especially for plans with high modulation and in different depths or geometries representing the variety of situations expected clinically.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
8044-8056Subventions
Organisme : Deutsche Forschungsgemeinschaft
ID : 259319519
Informations de copyright
© 2023 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.
Références
Das IJ, Cheng CW, Watts RJ, et al. Accelerator beam data commissioning equipment and procedures: report of the TG-106 of the Therapy Physics Committee of the AAPM. Med Phys. 2008;35(9):4186-4215.
Ezzell GA, Galvin JM, Low D, et al. Guidance document on delivery, treatment planning, and clinical implementation of IMRT: report of the IMRT subcommittee of the AAPM radiation therapy committee. Med Phys. 2003;30(8):2089-2115.
Smilowitz JB, Das IJ, Feygelman V, et al. AAPM medical physics practice guideline 5.a.: commissioning and QA of treatment planning dose calculations-megavoltage photon and electron beams. J Appl Clin Med Phys. 2015;16:14-34.
Edward SS, CG M, Peterson CB, et al. Dose calculation errors as a component of failing IROC lung and spine phantom irradiations. Med Phys. 2020;47(9):4502-4508.
Kerns JR, Stingo F, Followill DS, Howell RM, Melancon A, Kry SF. Treatment planning system calculation errors are present in most imaging and radiation oncology core-houston phantom failures. Int J Radiat Oncol Biol Phys. 2017;98(5):1197-1203.
Lechner W, Wesolowska P, Azangwe G, et al. A multinational audit of small field output factors calculated by treatment planning systems used in radiotherapy. Phys Imaging Radiat Oncol. 2018;5:58-63.
Fenwick JD, Kumar S, Scott AJ, Nahum AE. Using cavity theory to describe the dependence on detector density of dosimeter response in non-equilibrium small fields. Phys Med Biol. 2013;58(9):2901-2923.
IAEA. Dosimetry of Small Static Fields Used in External Beam Radiotherapy. International Atomic Energy Agency; 2017.
Looe HK, Harder D, Poppe B. Understanding the lateral dose response functions of high-resolution photon detectors by reverse Monte Carlo and deconvolution analysis. Phys Med Biol. 2015;60(16):6585-6607.
Wegener S, Sauer OA. Energy response corrections for profile measurements using a combination of different detector types. Med Phys. 2018;45(2):898-907.
Liu H, Li F, Park J, et al. Feasibility of photon beam profile deconvolution using a neural network. Med Phys. 2018;45(12):5586-5596.
Bednarz G, Huq MS, Rosenow UF. Deconvolution of detector size effect for output factor measurement for narrow Gamma Knife radiosurgery beams. Phys Med Biol. 2002;47(20):3643.
Rice RK, Hansen JL, Svensson GK, Siddon RL. Measurements of dose distributions in small beams of 6 MV x-rays. Phys Med Biol. 1987;32(9):1087-1099.
Ezzell GA, Burmeister JW, Dogan N, et al. IMRT commissioning: multiple institution planning and dosimetry comparisons, a report from AAPM Task Group 119. Med Phys. 2009;36(11):5359-5373.
McVicker D, Yin FF, Adamson JD. On the sensitivity of TG-119 and IROC credentialing to TPS commissioning errors. J Appl Clin Med Phys. 2016;17(1):34-48.
Azimi R, Alaei P, Higgins P. The effect of small field output factor measurements on IMRT dosimetry. Med Phys. 2012;39(8):4691-4694.
Clemente S, Falco MD, Cagni E, et al. The influence of small field output factors simulated uncertainties on the calculated dose in VMAT plans for brain metastases: a multicentre study. Br J Radiol. 2021;94(1119):20201354.
Lechner W, Primessnig A, Nenoff L, Wesolowska P, Izewska J, Georg D. The influence of errors in small field dosimetry on the dosimetric accuracy of treatment plans. Acta Oncol. 2020;59(5):511-517.
Steers JM, Fraass BA. IMRTQA: selecting gamma criteria based on error detection sensitivity. Med Phys. 2016;43(4):1982-1994.
Yan G, Fox C, Liu C, Li JG. The extraction of true profiles for TPS commissioning and its impact on IMRT patient-specific QA. Med Phys. 2008;35(8):3661-3670.
Kry SF, Molineu A, Kerns JR, et al. Institutional patient-specific IMRT QA does not predict unacceptable plan delivery. Int J Radiat Oncol Biol Phys. 2014;90(5):1195-1201.
Dobberthien BJ, Cao F, Zhao Y, Harvey E, Badragan G. Effect of inaccurate small field output factors on brain SRS plans. Biomed Phys Eng Express. 2022;8(2). doi:10.1088/2057-1976/ac4a85
Sánchez D, Mauricio M, García-Garduño Olivia A. The impact of output correction factor in non-conventional radiation fields for dose distribution calculation in radiosurgery: preliminary results. AIP Conf Proc. 2021;2348(1):050034.
Netherton T, Li Y, Gao S, et al. Experience in commissioning the halcyon linac. Med Phys. 2019;46(10):4304-4313.
De Roover R, Crijns W, Poels K, et al. Validation and IMRT/VMAT delivery quality of a preconfigured fast-rotating O-ring linac system. Med Phys. 2019;46(1):328-339.
Xu Z, Warrell G, Lee S, et al. Assessment of beam-matched linacs quality/accuracy for interchanging SBRT or SRT patient using VMAT without replanning. J Appl Clin Med Phys. 2019;20(1):68-75.
Glenn MC, Peterson CB, Followill DS, Howell RM, Pollard-Larkin JM, Kry SF. Reference dataset of users' photon beam modeling parameters for the Eclipse, Pinnacle, and RayStation treatment planning systems. Med Phys. 2020;47(1):282-288.
Miften M, Olch A, Mihailidis D, et al. Tolerance limits and methodologies for IMRT measurement-based verification QA: recommendations of AAPM Task Group No. 218. Med Phys. 2018;45(4):e53-e83.
McKenzie EM, Balter PA, Stingo FC, Jones J, Followill DS, Kry SF. Toward optimizing patient-specific IMRT QA techniques in the accurate detection of dosimetrically acceptable and unacceptable patient plans. Med Phys. 2014;41(12):121702.
Razinskas G, Wegener S, Greber J, Sauer OA. Sensitivity of the IQM transmission detector to errors of VMAT plans. Med Phys. 2018;45(12):5622-5630.
Steers JM, Fraass BA. IMRT QA and gamma comparisons: the impact of detector geometry, spatial sampling, and delivery technique on gamma comparison sensitivity. Med Phys. 2021;48(9):5367-5381.
Nelms BE, Zhen H, Tomé WA. Per-beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors. Med Phys. 2011;38(2):1037-1044.
Spickermann H, Wegener S, Sauer OA. Evaluation of the reconstructed dose from the three-dimensional dose module of a helical diode array: factors of influence and error detection. Phys Med Biol. 2019;64(1):015010.
Wegener S, Sauer OA. Separation of scatter from small MV beams and its effect on detector response. Med Phys. 2017;44(3):1139-1148.
Wegener S, Herzog B, Sauer OA. Detector response in the buildup region of small MV fields. Med Phys. 2020;47(3):1327-1339.
Das IJ, Francescon P, Moran JM, et al. Report of AAPM Task Group 155: megavoltage photon beam dosimetry in small fields and non-equilibrium conditions. Med Phys. 2021;48(10):e886-e921.