Assessment of the impact of CT calibration procedures for proton therapy planning on pediatric treatments.


Journal

Medical physics
ISSN: 2473-4209
Titre abrégé: Med Phys
Pays: United States
ID NLM: 0425746

Informations de publication

Date de publication:
Sep 2021
Historique:
revised: 11 06 2021
received: 07 02 2021
accepted: 13 06 2021
pubmed: 27 6 2021
medline: 23 9 2021
entrez: 26 6 2021
Statut: ppublish

Résumé

Relative stopping powers (RSPs) for proton therapy are estimated using single-energy computed tomography (SECT), calibrated with standardized tissues of the adult male. It is assumed that those tissues are representative of tissues of all age and sex. Female, male, and pediatric tissues differ from one another in density and composition. In this study, we use tabulated pediatric tissues and computational phantoms to investigate the impact of this assumption on pediatric proton therapy. The potential of dual-energy CT (DECT) to improve the accuracy of these calculations is explored. We study 51 human body tissues, categorized into male/female for the age groups newborn, 1-, 5-, 10-, and 15-year-old children, and adult, with given compositions and densities. CT numbers are simulated and RSPs are estimated using SECT and DECT methods. Estimated tissue RSPs from each method are compared to theoretical RSPs. The dose and range errors of each approach are evaluated on three computational phantoms (Ewing's sarcoma, salivary sarcoma, and glioma) derived from pediatric proton therapy patients. With SECT, soft tissues have mean estimation errors and standard deviation up to (1.96 ± 4.18)% observed in newborns, compared to (0.20 ± 1.15)% in adult males. Mean estimation errors for bones are up to (-3.35 ± 4.76)% in pediatrics as opposed to (0.10 ± 0.66)% in adult males. With DECT, mean errors reduce to (0.17 ± 0.13)% and (0.23 ± 0.22)% in newborns (soft tissues/bones). With SECT, dose errors in a Ewing's sarcoma phantom are exceeding 5 Gy (10% of prescribed dose) at the distal end of the treatment field, with volumes of dose errors >5 Gy of Single-energy computed tomography estimates RSPs for pediatric tissues with systematic shifts. DECT improves the accuracy of RSPs and dose distributions in pediatric tissues compared to the SECT calibration curve based on adult male tissues.

Identifiants

pubmed: 34174092
doi: 10.1002/mp.15062
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

5202-5218

Subventions

Organisme : National Institute for Health Research University College London Hospitals Biomedical Research Centre
Organisme : Radiation Research Unit at the Cancer Research UK
ID : C7893/A28990
Organisme : UKRI
ID : MR/T040785/1
Organisme : China Scholarship Council-UCL Joint Research Scholarship
ID : 201809150003
Organisme : Medical Research Council
ID : MR/T040785/1
Pays : United Kingdom

Informations de copyright

© 2021 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.

Références

Levin WP, Kooy H, Loeffler JS, DeLaney TF. Proton beam therapy. Br J Cancer. 2005;93(8):849.
Newhauser WD, Durante M. Assessing the risk of second malignancies after modern radiotherapy. Nat Rev Cancer. 2011;11(6):438-448. https://doi.org/10.1038/nrc3069
Hall EJ. Intensity-modulated radiation therapy, protons, and the risk of second cancers. Int J Radiat Oncol Biol Phys. 2006;65(1):1-7. https://doi.org/10.1016/j.ijrobp.2006.01.027
Moeller BJ, Chintagumpala M, Philip JJ, Woo SY, Wolff JE, Mahajan A. Proton radiotherapy for pediatric medulloblastoma: improved early ototoxicity. Int J Radiat Oncol Biol Phys. 2010;78(3):S18. https://doi.org/10.1016/j.ijrobp.2010.07.083
Torunn I, Yock, BY. Yeap DH, et al. Long-term toxic effects of proton radiotherapy for paediatric medulloblastoma: a phase 2 single-arm study. Lancet Oncol. 2016;17(3):287-298. https://doi.org/10.1016/S1470-2045(15)00167-9
Paulino AC, Mahajan A, Ye R, et al. Ototoxicity and cochlear sparing in children with medulloblastoma: proton vs. photon radiotherapy. Radioth Oncol, 2018;128(1):128-132. https://doi.org/10.1016/j.radonc.2018.01.002
Haas-Kogan D, Indelicato D, Paganetti H, et al. National cancer institute workshop on proton therapy for children: considerations regarding brainstem injury. Int J Radiat Oncol Biol Phys. 2018;101(1):152-168.
Yuh GE, Loredo LN, Yonemoto LT, et al. Reducing toxicity from craniospinal irradiation: using proton beams to treat medulloblastoma in young children. Cancer J. 2004;10(6):386-390. https://doi.org/10.1097/00130404-200411000-00009
St. Clair WH, Adams JA, Bues M, et al. Advantage of protons compared to conventional X-ray or IMRT in the treatment of a pediatric patient with medulloblastoma. Int J Radiat Oncol Biol Phys. 2004;58(3):727-734. https://doi.org/10.1016/S0360-3016(03)01574-8
Miralbell R, Lomax A, Cella L, Schneider U. Potential reduction of the incidence of radiation-induced second cancers by using proton beams in the treatment of pediatric tumors. Int J Radiat Oncol Biol Phys. 2002;54(3):824-829. https://doi.org/10.1016/S0360-3016(02)02982-6
Merchant TE. Proton beam therapy in pediatric oncology. Cancer J. 2009;15(4):298-305.
Merchant TE, Hua CH, Shukla H, Ying X, Nill S, Oelfke U. Proton versus photon radiotherapy for common pediatric brain tumors: comparison of models of dose characteristics and their relationship to cognitive function. Pediatr Blood Cancer. 2008;51(1):110-117. https://doi.org/10.1002/pbc.21530
Kahalley LS, Ris MD, Grosshans DR, et al. Comparing intelligence quotient change after treatment with proton versus photon radiation therapy for pediatric brain tumors. J Clin Oncol. ;34(10):1043-1049. https://doi.org/10.1200/JCO.2015.62.1383
Indelicato DJ, Flampouri S, Rotondo RL, et al. Incidence and dosimetric parameters of pediatric brainstem toxicity following proton therapy. Acta Oncol. 2014;53(10):1298-1304. https://doi.org/10.3109/0284186X.2014.957414
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(3):395-401. https://doi.org/10.1016/j.radonc.2016.11.001
Gunther JR, Sato M, Chintagumpala M, et al. Imaging changes in pediatric intracranial ependymoma patients treated with proton beam radiation therapy compared to intensity modulated radiation therapy. Int J Radiat Oncol Biol Phys. 2015;93(1):54-63. https://doi.org/10.1016/j.ijrobp.2015.05.018
Schneider U, Pedroni E, Lomax A. The calibration of CT Hounsfield units for radiotherapy treatment planning. Phys Med Biol. 1996;41(1):111.
White DR, Woodard HQ, Hammond SM. Average soft-tissue and bone models for use in radiation dosimetry. Br J Radiol. 1987;60(717):907-913.
Woodard HQ, White DR. The composition of body tissues. Br J Radiol. 1986;59(708):1209-1218.
White DR, Griffith RV, Wilson IJ. Report 46. J Int Commiss Radiat Units Measur. 1992;os24(1):NP. https://doi.org/10.1093/jicru/os24.1.report46
White DR, Widdowson EM, Woodard HQ, Dickerson JWT. The composition of body tissues. (II) Fetus to young adult. Br J Radiol. 1991;64(758):149-159. https://doi.org/10.1259/0007-1285-64-758-149
ICRP. ICRP Publication 110: adult reference computational phantoms. Ann ICRP. 2008;49(3):13-201. https://doi.org/10.1016/j.icrp.2009.07.004
Lee C, Lodwick D, Hurtado J, Pafundi D, Williams JL, Bolch WE. The UF family of reference hybrid phantoms for computational radiation dosimetry. Phys Med Biol. 2010;55(2):339-363.
Bolch W, Lee C, Wayson M, Johnson P. Hybrid computational phantoms for medical dose reconstruction. Radiat Environ Biophys. 2010;49(2):155-168.
Wayson MB, Leggett RW, Jokisch DW, et al. Suggested reference values for regional blood volumes in children and adolescents. Phys Med Biol. 2018;63(15):155022. https://doi.org/10.1088/1361-6560/aad313
Wayson MB. Computational internal dosimetry methods as applied to the University of Florida series of hybrid phantoms. Florida: University of Florida; 2012.
Pafundi D, Lee C, Watchman C, et al. An image-based skeletal tissue model for the ICRP reference newborn. Phys Med Biol. 2009;54(14):4497-4531. https://doi.org/10.1088/0031-9155/54/14/009
Bolch WE, Eckerman K, Endo A, et al. ICRP publication 143. Paediatr Ref Comput Phant. 2020;49(1):5-297.
Valentin J. ICRP. 89. Annals of the ICRP 32. Int Commiss Radiol Protect. 2002;32(3-4):1-277. https://doi.org/10.1016/0167-8140(93)90180-G
Zankl M, Eckerman KF, Bolch WE. Voxel-based models representing the male and female ICRP reference adult - The skeleton. Radiat Prot Dosimetry. 2007;127(1-4):174-186. https://doi.org/10.1093/rpd/ncm269
ICRP. ICRP 70. Annals of the ICRP. 1995. https://doi.org/10.1016/S0146-6453(00)80004-4
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. https://doi.org/10.1016/j.phro.2018.04.006
Poludniowski G, Landry G, Deblois F, Evans PM, Verhaegen F. SpekCalc: a program to calculate photon spectra from tungsten anode x-ray tubes. Phys Med Biol. 2009;54(19):N433. https://doi.org/10.1088/0031-9155/54/19/N01
Berger MJ. XCOM: Photon Cross Section Database (version 1.5). Online. 2010. http://physics.nist.gov/xcom
Bourque AE, Carrier J-F, Bouchard H. A stoichiometric calibration method for dual energy computed tomography. Phys Med Biol. 2014;59(8):2059.
Bethe H. Zur Theorie des Durchgangs schneller Korpuskularstrahlen durch Materie. Ann Phys. 1930;397(3):325-400.
Bär E, Andreo P, Lalonde A, Royle G, Bouchard H. Optimized I-values for use with the Bragg additivity rule and their impact on proton stopping power and range uncertainty. Phys Med Biol. 2018;63(16):165007.
Remy C, Lalonde A, Béliveau-Nadeau D, Carrier JF, Bouchard H. Dosimetric impact of dual-energy CT tissue segmentation for low-energy prostate brachytherapy: a Monte Carlo study. Phys Med Biol. 2018;63(2):025013. https://doi.org/10.1088/1361-6560/aaa30c
Beaulieu L, Carlsson Tedgren A, Carrier JF, et al. Report of the Task Group 186 on model-based dose calculation methods in brachytherapy beyond the TG-43 formalism: current status and recommendations for clinical implementation. Med Phys. 2012;39(10):6208-6236.
Pedregosa F, Varoquaux G, Gramfort A, et al. Scikit-learn: machine learning in Python. J Mach Learn Res. 2011;12(Oct):2825-2830.
Yang M, Zhu XR, Park PC, et al. Comprehensive analysis of proton range uncertainties related to patient stopping-power-ratio estimation using the stoichiometric calibration. Phys Med Biol. 2012;57(13):4095.
Bär E, Lalonde A, Royle G, Lu HM, Bouchard H. The potential of dual-energy CT to reduce proton beam range uncertainties. Med Phys. 2017;44(6):2332-2344. https://doi.org/10.1002/mp.12215
Paganetti H. Range uncertainties in proton therapy and the role of Monte Carlo simulations. Phys Med Biol. 2012;57(11):R99-R117.
Goitein M. Calculation of the uncertainty in the dose delivered during radiation therapy. Med Phys. 1985;12(5):608-612. https://doi.org/10.1118/1.595762
Gan HW, Phipps K, Aquilina K, Gaze MN, Hayward R, Spoudeas HA. Neuroendocrine morbidity after pediatric optic gliomas: a longitudinal analysis of 166 children over 30 years. J Clin Endocrinol Metab. 2015;100(10):3787-3799. https://doi.org/10.1210/jc.2015-2028
Tan TSE, Patel L, Gopal-Kothandapani JS, et al. The neuroendocrine sequelae of paediatric craniopharyngioma: a 40-year meta-data analysis of 185 cases from three UK centres. Eur J Endocrinol. 2017;176(3):359-369. https://doi.org/10.1530/EJE-16-0812
Vivekanandan S, Breene R, Ramanujachar R, et al. The UK experience of a treatment strategy for pediatric metastatic medulloblastoma comprising intensive induction chemotherapy, hyperfractionated accelerated radiotherapy and response directed high dose myeloablative chemotherapy or maintenance chemotherapy. Pediatr Blood Cancer. 2015;62(12):2132-2139. https://doi.org/10.1002/pbc.25663
Thust SC, Blanco E, Michalski AJ, et al. MRI abnormalities in children following sequential chemotherapy, hyperfractionated accelerated radiotherapy and high-dose thiotepa for high-risk primitive neuroectodermal tumours of the central nervous system. J Med Imaging Radiat Oncol. 2014;58(6):683-690. https://doi.org/10.1111/1754-9485.12232
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(3):526-533. https://doi.org/10.1016/j.radonc.2017.09.042
Wohlfahrt P, Möhler C, Troost E, Greilich S, Richter C. Dual-energy computed tomography to assess intra- and inter-patient tissue variability for proton treatment planning of patients with brain tumor. Int J Radiat Oncol Biol Phys. 2019;105(3):504-513. https://doi.org/10.1016/j.ijrobp.2019.06.2529
Collins-Fekete CA, Brousmiche S, Hansen DC, Beaulieu L, Seco J. Pre-treatment patient-specific stopping power by combining list-mode proton radiography and x-ray CT. Phys Med Biol. 2017;62(17):6836-6852. https://doi.org/10.1088/1361-6560/aa7c42
Dedes G, Dickmann J, Niepel K, et al. Experimental comparison of proton CT and dual energy x-ray CT for relative stopping power estimation in proton therapy. Phys Med Biol. 2019;64(16):165002. https://doi.org/10.1088/1361-6560/ab2b72
Poludniowski G, Allinson NM, Evans PM. Proton radiography and tomography with application to proton therapy. Br J Radiol. 2015;88(1053):20150134.
Schulte R, Bashkirov V, Li T, et al. Conceptual design of a proton computed tomography system for applications in proton radiation therapy. IEEE Trans Nucl Sci. 2004;51(3):866-872. https://doi.org/10.1109/TNS.2004.829392

Auteurs

Esther Bär (E)

Department of Medical Physics and Biomedical Engineering, University College London, London, UK.

Charles-Antoine Collins-Fekete (CA)

Department of Medical Physics and Biomedical Engineering, University College London, London, UK.

Vasilis Rompokos (V)

Department of Radiotherapy Physics, University College London Hospitals NHS Foundation Trust, London, UK.

Ying Zhang (Y)

Department of Medical Physics and Biomedical Engineering, University College London, London, UK.

Mark N Gaze (MN)

Department of Oncology, University College London Hospitals NHS Foundation Trust, London, UK.

Alison Warry (A)

Department of Radiotherapy Physics, University College London Hospitals NHS Foundation Trust, London, UK.

Andrew Poynter (A)

Department of Radiotherapy Physics, University College London Hospitals NHS Foundation Trust, London, UK.

Gary Royle (G)

Department of Medical Physics and Biomedical Engineering, University College London, London, UK.

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