Guía para el control de calidad y seguridad de los sistemas de planificación y planes de tratamiento de radioterapia externa

Autores/as

  • Alejandro García Romero Hospital Clínico Universitario Lozano Blesa de Zaragoza.
  • Montserrat Baeza Trujillo Hospital Universitario Virgen del Rocío de Sevilla.
  • Antonio Teijeiro García Hospital Do Meixoeiro de Vigo.
  • Francisco Clemente Gutiérrez Complejo Hospitalario de Toledo
  • Daniel Morera Cano Hospital Univeritario Son Espases, Palma de Mallorca.
  • Víctor Hernández Masgrau Hospital Sant Joan de Reus, IISPV.

DOI:

https://doi.org/10.37004/sefm/2024.25.1.008

Palabras clave:

Sistema de planificación de tratamientos, verificación de planes, garantía de calidad, estado de referencia inicial, auditorías, test end-to-end

Resumen

El contenido del documento refleja las recomendaciones de la SEFM para el control de calidad y uso seguro de los sistemas de planificación de radioterapia externa. Se hace una exposición inicial de los motivos, consideraciones generales y principales novedades a tener en cuenta en los sistemas de planificación actuales, para pasar a analizar detalladamente la caracterización de las unidades de tratamiento y los parámetros que hay que tener en cuenta en el modelado de las mismas, haciendo especial hincapié en aquellos que tienen que ver con el colimador multilámina. En el documento se distinguen tres secciones diferentes que tratan de abarcar todo aquello que influye en que el producto del sistema de planificación, el plan de tratamiento, tenga la mejor calidad y seguridad asociada: control de calidad del sistema de planificación, garantía de calidad del proceso de planificación y verificación de planes de tratamiento, todo ello siempre manteniendo la visión que proporciona el análisis de riesgos asociado.

El programa de control de calidad se establece en tres pasos: estado de referencia inicial, controles periódicos y controles tras actualizaciones. Añadido a esto, se analiza el proceso de planificación y cómo garantizar la calidad en el mismo por medio de procesos globales (auditorías y pruebas end-to-end), evaluación de planes y sistematización relacionada con la protocolización y las soluciones de clase. Por último, se describen las herramientas de verificación de planes y sus limitaciones, las métricas asociadas así como las estrategias de verificación posibles. Todo el documento culmina con un último capítulo que resume todas las recomendaciones basándose en lo expuesto y concreta las tolerancias a utilizar en cada etapa.

Referencias

del ESTADO BO. REAL DECRETO, 1566/1998, 17 de julio, por el que se establecen los criterios de calidad en radioterapia. Boletín Of del Estado. 1998:29383-29395. papers2://publication/uuid/099423F4-7378-45A5-AE99-CD26B6AABEA3.

Ministerio de Sanidad. Real Decreto 601/2019, de 18 de octubre, sobre justificación y optimización del uso de las radiaciones ionizantes para la protección radiológica de las personas con ocasión de exposiciones médicas. Boletín Of del estado. 2019;262:120840-120856.

Millan-Cebrian E, Garcia-Vicente F, Delgado-Rodríguez JM. Protocolo de Control de Calidad de Sistemas de Planificación En Radioterapia y Braquiterapia. (SEFM, ed.). SEFM; 2005.

Delgado-Rodríguez JM, García-Romero A, Millán Cebrián E, García Vicente F. Fundamentos de Física Médica: Volumen 4. Dosimetría Clínica, Algoritmos de Cálculo y Sistemas de Planificación y Control de Calidad. 1st ed. (SEFM, ed.). ADI Servicios Editoriales; 2013.

Ahnesjö A, Aspradakis MM. Dose calculations for external photon beams in radiotherapy. Phys Med Biol. 1999;44:R99-R115.

Andreo P. Monte Carlo techniques in medical radiation physics. Phys Med Biol. 1991;36(7):861-920. https://doi.org/10.1088/0031-9155/36/7/001

Curran B, Cygler JE, Demarco JJ, et al. Report of the AAPM Task Group No . 105 : Issues associated with clinical implementation of Monte Carlo-based photon and electron external beam treatment planning. Organization. 2007;(105):4818-4853. https://doi.org/10.1118/1.2795842

Vassiliev ON, Wareing T a, McGhee J, Failla G, Salehpour MR, Mourtada F. Validation of a new grid-based Boltzmann equation solver for dose calculation in radiotherapy with photon beams. Phys Med Biol. 2010;55(3):581-598. https://doi.org/10.1088/0031-9155/55/3/002

Knöös T, Wieslander E, Cozzi L, et al. Comparison of dose calculation algorithms for treatment planning in external photon beam therapy for clinical situations. Phys Med Biol. 2006;51(22):5785-5807. https://doi.org/10.1088/0031-9155/51/22/005

Ojala J, Kapanen M, Sipilä P, Hyödynmaa S. The accuracy of Acuros XB algorithm for radiation beams traversing a metallic hip implant — comparison with measurements and Monte Carlo calculations. 2014;15(5):162-176.

Berger M. Methods in Computational Physics. (Alder B, Fernbach S, Rotenberg M, eds.). Academic Press; 1963.

Huang JY, Dunkerley D, Smilowitz JB. Evaluation of a commercial Monte Carlo dose calculation algorithm for electron treatment planning. J Appl Clin Med Phys. 2019;20(6):184-193. https://doi.org/10.1002/acm2.12622

Ma CMC, Chetty IJ, Deng J, et al. Beam modeling and beam model commissioning for Monte Carlo dose calculation-based radiation therapy treatment planning: Report of AAPM Task Group 157. Med Phys. 2020;47(1):e1-e18. https://doi.org/10.1002/mp.13898

Adam DP, Liu T, Caracappa PF, Bednarz BP, Xu XG. New capabilities of the Monte Carlo dose engine ARCHER-RT: Clinical validation of the Varian TrueBeam machine for VMAT external beam radiotherapy. Med Phys. 2020;47(6):2537-2549. https://doi.org/10.1002/mp.14143

Fippel M. Fast Monte Carlo dose calculation for photon beams based on the VMC electron algorithm. Med Phys. 1999;26(8):1466-1475. http://www.ncbi.nlm.nih.gov/pubmed/10501045.

Raaijmakers AJE, Raaymakers BW, Lagendijk JJW. Integrating a MRI scanner with a 6 MV radiotherapy accelerator: dose increase at tissue-air interfaces in a lateral magnetic field due to returning electrons. Phys Med Biol. 2005;50(7):1363-1376. https://doi.org/10.1088/0031-9155/50/7/002

Han T, Mikell JK, Salehpour M, Mourtada F. Dosimetric comparison of Acuros XB deterministic radiation transport method with Monte Carlo and model-based convolution methods in heterogeneous media. Med Phys. 2011;38(5):2651-2664. https://doi.org/10.1118/1.3582690

Siebers J V, Keall PJ, Nahum AE, Mohan R. Converting absorbed dose to medium to absorbed dose to water for Monte Carlo based photon beam dose calculations. Phys Med Biol. 2000;45(4):983-995. http://www.ncbi.nlm.nih.gov/pubmed/10795986.

Ma C, Li J. Dose specification for radiation therapy : dose to water or dose to medium ? 2011;56:3073-3089. https://doi.org/10.1088/0031-9155/56/10/012

ICRU. Prescribing, Recording, and Reporting of Stereotactic Treatments with Small Photon Beams. J ICRU. 2014;14(2):1-5. https://doi.org/10.1093/jicru/ndx013

Andreo P. Dose to “water-like” media or dose to tissue in MV photons radiotherapy treatment planning: still a matter of debate. Phys Med Biol. 2015;60(1):309-337. https://doi.org/10.1088/0031-9155/60/1/309

Gladstone DJ, Kry SF, Xiao Y, Chetty IJ. Dose Specification for NRG Radiation Therapy Trials. Int J Radiat Oncol. 2016;95(5):1344-1345. https://doi.org/10.1016/j.ijrobp.2016.03.044

Kry SF, Feygelman V, Balter P, et al. AAPM Task Group 329 Reference dose specification for dose calculations: Dose-to-water or dose-to-muscle? Med Phys. 2019;47(3):e52-e64.

Al-Hallaq HA, Chmura SJ, Salama JK, et al. Benchmark Credentialing Results for NRG-BR001: The First National Cancer Institute-Sponsored Trial of Stereotactic Body Radiation Therapy for Multiple Metastases. Int J Radiat Oncol. 2017;97(1):155-163. https://doi.org/10.1016/j.ijrobp.2016.09.030

Fernández-Varea JM, Carrasco P, Panettieri V, Brualla L. Monte Carlo based water/medium stopping-power ratios for various ICRP and ICRU tissues. Phys Med Biol. 2007;52(21):6475-6483. https://doi.org/10.1088/0031-9155/52/21/009

Younes T, Chauvin M, Delbaere A, et al. Towards the standardization of the absorbed dose report mode in high energy photon beams. Phys Med Biol. 2021;66(4):45009. https://doi.org/10.1088/1361-6560/abd22c

Kry SF, Lye J, Clark CH, et al. Report dose-to-medium in clinical trials where available; a consensus from the Global Harmonisation Group to maximize consistency. Radiother Oncol. 2021;159:106-111. https://doi.org/10.1016/j.radonc.2021.03.006

Muñoz-Montplet C, Marruecos J, Buxó M, et al. Dosimetric impact of Acuros XB dose-to-water and dose-to-medium reporting modes on VMAT planning for head and neck cancer. Phys Medica. 2018;55:107-115. https://doi.org/10.1016/j.ejmp.2018.10.024

Jurado-Bruggeman D, Muñoz-Montplet C, Hernandez V, Saez J, Fuentes-Raspall R. Impact of the dose quantity used in MV photon optimization on dose distribution, robustness, and complexity. Med Phys. 2022;49(1):648-665. https://doi.org/10.1002/mp.15389

Draeger E, Sawant A, Johnstone C, et al. A Dose of Reality: How 20 Years of Incomplete Physics and Dosimetry Reporting in Radiobiology Studies May Have Contributed to the Reproducibility Crisis. Int J Radiat Oncol. 2020;106(2):243-252. https://doi.org/10.1016/j.ijrobp.2019.06.2545

García Riñón D, Ferrer Gracia C, Huertas Martínez C, Sánchez López R, Sáez Beltrán M. Comparación de dosis absorbida en agua y dosis absorbida en medio en tratamientos de próstata y cabeza y cuello. Análisis con diferentes tamaños de rejilla y curvas de calibración CT. Rev Física Médica. 2022;23(1):11-26. https://doi.org/10.37004/sefm/2022.23.1.001

Romero AG, Masgrau VH, García AT, Gutiérrez FC, Cano DM. Resultados de la encuesta de la Sociedad Española de Física Médica sobre el control de calidad de los sistemas de planificación de tratamientos en el ámbito de haces de fotones y electrones de radioterapia externa Results of the SEFM’s national survey o. Rev Física Médica. 2021;22(2):55-66.

Jia X, Ziegenhein P, Jiang SB. GPU-based high-performance computing for radiation therapy. Phys Med Biol. 2014;59(4):R151-82. https://doi.org/10.1088/0031-9155/59/4/R151

Edmund JM, Nyholm T. A review of substitute CT generation for MRI-only radiation therapy. Radiat Oncol. 2017;12(1):1-15. https://doi.org/10.1186/s13014-016-0747-y

Craft D, Mcquaid D, Wala J, Chen W, Salari E, Bortfeld T. Multicriteria VMAT optimization. Med Phys. 2014;686(2012). https://doi.org/10.1118/1.3675601

Unkelbach J, Bortfeld T, Craft D, et al. Optimization approaches to volumetric modulated arc therapy planning Optimization approaches to volumetric modulated arc therapy planning. Med Phys. 2015;1367. https://doi.org/10.1118/1.4908224

AAPM Task Group 166 TPC. The Use and QA of Biologically Related Models for Treatment Planning Report of AAPM Task Group 166.; 2012.

Fogliata A, Thompson S, Stravato A, Tomatis S, Scorsetti M, Cozzi L. On the gEUD biological optimization objective for organs at risk in Photon Optimizer of Eclipse treatment planning system. J Appl Clin Med Phys. 2018;(October 2017):106-114. https://doi.org/10.1002/acm2.12224

Vanetti E, Nicolini G, Nord J, et al. On the role of the optimization algorithm of RapidArc® volumetric modulated arc therapy on plan quality and efficiency On the role of the optimization algorithm of RapidArc V volumetric modulated arc therapy on plan quality and efficiency. Med Phys. 2014;5844(2011). https://doi.org/10.1118/1.3641866

Palmans H, Andreo P, Huq S, Seuntjens J. Dosimetry of small static fields used in external beam radiotherapy: An IAEA-AAPM International Code of Practice for reference and relative dose determination. Technical Report Series No. 483. Iaea Trs483. 2017;(November). http://www-pub.iaea.org/MTCD/Publications/PDF/D483_web.pdf.

Sharp G, Fritscher KD, Pekar V, et al. Vision 20/20: Perspectives on automated image segmentation for radiotherapy. Med Phys. 2014;41(5):1-13. https://doi.org/10.1118/1.4871620

Fu Y, Zhang H, Morris ED, et al. Artificial Intelligence in Radiation Therapy. IEEE Trans Radiat Plasma Med Sci. 2022;6(2):158-181.

Wang C, Zhu X, Hong JC, Zheng D. Artificial Intelligence in Radiotherapy Treatment Planning: Present and Future. Technol Cancer Res Treat. 2019;18:1-11. https://doi.org/10.1177/1533033819873922

Liu X, Li K, Yang R, Geng L. Review of Deep Learning Based Automatic Segmentation for Lung Cancer Radiotherapy Basis of Deep Learning. Front Oncol. 2021;11(July):1-16. https://doi.org/10.3389/fonc.2021.717039

Hussein M, Heijmen BJM, Verellen D, Nisbet A. Automation in intensity modulated radiotherapy treatment planning — a review of recent innovations. Br J Radiol. 2018;91(July).

Hussein M, Heijmen BJM, Verellen D, Nisbet A. Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations. Br J Radiol. 2018;91(1092). https://doi.org/10.1259/bjr.20180270

Craft D, Wala J, Chen W, Salari E, Bortfeld T. Multicriteria VMAT optimization. Med Phys. 2012;39(2):686-696. https://doi.org/10.1118/1.3675601

Liu H, Sintay B, Pearman K, et al. Comparison of the progressive resolution optimizer and photon optimizer in VMAT optimization for stereotactic treatments. J Appl Clin Med Phys 2018;(April):155-162. https://doi.org/10.1002/acm2.12355

Yan H, Dai J, Li Y. A fast optimization approach for treatment planning of volumetric modulated arc therapy. Radiat Oncol. 2018:1-13.

Wheeler PA, Chu M, Holmes R, et al. Utilisation of Pareto navigation techniques to calibrate a fully automated radiotherapy treatment planning solution. Phys Imaging Radiat Oncol. 2019;10(April):41-48. https://doi.org/10.1016/j.phro.2019.04.005

Hrinivich WT, Lee J. Artificial intelligence-based radiotherapy machine parameter optimization using reinforcement learning. Med Phys. 2020;47(12):6140-6150. https://doi.org/10.1002/mp.14544

Moore KL. Automated Radiotherapy Treatment Planning. Semin Radiat Oncol. 2019;29(3):209-218. https://doi.org/10.1016/j.semradonc.2019.02.003

Brock KK, Mutic S, McNutt TR, Li H, Kessler ML. Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the AAPM Radiation Therapy Committee Task Group No. 132: Report. Med Phys. 2017;44(7):e43-e76. https://doi.org/10.1002/mp.12256

García-Mollá R, Sánchez Rubio P, Bonaque Alandí J, Carrasco Herrera MA, Lliso Valverde F. Implementación y uso clínico de la radioterapia adaptativa. Informe del grupo de trabajo de radioterapia adaptativa de la Sociedad Española de Física Médica (SEFM). Rev Física Médica. 2021;22(1):123-166. https://doi.org/10.37004/sefm/2021.22.1.004

Dutreix A. When and how can we improve precision in radiotherapy? Radiother Oncol J Eur Soc Ther Radiol Oncol. 1984;2(4):275-292. https://doi.org/10.1016/s0167-8140(84)80070-5

Mijnheer BJ, Battermann JJ, Wambersie A. What degree of accuracy is required and can be achieved in photon and neutron therapy? Radiother Oncol J Eur Soc Ther Radiol Oncol. 1987;8(3):237-252. https://doi.org/10.1016/s0167-8140(87)80247-5

Dyk J Van, Barnett RB, Cygler JE, Shragge PC. Commissioning and quality assurance of treatment planning computers. Int J Radiat Oncol Biol Phys. 1993;26(2):261-273. https://doi.org/10.1016/0360-3016(93)90206-B

Ahnesjö a, Aspradakis MM. Dose calculations for external photon beams in radiotherapy. Phys Med Biol. 1999;44(11):R99-155. http://www.ncbi.nlm.nih.gov/pubmed/10588277.

Zhu TC, Stathakis S, Clark JR, et al. Report of AAPM Task Group 219 on independent calculation-based dose/MU verification for IMRT. Med Phys. 2021;48(10):e808-e829. https://doi.org/10.1002/mp.15069

Andreo P, Izewska J, Shortt K, Vatnitsky S. IAEA Technical Reports Series No. 430: Commissioning And Quality Assurance Of Computerized Planning Systems For Radiation Treatment Of Cancer. IAEA TECDOC 430. 2004:281.

Mijnheer B, Olszewska A, Fiorino C. Estro Booklet No7. Quality Assurance of Treatment Planning Systems.; 2008.

D. Schuring, Westendorp H, Bijl E van der, et al. Quality Assurance of Treatment Planning Systems Practical guideline for verification of installations and updates of treatment. NCS reports. 2022;(July). https://doi.org/10.25030/ncs-035

Geurts MW, Jacqmin DJ, Mihailidis DN, et al. AAPM Medical Physics Practice Guideline 5. b: Commissioning and QA of treatment planning dose calculations — Megavoltage photon and electron beams. J Appl Clin Med Phys. 2022. https://doi.org/10.1002/acm2.13641

International Atomic Energy Agency IAEA. IAEA-TECDOC-1583. Commissioning of Radiotherapy Treatment Planning Systems : Testing for Typical External Beam Treatment Techniques. 2008.

Ghazal M, Södergren L, Westermark M, Söderström J, Pommer | Tobias. Dosimetric and mechanical equivalency of Varian TrueBeam linear accelerators beam-matching, DLG and jaw calibration, energy-matching. J Appl Clin Med Phys. 2020;21:43-53. https://doi.org/10.1002/acm2.13058

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. https://doi.org/10.1118/1.2969070

Chen S, Yi BY, Yang X, Xu H, Prado KL, D’Souza WD. Optimizing the MLC model parameters for IMRT in the RayStation treatment planning system. J Appl Clin Med Phys. 2015;16(5):322-332. https://doi.org/10.1120/jacmp.v16i5.5548

Georg D, Heukelom S, Venselaar J. Formalisms for MU calculations, ESTRO booklet 3 versus NCS report 12. Radiother Oncol. 2001;60(3):319-328. https://doi.org/10.1016/S0167-8140(01)00348-6

Gershkevitsh E, Schmidt R, Velez G, et al. Dosimetric verification of radiotherapy treatment planning systems: Results of IAEA pilot study. Radiother Oncol. 2008;89(3):338-346. https://doi.org/10.1016/j.radonc.2008.07.007

Bruinvis IAD, Keus RB, Lenglet WJM, et al. Quality assurance of 3-D treatment planning systems for external photon and electron beams. Ned Comm voor Stralingsdosimetrie. 2005;15(March):1-31.

Liu C, Li Z, Palta JR. Characterizing output for the Varian enhanced dynamic wedge field. Med Phys. 1998;25(1):64-70. https://doi.org/10.1118/1.598161

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. https://doi.org/10.1002/mp.15030

Chang Z, Wu Q, Adamson J, et al. Commissioning and dosimetric characteristics of TrueBeam system: composite data of three TrueBeam machines. Med Phys. 2012;39(11):6981-7018. https://doi.org/10.1118/1.4762682

Ezzell G a., 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. https://doi.org/10.1118/1.3238104

Carrasco P, Jornet N, Duch M a., et al. Comparison of dose calculation algorithms in phantoms with lung equivalent heterogeneities under conditions of lateral electronic disequilibrium. Med Phys. 2004;31(10):2899. https://doi.org/10.1118/1.1788932

Fogliata A, Lobefalo F, Reggiori G, et al. Evaluation of the dose calculation accuracy for small fields defined by jaw or MLC for AAA and Acuros XB algorithms. Med Phys. 2016;43(10):5685-5694. https://doi.org/10.1118/1.4963219

Williams MJ, Metcalfe P. Verification of a rounded leaf-end MLC model used in a radiotherapy treatment planning system. Phys Med Biol. 2006;51(4):N65-78. https://doi.org/10.1088/0031-9155/51/4/N03

Mzenda B, Mugabe K V., Sims R, Godwin G, Loria D. Modeling and dosimetric performance evaluation of the RayStation treatment planning system. J Appl Clin Med Phys. 2014;15(5):29-46. https://doi.org/10.1120/jacmp.v15i5.4787

Young LA, Yang F, Cao N, Meyer J. Rounded leaf end modeling in Pinnacle VMAT treatment planning for fixed jaw linacs. J Appl Clin Med Phys. 2016;17(6):149-162. https://doi.org/10.1120/jacmp.v17i6.6343

Kinsella P, Shields L, McCavana P, McClean B, Langan B. Determination of MLC model parameters for Monaco using commercial diode arrays. J Appl Clin Med Phys. 2016;17(4):37-47. https://doi.org/10.1120/jacmp.v17i4.6190

Snyder M, Halford R, Knill C, et al. Modeling the Agility MLC in the Monaco treatment planning system. J Appl Clin Med Phys. 2016;17(3):190-202. https://doi.org/10.1120/jacmp.v17i3.6044

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. 2016;17(1):6166.

Mans A, Schuring D, Arends MP, et al. The NCS code of practice for the quality assurance and control for volumetric modulated arc therapy. Phys Med Biol. 2016;61(19):7221-7235. https://doi.org/10.1088/0031-9155/61/19/7221

McKenzie EM, Balter P a, 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. https://doi.org/10.1118/1.4899177

Glenn MC, Peterson CB, Howell RM, Followill DS, Pollard-Larkin JM, Kry SF. Sensitivity of IROC phantom performance to radiotherapy treatment planning system beam modeling parameters based on community-driven data. Med Phys. 2020. https://doi.org/10.1002/mp.14396

Nelms BE, Chan MF, Jarry G, et al. Evaluating IMRT and VMAT dose accuracy: practical examples of failure to detect systematic errors when applying a commonly used metric and action levels. Med Phys. 2013;40(11):111722. https://doi.org/10.1118/1.4826166

Kry SF, Molineu A, Kerns J, et al. Institutional patient-specific intensity-modulated radiation therapy quality assurance does not predict unacceptable plan delivery as measured by IROC Houston’s head and neck phantom. Int J Radiat Oncol Biol Phys. 2014;90(5):1195-1201. https://doi.org/10.1016/j.ijrobp.2014.08.334.Institutional

Koger B, Price R, Wang D, Toomeh D, Geneser S, Ford E. Impact of the MLC leaf-tip model in a commercial TPS: Dose calculation limitations and IROC-H phantom failures. J Appl Clin Med Phys. 2020;21(2):82-88. https://doi.org/10.1002/acm2.12819

Vieillevigne L, Khamphan C, Saez J, Hernandez V. On the need for tuning the dosimetric leaf gap for stereotactic treatment plans in the Eclipse treatment planning system. J Appl Clin Med Phys. 2019;(May):68-77. https://doi.org/10.1002/acm2.12656

Hernandez V, Saez J, Angerud A, et al. Dosimetric leaf gap and leaf trailing effect in a double-stacked multileaf collimator. Med Phys. 2021;48(7):3413-3424. https://doi.org/10.1002/mp.14914

Hernandez V, Angerud A, Bogaert E, et al. Challenges in modeling the Agility multileaf collimator in treatment planning systems and current needs for improvement. Med Phys. 2022;49(12):7404-7416. https://doi.org/10.1002/mp.16016

Saez J, Hernandez V, Goossens J, De Kerf G, Verellen D. A novel procedure for determining the optimal: MLC. configuration parameters in treatment planning systems based on measurements with a Farmer chamber. Phys Med Biol. 2020;65(15). https://doi.org/10.1088/1361-6560/ab8cd5

Kielar KN, Mok E, Hsu A, Wang L, Luxton G. Verification of dosimetric accuracy on the TrueBeam STx: Rounded leaf effect of the high definition MLC. Med Phys. 2012;39(10):6360-6371. https://doi.org/10.1118/1.4752444

Kim J, Han JS, Hsia AT, Li S, Xu Z, Ryu S. Relationship between dosimetric leaf gap and dose calculation errors for high definition multi-leaf collimators in radiotherapy. Phys Imaging Radiat Oncol. 2018;5(September 2017):31-36. https://doi.org/10.1016/j.phro.2018.01.003

Yao W, Farr JB. Determining the optimal dosimetric leaf gap setting for rounded leaf-end multileaf collimator systems by simple test fields. J Appl Clin Med Phys. 2015;16(4):65-77. https://doi.org/10.1120/jacmp.v16i4.5321

Hernandez V, Vera-Sánchez JA, Vieillevigne L, Saez J. Commissioning of the tongue-and-groove modelling in treatment planning systems: From static fields to VMAT treatments. Phys Med Biol. 2017;62(16):6688-6707. https://doi.org/10.1088/1361-6560/aa7b1a

Antoine M, Ralite F, Soustiel C, et al. Use of metrics to quantify IMRT and VMAT treatment plan complexity: A systematic review and perspectives. Phys Medica. 2019;64. https://doi.org/10.1016/j.ejmp.2019.05.024

Chiavassa S, Bessieres I, Edouard M, Mathot M, Moignier A. Complexity metrics for IMRT and VMAT plans: A review of current literature and applications. Br J Radiol. 2019;92(1102). https://doi.org/10.1259/bjr.20190270

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. https://doi.org/10.1002/mp.12810

Saez J, Bar-Deroma R, Bogaert E, et al. Universal evaluation of MLC models in treatment planning systems based on a common set of dynamic tests. Radiother Oncol. 2023;186:109775. https://doi.org/10.1016/j.radonc.2023.109775

Saini A, Tichacek C, Johansson W, et al. Unlocking a closed system: dosimetric commissioning of a ring gantry linear accelerator in a multivendor environment. J Appl Clin Med Phys. 2021;22(2):21-34. https://doi.org/10.1002/acm2.13116

Passal V, Barreau M, Tiplica T, Dufreneix S. Optimizing the effective spot size and the dosimetric leaf gap of the AcurosXB algorithm for VMAT treatment planning. J Appl Clin Med Phys. 2021;22(6):154-161. https://doi.org/10.1002/acm2.13256

Hill DL, Batchelor PG, Holden M, Hawkes DJ. Medical image registration. Phys Med Biol. 2001;46(3):R1-45. http://www.ncbi.nlm.nih.gov/pubmed/11277237.

Hussein M, Akintonde A, McClelland J, Speight R, Clark CH. Clinical use, challenges, and barriers to implementation of deformable image registration in radiotherapy – the need for guidance and QA tools. Br J Radiol. 2021;94(1122). https://doi.org/10.1259/bjr.20210001

Olch AJ, Gerig L, Li H, Mihaylov I, Morgan A. Dosimetric effects caused by couch tops and immobilization devices: Report of AAPM Task Group 176. Med Phys. 2014;41(6). https://doi.org/10.1118/1.4876299

Chen W, Wang C, Zhan W, et al. A comparative study of auto-contouring softwares in delineation of organs at risk in lung cancer and rectal cancer. Sci Rep. 2021;11(1):1-8. https://doi.org/10.1038/s41598-021-02330-y

Zabel WJ, Conway JL, Gladwish A, et al. Clinical Evaluation of Deep Learning and Atlas-Based Auto-Contouring of Bladder and Rectum for Prostate Radiation Therapy. Pract Radiat Oncol. 2021;11(1):e80-e89. https://doi.org/10.1016/J.PRRO.2020.05.013

Wong J, Huang V, Wells D, et al. Implementation of deep learning-based auto-segmentation for radiotherapy planning structures: a workflow study at two cancer centers. Radiat Oncol. 2021;16(1):1-10. https://doi.org/10.1186/s13014-021-01831-4

Boyd R a., Hogstrom KR, Antolak J a., Shiu AS. A measured data set for evaluating electron-beam dose algorithms. Med Phys. 2001;28(6):950. https://doi.org/10.1118/1.1374245

Ding GX, Cygler JE, Zhang GG, Yu MK. Evaluation of a commercial three-dimensional electron beam treatment planning system. Med Phys. 1999;26(12):2571-2580. https://doi.org/10.1118/1.598795

Venselaar J, Welleweerd H, Mijnheer B. Tolerances for the accuracy of photon beam dose calculations of treatment planning systems. Radiother Oncol. 2001;60(2):191-201. https://doi.org/10.1016/S0167-8140(01)00377-2

Koger B, Price R, Wang D, Toomeh D, Geneser S, Ford E. Impact of the MLC leaf-tip model in a commercial TPS: Dose calculation limitations and IROC-H phantom failures. J Appl Clin Med Phys. 2020. https://doi.org/10.1002/acm2.12819

van Elmpt WJC, Nijsten SMJJG, Dekker AL a. J, Mijnheer BJ, Lambin P. Treatment verification in the presence of inhomogeneities using EPID-based three-dimensional dose reconstruction. Med Phys. 2007;34(7):2816. https://doi.org/10.1118/1.2742778

Vieillevigne L, Khamphan C, Saez J, Hernandez V. On the need for tuning the dosimetric leaf gap for stereotactic treatment plans in the Eclipse treatment planning system. J Appl Clin Med Phys. 2019;20(7):68-77. https://doi.org/10.1002/acm2.12656

Mechalakos JG, Dieterich S, Fong de los Santos LE, et al. Electronic charting of radiation therapy planning and treatment: Report of Task Group 262. Med Phys. 2021;48(11):e927-e968. https://doi.org/10.1002/mp.15116

Medical Imaging and Technology Alliance. Supplement 11: Radiotherapy Objects DICOM-RT. DICOM-RT Suppl. 1997;(June).

Medical Imaging and Technology Alliance. Supplement 29: Radiotherapy Treatment Records and Radiotherapy Media Extensions. DICOM-RT Suppl. 1999;(May):1-7.

IAEA. Record and Verify Systems for Radiation Treatment of Cancer: Acceptance Testing, Commissioning and Quality Control. Heal Rep Ser. 2013;7:39. http://www-pub.iaea.org/MTCD/Publications/PDF/Pub1607_web.pdf.

AAPM Task Group 263. Standardizing Nomenclatures in Radiation Oncology: The Report of AAPM Task Group 263.; 2018. https://www.aapm.org/pubs/reports/RPT_263.pdf.

Huq MS, Fraass BA, Dunscombe PB, et al. The report of Task Group 100 of the AAPM: Application of risk analysis methods to radiation therapy quality management. Med Phys. 2016;43(33):4078-3874. https://doi.org/10.1118/1.2349696

Little MP, Wakeford R, Tawn EJ, Bouffler SD, Berrington de Gonzalez A. Risks associated with low doses and low dose rates of ionizing radiation: why linearity may be (almost) the best we can do. Radiology. 2009;251(1):6-12. https://doi.org/10.1148/radiol.2511081686

Fraass B, Doppke K, Hunt M, et al. AAPM TG 53. Quality assurance for clinical radiotherapy treatment planning. Med Phys. 1998;25(10):1773-1829.

Siochi RA, Balter P, Bloch CD, et al. Report of Task Group 201 of the American Association of Physicists in Medicine: Quality management of external beam therapy data transfer. Med Phys. 2021. https://doi.org/10.1002/mp.14868

Lehmann J, Alves A, Dunn L, et al. Dosimetric end-to-end tests in a national audit of 3D conformal radiotherapy. Phys Imaging Radiat Oncol. 2018;6(October 2017):5-11. https://doi.org/10.1016/j.phro.2018.03.006

Yeung TK, Bortolotto K, Cosby S, Hoar M, Lederer E. Quality assurance in radiotherapy: evaluation of errors and incidents recorded over a 10 year period. Radiother Oncol. 2005;74(3):283-291. https://doi.org/10.1016/j.radonc.2004.12.003

Oh Y, Shin DO, Kim J, et al. Proposal on Guideline for Quality Assurance of Radiation Treatment Planning System. Prog Med Phys. 2017;28(4):197. https://doi.org/10.14316/pmp.2017.28.4.197

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. https://doi.org/10.1016/j.ijrobp.2017.03.049

Derreumaux S, Etard C, Huet C, et al. Lessons from recent accidents in radiation therapy in France. Radiat Prot Dosimetry. 2008;131(1):130-135. https://doi.org/10.1093/rpd/ncn235

Proyecto MARR (Matrices de riesgo en radioterapia). 2016. http://www.sefm.es/new/download/1.-MARR-Documento-MARR.pdf.

Ezzell G a., 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. https://doi.org/10.1118/1.1591194

Mijnheer B GD. Guidelines for the verification of IMRT. Physics for Clinical Radiotherapy. Bookl no 9 Brussels ESTRO. 2008.

Palmer AL, Nash D, Kearton JR, Jafari SM, Muscat S. A multicentre “end to end” dosimetry audit of motion management (4DCT-defined motion envelope) in radiotherapy. Radiother Oncol J Eur Soc Ther Radiol Oncol. 2017;125(3):453-458. https://doi.org/10.1016/j.radonc.2017.09.033

Chow JCL, Grigorov GN. Surface dosimetry for oblique tangential photon beams: A Monte Carlo simulation study. Med Phys. 2008;35(1):70. https://doi.org/10.1118/1.2818956

Kry SF, Bednarz B, Howell RM, et al. AAPM TG 158: Measurement and calculation of doses outside the treated volume from external-beam radiation therapy. Med Phys. 2017. https://doi.org/10.1002/mp.12462

Thwaites D. Accuracy required and achievable in radiotherapy dosimetry: Have modern technology and techniques changed our views? J Phys Conf Ser. 2013;444(1). https://doi.org/10.1088/1742-6596/444/1/012006

Ibbott GS, Thwaites DI. Audits for advanced treatment dosimetry. J Phys Conf Ser. 2015;573(1). https://doi.org/10.1088/1742-6596/573/1/012002

Gershkevitsh E, Pesznyak C, Petrovic B, et al. Dosimetric inter-institutional comparison in European radiotherapy centres: Results of IAEA supported treatment planning system audit. Acta Oncol (Madr). 2014;53(5):628-636. https://doi.org/10.3109/0284186X.2013.840742

Melidis C, Bosch WR, Izewska J, et al. Global harmonization of quality assurance naming conventions in radiation therapy clinical trials. Int J Radiat Oncol Biol Phys. 2014;90(5):1242-1249. https://doi.org/10.1016/j.ijrobp.2014.08.348

Kron T, Haworth A, Williams I. Dosimetry for audit and clinical trials: Challenges and requirements. J Phys Conf Ser. 2013;444(1). https://doi.org/10.1088/1742-6596/444/1/012014

Lee J, Mayles HMO, Baker C, Jafari S, Distefano G, Clark C. UK SABR Consortium Lung Dosimetry Audit; relative dosimetry results. Radiother Oncol. 2015;115:95-96. https://doi.org/10.1016/S0167-8140(15)40152-5

Izewska J, Wesolowska P, Azangwe G, et al. Testing the methodology for dosimetry audit of heterogeneity corrections and small MLC-shaped fields: Results of IAEA multi-center studies. Acta Oncol (Madr). 2016;55(7):909-916. https://doi.org/10.3109/0284186X.2016.1139180

Weber DC, Poortmans PMP, Hurkmans CW, Aird E, Gulyban A, Fairchild A. Quality assurance for prospective EORTC radiation oncology trials: the challenges of advanced technology in a multicenter international setting. Radiother Oncol J Eur Soc Ther Radiol Oncol. 2011;100(1):150-156. https://doi.org/10.1016/j.radonc.2011.05.073

Weber DC, Vallet V, Molineu A, et al. IMRT Credentialing for Prospective Trials Using Institutional Virtual Phantoms: Results of a Joint European Organization for the Research and Treatment of Cancer and Radiological Physics Center Project.; 2014. https://doi.org/10.1186/1748-717X-9-123

Alvarez P, Molineu A, Lowenstein J, Taylor P, Kry S, Followill D. SU-F-T-485: Independent Remote Audits for TG51 NonCompliant Photon Beams Performed by the IROC Houston QA Center. Med Phys. 2016;43(6Part20):3574. https://doi.org/10.1118/1.4956670

Kry SF, Dromgoole L, Alvarez P, et al. Radiotherapy deficiencies identified during on-site dosimetry visits by the IROC HoustonQA Center. Int J Radiat Oncol Biol Phys. 2017;99(5):1094-1100. https://doi.org/10.1016/j.ijrobp.2017.08.013

Miles E, Venables K. Radiotherapy quality assurance: facilitation of radiotherapy research and implementation of technology. Clin Oncol (R Coll Radiol). 2012;24(10):710-712. https://doi.org/10.1016/j.clon.2012.06.006

Ishikura S, Ito Y, Hiraoka M. JCOG Radiation Therapy Study Group: history and achievements. Jpn J Clin Oncol. 2011;41(11):1241-1243. https://doi.org/10.1093/jjco/hyr126

Pasler M, Hernandez V, Jornet N, Clark CH. Novel methodologies for dosimetry audits: Adapting to advanced radiotherapy techniques. Phys Imaging Radiat Oncol. 2018;5(September 2017):76-84. https://doi.org/10.1016/j.phro.2018.03.002

McGarry CK, Agnew CE, Hussein M, et al. The role of complexity metrics in a multi-institutional dosimetry audit of VMAT. Br J Radiol. 2016;89(1057). https://doi.org/10.1259/bjr.20150445

Tsang Y, Ciurlionis L, Clark C, Venables K, On UK. Development of a novel treatment planning test for credentialing rotational intensity-modulated radio-therapy techniques in the UK. Br J Radiol. 2013;86. https://doi.org/10.1259/bjr.20120315

Jornet N, Carrasco P, Beltrán M, et al. Multicentre validation of IMRT pre-treatment verification: comparison of in-house and external audit. Radiother Oncol. 2014;112(3):381-388. https://doi.org/10.1016/j.radonc.2014.06.016

Clark CH, Hussein M, Tsang Y, et al. A multi-institutional dosimetry audit of rotational intensity-modulated radiotherapy. Radiother Oncol. 2014;113(2):272-278. https://doi.org/10.1016/J.RADONC.2014.11.015

Jurado-Bruggeman D, Hernández V, Sáez J, et al. Multi-centre audit of VMAT planning and pre-treatment verification. Radiother Oncol. 2017;124(2):302-310. https://doi.org/10.1016/j.radonc.2017.05.019

Hussein M, Tsang Y, Thomas RAS, et al. A methodology for dosimetry audit of rotational radiotherapy using a commercial detector array. Radiother Oncol J Eur Soc Ther Radiol Oncol. 2013;108(1):78-85. https://doi.org/10.1016/j.radonc.2013.05.027

Spreeuw H, Rozendaal R, Olaciregui-ruiz I, Mans A, Mijnheer B, Herk M Van. Online 3D EPID-based dose verification : proof of concept. Med Phys. 2016;43(7):1-13. https://doi.org/10.1118/1.4952729

Olaciregui-Ruiz I, Rozendaal R, Mijnheer B, van Herk M, Mans a. Automatic in vivo portal dosimetry of all treatments. Phys Med Biol. 2013;58(22):8253-8264. https://doi.org/10.1088/0031-9155/58/22/8253

Woodruff HC, Fuangrod T, Van Uytven E, et al. First Experience With Real-Time EPID-Based Delivery Verification During IMRT and VMAT Sessions. Int J Radiat Oncol Biol Phys. 2015;93(3):516-522. https://doi.org/10.1016/j.ijrobp.2015.07.2271

Fuangrod T, Greer PB, Woodruff HC, et al. Investigation of a real-time EPID-based patient dose monitoring safety system using site-specific control limits. Radiat Oncol. 2016. https://doi.org/10.1186/s13014-016-0682-y

Passarge M, Fix MK, Manser P, Stampanoni MFM, Siebers J V. A Swiss cheese error detection method for real-time EPID-based quality assurance and error prevention. Med Phys. 2017;44(4):1212-1223. https://doi.org/10.1002/mp.12142

Thoelking J, Fleckenstein J, Sekar Y, et al. Patient-specific online dose verification based on transmission detector measurements. Radiother Oncol J Eur Soc Ther Radiol Oncol. 2016;119(2):351-356. https://doi.org/10.1016/j.radonc.2016.04.003

Hoffman D, Chung E, Hess | Clayton, Stern R, Benedict S. Characterization and evaluation of an integrated quality monitoring system for online quality assurance of external beam radiation therapy. J Appl Clin Med Phys. 2017;18:40-48. https://doi.org/10.1002/acm2.12014

Islam MK, Norrlinger BD, Smale JR, et al. An integral quality monitoring system for real-time verification of intensity modulated radiation therapy. Med Phys. 2009;36(12):5420-5428. https://doi.org/10.1118/1.3250859

Pasler M, Michel K, Marrazzo L, et al. Error detection capability of a novel transmission detector: a validation study for online VMAT monitoring. Phys Med Biol. 2017;62(18):7440-7450. https://doi.org/10.1088/1361-6560/aa7dc7

Boylan CJ, Aitkenhead AH, Rowbottom CG, Mackay RI. Simulation of realistic linac motion improves the accuracy of a Monte Carlo based VMAT plan QA system. Radiother Oncol J Eur Soc Ther Radiol Oncol. 2013;109(3):377-383. https://doi.org/10.1016/j.radonc.2013.08.046

Kerns JR, Childress N, Kry SF. A Multi-Institution Evaluation of MLC Log Files and Performance in IMRT Delivery.; Radiat Oncol. 2014. https://doi.org/10.1186/1748-717X-9-176

Clark CH, Ga Aird E, Bolton S, et al. Radiotherapy dosimetry audit: Three decades of improving standards and accuracy in UK clinical practice and trials. Br J Radiol. 2015;88(1055). https://doi.org/10.1259/bjr.20150251

Followill DS, Evans DR, Cherry C, et al. Design, development, and implementation of the radiological physics center’s pelvis and thorax anthropomorphic quality assurance phantoms. Med Phys. 2007;34(6):2070-2076. https://doi.org/10.1118/1.2737158

Distefano G, Lee J, Jafari S, et al. A national dosimetry audit for stereotactic ablative radiotherapy in lung. Radiother Oncol. 2017;122(3):406-410. https://doi.org/10.1016/j.radonc.2016.12.016

Lambrecht M, Melidis C, Sonke J-J, et al. Lungtech, a phase II EORTC trial of SBRT for centrally located lung tumours-a clinical physics perspective. Radiat Oncol. 2016. https://doi.org/10.1186/s13014-015-0567-5

Clark CH, Hurkmans CW, Kry SF. The role of dosimetry audit in lung SBRT multi-centre clinical trials. Phys medica. 2017;44:171-176. https://doi.org/10.1016/j.ejmp.2017.04.003

Molineu A, Hernandez N, Nguyen T, Ibbott G, Followill D. Credentialing results from IMRT irradiations of an anthropomorphic head and neck phantom. Med Phys. 2013;40(2):1-8. https://doi.org/10.1118/1.4773309

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(February):58-63. https://doi.org/10.1016/j.phro.2018.02.005

Followill DS, Kry SF, Qin L, et al. The Radiological Physics Center's standard dataset for small field size output factors J Appl Clin Med Phys. Vol 13.; 2012. https://doi.org/10.1120/jacmp.v13i5.3962

Kerns JR, Followill DS, Lowenstein J, et al. Agreement Between Institutional Measurements and Treatment Planning System Calculations for Basic Dosimetric Parameters as Measured by the Imaging and Radiation Oncology Core-Houston HHS Public Access. Int J Radiat Oncol Biol Phys. 2016;95(5):1527-1534. https://doi.org/10.1016/j.ijrobp.2016.03.035

Kry SF. Beyond auditing : What we have learned from phantom credentialing for clinical trials. 2014.

Seravalli E, Houweling AC, Van Battum L, et al. Auditing local methods for quality assurance in radiotherapy using the same set of predefined treatment plans. Phys Imaging Radiat Oncol. 2018;5(September 2017):19-25. https://doi.org/10.1016/j.phro.2018.01.002

Followill DS, Clark CH, Kron T. Clinical 3D Dosimetry in Modern Radiation Therapy. 1st ed. CRC Press; 2017.

Pulliam KB, Huang JY, Howell RM, et al. Comparison of 2D and 3D gamma analyses. Med Phys. 2014;41(2):021710. https://doi.org/10.1118/1.4860195

Ibbott GS. QA in radiation therapy: The RPC perspective. J Phys Conf Ser. 2010;250:1-7. https://doi.org/10.1088/1742-6596/250/1/012001

Hernandez V, Hansen CR, Widesott L, et al. What is plan quality in radiotherapy? The importance of evaluating dose metrics, complexity, and robustness of treatment plans. Radiother Oncol. 2020;153(xxxx):26-33. https://doi.org/10.1016/j.radonc.2020.09.038

Hansen CR, Hussein M, Bernchou U, Zukauskaite R, Thwaites D. Plan quality in radiotherapy treatment planning - Review of the factors and challenges. J Med Imaging Radiat Oncol. 2022;66(2):267-278. https://doi.org/10.1111/1754-9485.13374

Dionisi F, Fiorica F, D’Angelo E, et al. Organs at risk’s tolerance and dose limits for head and neck cancer re-irradiation: A literature review. Oral Oncol. 2019;98:35-47. https://doi.org/10.1016/j.oraloncology.2019.08.017

DeLuca PM, Seltzer SM. ICRU Report 83. ICRU Rep 83. 2008;8(2):1-98. https://doi.org/10.1093/jicru/ndn032

Hansen CR, Friborg J, Jensen K, et al. NTCP model validation method for DAHANCA patient selection of protons versus photons in head and neck cancer radiotherapy. Acta Oncol (Madr). 2019;58(10):1410-1415. https://doi.org/10.1080/0284186X.2019.1654129

Wilke L, Andratschke N, Guckenberger M, et al. ICRU report 91 on prescribing, recording, and reporting of stereotactic treatments with small photon beams. Strahlentherapie und Onkol. 195(3):193-198. http://inis.iaea.org/search/search.aspx?orig_q=RN:51000335.

Akpati H, Kim C, Kim B, Park T, Meek A. Unified Dosimetry Index (UDI): A Figure of Merit for Ranking Treatment Plans; J Appl Clin Med Phys, Vol 9.; 2008. https://doi.org/10.1120/jacmp.v9i3.2803

Ruan D, Shao W, Demarco J, et al. Evolving treatment plan quality criteria from institution-specific experience. Med Phys. 2012;39(5):2708-2712. https://doi.org/10.1118/1.4704497

Ventura T, Do M, Lopes C, Ferreira BC, Khouri L. ScienceDirect SPIDERplan: A tool to support decision-making in radiation therapy treatment plan assessment. Rep Pract Oncol Radiother. 2016. https://doi.org/10.1016/j.rpor.2016.07.002

Mambretti M, Romanò C, Marvaso G, et al. A global Unified Dosimetry Index (gUDI) to evaluate simultaneous integrated boost radiotherapy plans in prostate cancer. Radiother Oncol . 2018;128(2):315-320. https://doi.org/10.1016/j.radonc.2018.06.002

Nelms BE, Robinson G, Markham J, et al. Variation in external beam treatment plan quality: An inter-institutional study of planners and planning systems. Pract Radiat Oncol. 2012;2(4):296-305. https://doi.org/10.1016/j.prro.2011.11.012

Ahmed S, Nelms B, Gintz D, et al. A method for a priori estimation of best feasible DVH for organs-at-risk: Validation for head and neck VMAT planning. Med Phys. 2017;44(10):5486-5497. https://doi.org/10.1002/mp.12500

Stroom JC, de Boer HCJ, Huizenga H, Visser AG. Inclusion of geometrical uncertainties in radiotherapy treatment planning by means of coverage probability. Int J Radiat Oncol Biol Phys. 1999;43(4):905-919. https://doi.org/10.1016/S0360-3016(98)00468-4

van Herk M, Remeijer P, Rasch C, Lebesque J V. The probability of correct target dosage: dose-population histograms for deriving treatment margins in radiotherapy. Int J Radiat Oncol Biol Phys. 2000;47(4):1121-1135. https://doi.org/10.1016/S0360-3016(00)00518-6

Liu PZY, Reggiori G, Lobefalo F, et al. Small field correction factors for the IBA Razor. Phys Medica. 2016;32(8):1025-1029. https://doi.org/10.1016/j.ejmp.2016.07.004

McKenzie A, van Herk M, Mijnheer B. Margins for geometric uncertainty around organs at risk in radiotherapy. Radiother Oncol. 2002;62(3):299-307. https://doi.org/10.1016/S0167-8140(02)00015-4

Stroom JC, Heijmen BJM. Limitations of the planning organ at risk volume (PRV) concept. Int J Radiat Oncol. 2006;66(1):279-286. https://doi.org/10.1016/j.ijrobp.2006.05.009

Sterpin E. Potential pitfalls of the PTV concept in dose-to-medium planning optimization. Phys Medica. 2016;32(9):1103-1110. https://doi.org/10.1016/j.ejmp.2016.08.009

Unkelbach J, Alber M, Bangert M, et al. Robust radiotherapy planning. Phys Med Biol. 2018;63(22):22TR02. https://doi.org/10.1088/1361-6560/aae659

Hong L, Alektiar K, Chui C, et al. IMRT of large fields: whole-abdomen irradiation. Int J Radiat Oncol. 2002;54(1):278-289. https://doi.org/10.1016/S0360-3016(02)02921-8

Evans PM, Donovan EM, Partridge M, et al. The delivery of intensity modulated radiotherapy to the breast using multiple static fields. Radiother Oncol. 2000;57(1):79-89. https://doi.org/10.1016/s0167-8140(00)00263-2

Sankar A, Velmurugan J. Different intensity extension methods and their impact on entrance dose in breast radiotherapy: A study. J Med Phys. 2009;34(4):200-205. https://doi.org/10.4103/0971-6203.56079

Lizondo M, Latorre-Musoll A, Ribas M, et al. Pseudo skin flash on VMAT in breast radiotherapy: Optimization of virtual bolus thickness and HU values. Phys medica. 2019;63:56-62. https://doi.org/10.1016/j.ejmp.2019.05.010

Wiant D, Vanderstraeten C, Maurer J, Pursley J, Terrell J, Sintay BJ. On the validity of density overrides for VMAT lung SBRT planning. Med Phys. 2014;41(8):81707. https://doi.org/10.1118/1.4887778

Healy GEA, Marsh SH, Cousins AT. The dosimetric effect of electron density overrides in 3DCRT Lung SBRT for a range of lung tumor dimensions. J Appl Clin Med Phys. 2018;19(6):79-87. https://doi.org/10.1002/acm2.12446

Crowe SB, Kairn T, Middlebrook N, et al. Examination of the properties of IMRT and VMAT beams and evaluation against pre-treatment quality assurance results. Phys Med Biol. 2015;60(6):2587-2601. https://doi.org/10.1088/0031-9155/60/6/2587

Du W, Cho SH, Zhang X, Hoffman KE, Kudchadker RJ. Quantification of beam complexity in intensity-modulated radiation therapy treatment plans. Med Phys. 2014;41(2):021716. https://doi.org/10.1118/1.4861821

McNiven AL, Sharpe MB, Purdie TG. A new metric for assessing IMRT modulation complexity and plan deliverability. Med Phys. 2010;37(2):505-515. https://doi.org/10.1118/1.3276775

Younge KC, Matuszak MM, Moran JM, Mcshan DL, Fraass BA. Penalization of aperture complexity in inversely planned volumetric modulated arc therapy. Med Phys. 2012;39(11):7160-7170.

Götstedt J, Hauer AK, Bäck A. Complexity metric as a complement to measurement based IMRT/VMAT patient-specific QA. J Phys Conf Ser. 2015;573(1):6-10. https://doi.org/10.1088/1742-6596/573/1/012016

Kairn T, Crowe SB, Kenny J, Knight RT, Trapp J V. Predicting the likelihood of QA failure using treatment plan accuracy metrics. J Phys Conf Ser. 2014;489(1). https://doi.org/10.1088/1742-6596/489/1/012051

Masi L, Doro R, Favuzza V, Cipressi S, Livi L. Impact of plan parameters on the dosimetric accuracy of volumetric modulated arc therapy. Med Phys. 2013;40(7). https://doi.org/10.1118/1.4810969

Park JM, Park S-Y, Kim H. Modulation index for VMAT considering both mechanical and dose calculation uncertainties. Phys Med Biol. 2015;60(18):7101-7125. https://doi.org/10.1088/0031-9155/60/18/7101

Min Park J, Park SY, Kim H, Ho Kim J, Carlson J, Ye SJ. Modulation indices for volumetric modulated arc therapy. Phys Med Biol. 2014;59(23):7315-7340. https://doi.org/10.1088/0031-9155/59/23/7315

Craft D, Süss P, Bortfeld T. The tradeoff between treatment plan quality and required number of monitor units in intensity-modulated radiotherapy. Int J Radiat Oncol Biol Phys. 2007;67(5):1596-1605. https://doi.org/10.1016/j.ijrobp.2006.11.034

Scaggion A, Fusella M, Agnello G, et al. Limiting treatment plan complexity by applying a novel commercial tool. J Appl Clin Med Phys. 2020;21(8):27-34. https://doi.org/10.1002/acm2.12908

Glenn MC, Hernandez V, Saez J, Followill DS, Howell RM. Treatment plan complexity does not predict IROC Houston anthropomorphic head and neck phantom performance. Phys Med Biol. 2018. 17;63(20):205015. https://doi.org/10.1088/1361-6560/aae29e

Hernandez V, Vera-Sánchez JA, Vieillevigne L, Khamphan C, Saez J. A new method for modelling the tongue-and-groove in treatment planning systems. Phys Med Biol. 2018;63(24). https://doi.org/10.1088/1361-6560/aaf098

Kamperis E, Kodona C, Hatziioannou K, Giannouzakos V. Complexity in Radiation Therapy: It’s Complicated. Int J Radiat Oncol Biol Phys. 2020;106(1):182-184. https://doi.org/10.1016/j.ijrobp.2019.09.003

Khoo VS, Bedford JL, Webb S, Dearnaley DP. Class solutions for conformal external beam prostate radiotherapy. Int J Radiat Oncol Biol Phys. 2003;55(4):1109-1120. https://doi.org/10.1016/s0360-3016(02)04393-6

Weksberg DC, Palmer MB, Vu KN, et al. Generalizable class solutions for treatment planning of spinal stereotactic body radiation therapy. Int J Radiat Oncol Biol Phys. 2012;84(3):847-853. https://doi.org/10.1016/j.ijrobp.2011.12.060

Netherlands Commission on Radiation Dosimetry. Subcommittee VMAT QA. Code of Practice for the Quality Assurance and Control for Volumetric Modulated Arc Therapy. NCS Report 24. 2015;(February):65.

Commissie N, Stralingsdosimetrie V. Code of Practice for the Quality Assurance and Control for Intensity Modulated Radiotherapy Disclaimer regarding NCS reports. 2013;(June).

Babier A, Boutilier JJ, Sharpe MB, McNiven AL, Chan TCY. Inverse optimization of objective function weights for treatment planning using clinical dose-volume histograms. Phys Med Biol. 2018;63(10):105004. https://doi.org/10.1088/1361-6560/aabd14

Gallio E, Giglioli FR, Girardi A, et al. Evaluation of a commercial automatic treatment planning system for liver stereotactic body radiation therapy treatments. Phys Medica. 2018;46(March):153-159. https://doi.org/10.1016/j.ejmp.2018.01.016

Harms WBS, Low DA, Wong JW, Purdy JA. A software tool for the quantitative evaluation of 3D dose calculation algorithms. Med Phys. 1998;25(10):1830-1836. https://doi.org/10.1118/1.598363

Low D a, Harms WB, Mutic S, Purdy J a. A technique for the quantitative evaluation of dose distributions. Med Phys. 1998;25(5):656-661. http://www.ncbi.nlm.nih.gov/pubmed/9608475.

Depuydt T, Van Esch A, Huyskens DP. A quantitative evaluation of IMRT dose distributions: refinement and clinical assessment of the gamma evaluation. Radiother Oncol. 2002;62(3):309-319. https://doi.org/10.1016/s0167-8140(01)00497-2

Moran JM, Radawski J, Fraass BA. A gradient analysis tool for IMRT QA. J Appl Clin Med Phys. 2005:62-73.

Childress NL, Rosen II. The design and testing of novel clinical parameters for dose comparison. Int J Radiat Oncol Biol Phys. 2003;56(5):1464-1479. https://doi.org/10.1016/s0360-3016(03)00430-9

Bakai A, Alber M, Nüsslin F. A revision of the gamma-evaluation concept for the comparison of dose distributions. Phys Med Biol. 2003;48(21):3543-3553. https://doi.org/10.1088/0031-9155/48/21/006

Peng J, Shi C, Laugeman E, et al. Implementation of the structural SIMilarity (SSIM) index as a quantitative evaluation tool for dose distribution error detection. Med Phys. 2020;47(4):1907-1919. https://doi.org/10.1002/mp.14010

Ju T, Simpson T, Deasy JO, Low DA. Geometric interpretation of the gamma dose distribution comparison technique: interpolation-free calculation. Med Phys. 2008;35(3):879-887. https://doi.org/10.1118/1.2836952

Nelms BE, Zhen H, Tomé W a. Per-beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors. Med Phys. 2011;38(2):1037. https://doi.org/10.1118/1.3544657

Zhen H, Nelms BE, Tome W a. Moving from gamma passing rates to patient DVH-based QA metrics in pretreatment dose QA. Med Phys. 2011;38(10):5477-5489. https://doi.org/10.1118/1.3633904

Gutiérrez FC, Vara CP. Validación de un sistema de control de calidad pre-tratamiento 3D en técnicas volumétricas basado en matrices bidimensionales de detectores. Revista de física médica. 2015;16(1):11-32.

Garcia-Romero A, Hernandez-Vitoria A, Millan-Cebrian E, Alba-Escorihuela V, Serrano-Zabaleta S, Ortega-Pardina P. On the new metrics for IMRT QA verification. Med Phys. 2016;43(11):6058-6071. https://doi.org/10.1118/1.4964796

Vicini F a, Martinez A, Hanks G, et al. An interinstitutional and interspecialty comparison of treatment outcome data for patients with prostate carcinoma based on predefined prognostic categories and minimum follow-up. Cancer. 2002;95(10):2126-2135. https://doi.org/10.1002/cncr.10919

Leybovich LB, Sethi A, Dogan N. Comparison of ionization chambers of various volumes for IMRT absolute dose verification. Med Phys. 2003;30(2):119-123. https://doi.org/10.1118/1.1536161

Carrasco P, Jornet N, Latorre A, Eudaldo T, Ruiz A, Ribas M. 3D DVH-based metric analysis versus per-beam planar analysis in IMRT pretreatment verification. Med Phys. 2012;39(8):5040-5049. https://doi.org/10.1118/1.4736949

Ling CC, Zhang P, Archambault Y, Bocanek J, Tang G, Losasso T. Commissioning and quality assurance of RapidArc radiotherapy delivery system. Int J Radiat Oncol Biol Phys. 2008;72(2):575-581. https://doi.org/10.1016/j.ijrobp.2008.05.060

Szczurek L, Juszkat RI, Szczurek J, Turek I, Sosnowski P. Pre-treatment 2D and 3D dosimetric verification of volumetric arc therapy. A correlation study between gamma index passing rate and clinical dose volume histogram. PLoS One. 2019. https://doi.org/10.1371/journal.pone.0221086

Niroomand-Rad A, Chiu-Tsao S-T, Grams MP, et al. Report of AAPM Task Group 235 Radiochromic Film Dosimetry: An Update to TG-55. Med Phys. 2020;47(12):5986-6025. https://doi.org/10.1002/mp.14497

Maraghechi B, Davis J, Mitchell N, et al. The sensitivity of gamma index analysis to detect multileaf collimator (MLC) positioning errors using Varian TrueBeam EPID and ArcCHECK for patient-specific prostate volumetric-modulated arc therapy (VMAT) quality assurance. J Radiother Pract. 2018;17(1):66-77. https://doi.org/10.1017/S1460396917000425

Chae S-M, Lee GW, Son SH. The effect of multileaf collimator leaf width on the radiosurgery planning for spine lesion treatment in terms of the modulated techniques and target complexity. Radiat Oncol. 2014;9(1):72. https://doi.org/10.1186/1748-717X-9-72

Woon W, Ravindran PB, Ekanayake P, Vikraman S, Lim YYF, Khalid J. A study on the effect of detector resolution on gamma index passing rate for VMAT and IMRT QA. J Appl Clin Med Phys. 2018;19(2):230-248. https://doi.org/10.1002/acm2.12285

Bresciani S, Poli M, Miranti A, et al. Comparison of two different EPID-based solutions performing pretreatment quality assurance: 2D portal dosimetry versus 3D forward projection method. Phys Medica. 2018;52(June):65-71. https://doi.org/10.1016/j.ejmp.2018.06.005

Chaswal V, Weldon M, Gupta N, Chakravarti A, Rong Y. Commissioning and comprehensive evaluation of the ArcCHECK cylindrical diode array for VMAT pretreatment delivery QA. J Appl Clin Med Phys. 2014;15(4):212-225. https://doi.org/10.1120/jacmp.v15i4.4832

Fontenot JD. Evaluation of a novel secondary check tool for intensity-modulated radiotherapy treatment planning. J Appl Clin Med Phys. 2014;15(5):207-215.

Clemente-Gutiérrez F, Pérez-Vara C. Dosimetric validation and clinical implementation of two 3D dose verification systems for quality assurance in volumetric-modulated arc therapy techniques. J Appl Clin Med Phys. 2015;16(2):198-217. https://doi.org/10.1120/jacmp.v16i2.5190

Greer PB. 3D EPID based dosimetry for pre-treatment verification of VMAT - Methods and challenges. J Phys Conf Ser. 2013;444(1). https://doi.org/10.1088/1742-6596/444/1/012010

Alani S, Schlocker A, Honig N. Statistical Process Control for VMAT Pre-Treatment Verification QA Using ArcCHECK and Mobius3D. Med Phys. Vol 42.; 2015. https://doi.org/10.1118/1.4923932

Han C, Yi J, Zhu K, et al. Cross verification of independent dose recalculation, log files based, and phantom measurement-based pretreatment quality assurance for volumetric modulated arc therapy. J Appl Clin Med Phys. 2020;21(11):98-104. https://doi.org/10.1002/acm2.13036

Boggula R, Lorenz F, Mueller L, et al. Experimental validation of a commercial 3D dose verification system for intensity-modulated arc therapies. Phys Med Biol. 2010;55(19):5619-5633. https://doi.org/10.1088/0031-9155/55/19/001

Bakhtiari M, Parniani A, Lerma F, et al. Evaluation of a software system for estimating planned dose error in patients, based on planar IMRT QA measurements. Radiol Oncol. 2014;48(1):87-93. https://doi.org/10.2478/raon-2013-0042

Bedford JL, Lee YK, Wai P, South CP, Warrington AP. Evaluation of the Delta4 phantom for IMRT and VMAT verification. Phys Med Biol. 2009;54(9):N167-76. https://doi.org/10.1088/0031-9155/54/9/N04

Podesta M, Persoon LCGG, Verhaegen F. A novel time dependent gamma evaluation function for dynamic 2D and 3D dose distributions. Phys Med Biol. 2014;59(20):5973-5985. https://doi.org/10.1088/0031-9155/59/20/5973

Alharthi T, Pogson EM, Arumugam S, Holloway L, Thwaites D. Pre-treatment verification of lung SBRT VMAT plans with delivery errors: Toward a better understanding of the gamma index analysis. Phys Medica. 2018;49:119-128. https://doi.org/10.1016/J.EJMP.2018.04.005

Petrucci E, Radici L, Borca VC, Ferrario S, Paolini M, Pasquino M. Delta(4) Discover transmission detector: A comprehensive characterization for in-vivo VMAT monitoring. Phys medica. 2021;85:15-23. https://doi.org/10.1016/j.ejmp.2021.04.017

Colussi VC, Beddar AS, Kinsella TJ, Sibata CH. In vivo dosimetry using a single diode for megavoltage photon beam radiotherapy: implementation and response characterization. J Appl Clin Med Phys. 2001;2(4):210-218. https://doi.org/10.1120/jacmp.v2i4.2598

Jornet N, Ribas M, Eudaldo T. In vivo dosimetry: Intercomparison between p-type based and n-type based diodes for the 16–25 MV energy range. Med Phys. 2000;27(6):1287-1293. https://doi.org/10.1118/1.599013

Ghafarian M, Price M, Morales-Paliza M. Comparison of pretreatment VMAT quality assurance with the integral quality monitor (IQM) and electronic portal imaging device (EPID) EPID, IQM, pretreatment VMAT QA. J Appl Clin Med Phys. 2021;22(3):166-175. https://doi.org/10.1002/acm2.13201

Olaciregui-Ruiz I, Beddar S, Greer P, et al. In vivo dosimetry in external beam photon radiotherapy: Requirements and future directions for research, development, and clinical practice. Phys Imaging Radiat Oncol. 2020;15(March):108-116. https://doi.org/10.1016/j.phro.2020.08.003

Bossuyt E, Weytjens R, Nevens D, Vos S De, Verellen D. Evaluation of automated pre-treatment and transit in-vivo dosimetry in radiotherapy using empirically determined parameters. Phys Imaging Radiat Oncol. 2020;16(November):113-129.

Fawcett T. An introduction to ROC analysis. Pattern Recognit Lett. 2006;27(8):861-874. https://doi.org/10.1016/j.patrec.2005.10.010

Brown CD, Davis HT. Receiver operating characteristics curves and related decision measures: A tutorial. Chemom Intell Lab Syst. 2006;80(1):24-38. https://doi.org/10.1016/j.chemolab.2005.05.004

Zweig MH, Campbell G. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem. 1993;39(4):561-577.

Carlone M, Cruje C, Rangel A, McCabe R, Nielsen M, MacPherson M. ROC analysis in patient specific quality assurance. Med Phys. 2013;40(4):1-7. https://doi.org/10.1118/1.4795757

Shen Z, Tan X, Li S, et al. Correlation between the γ passing rates of IMRT plans and the volumes of air cavities and bony structures in head and neck cancer. Radiat Oncol. 2021;16(1):1-8. https://doi.org/10.1186/s13014-021-01861-y

Kim J in, Park SY, Kim HJ, Kim JH, Ye SJ, Park JM. The sensitivity of gamma-index method to the positioning errors of high-definition MLC in patient-specific VMAT QA for SBRT. Radiat Oncol. 2014;9(1):1-12. https://doi.org/10.1186/1748-717X-9-167

Kim JI, Kim JH, Park JM. Gamma analysis with a gamma criterion of 2%/1 mm for stereotactic ablative radiotherapy delivered with volumetric modulated arc therapy technique: A single institution experience. Oncotarget. 2017;8(44):76076-76084. https://doi.org/10.18632/oncotarget.18530

Schmitt D, Blanck O, Gauer T, et al. Technological quality requirements for stereotactic radiotherapy: Expert review group consensus from the DGMP Working Group for Physics and Technology in Stereotactic Radiotherapy. Strahlentherapie und Onkol. 2020;196(5):421-443. https://doi.org/10.1007/s00066-020-01583-2

Agnew CE, McGarry CK. A tool to include gamma analysis software into a quality assurance program. Radiother Oncol. 2016;118(3):568-573. https://doi.org/10.1016/j.radonc.2015.11.034

Hussein M, Clementel E, Eaton DJ, et al. A virtual dosimetry audit - Towards transferability of gamma index analysis between clinical trial QA groups. Radiother Oncol . 2017;125(3):398-404. https://doi.org/10.1016/j.radonc.2017.10.012

Chan MF, Witztum A, Valdes G. Integration of AI and Machine Learning in Radiotherapy QA. Front Artif Intell. 2020;3(September):1-8. https://doi.org/10.3389/frai.2020.577620

Li J, Wang L, Zhang X, et al. Machine Learning for Patient-Specific Quality Assurance of VMAT: Prediction and Classification Accuracy. Int J Radiat Oncol Biol Phys. 2019;105(4):893-902. https://doi.org/10.1016/j.ijrobp.2019.07.049

Valdes G, Scheuermann R, Hung CY, Olszanski A, Bellerive M, Solberg TD. A mathematical framework for virtual IMRT QA using machine learning. Med Phys. 2016;43(7):4323. https://doi.org/10.1118/1.4953835

Cilla S, Viola P, Romano C, et al. Prediction and classification of VMAT dosimetric accuracy using plan complexity and log-files analysis. Phys medica. 2022;103:76-88. https://doi.org/10.1016/j.ejmp.2022.10.004

Viola P, Romano C, Craus M, et al. Prediction of VMAT delivery accuracy using plan modulation complexity score and log-files analysis. Biomed Phys Eng Express. 2022;8(5):55020. https://doi.org/10.1088/2057-1976/ac82c6

Granville DA, Sutherland JG, Belec JG, Russa DJ La. Predicting VMAT patient-specific QA results using a support vector classifier trained on treatment plan characteristics and linac QC metrics. Phys Med Biol. 2019;64(January).

Interian Y, Rideout V, Kearney VP, et al. Deep nets vs expert designed features in medical physics: An IMRT QA case study. Med Phys. 2018;45(6):2672-2680. https://doi.org/10.1002/mp.12890

Tomori S, Kadoya N, Kajikawa T, et al. Systematic method for a deep learning-based prediction model for gamma evaluation in patient-specific quality assurance of volumetric modulated arc therapy. Med Phys. 2021;48(3):1003-1018. https://doi.org/10.1002/mp.14682

Lam D, Zhang X, Li H, et al. Predicting gamma passing rates for portal dosimetry-based IMRT QA using machine learning. Med Phys. 2019;46(10):4666-4675. https://doi.org/10.1002/mp.13752

Wang L, Li J, Zhang S, et al. Multi-task autoencoder based classification-regression model for patient-specific VMAT QA. Phys Med Biol. 2020;65(23):235023. https://doi.org/10.1088/1361-6560/abb31c

Hirashima H, Ono T, Nakamura M, et al. Improvement of prediction and classification performance for gamma passing rate by using plan complexity and dosiomics features. Radiother Oncol. 2020;153:250-257. https://doi.org/10.1016/j.radonc.2020.07.031

Huang Y, Pi Y, Ma K, et al. Virtual Patient-Specific Quality Assurance of IMRT Using UNet++: Classification, Gamma Passing Rates Prediction, and Dose Difference Prediction. Front Oncol. 2021;11. https://doi.org/10.3389/fonc.2021.700343

Lambri N, Hernandez V, Sáez J, et al. Multicentric evaluation of a machine learning model to streamline the radiotherapy patient specific quality assurance process. Phys medica. 2023;110:102593. https://doi.org/10.1016/j.ejmp.2023.102593

Qiu Z, Olberg S, den Hertog D, Ajdari A, Bortfeld T, Pursley J. Online adaptive planning methods for intensity-modulated radiotherapy. Phys Med Biol. 2023;68(10). https://doi.org/10.1088/1361-6560/accdb2

Carson ME, Molineu A, Taylor PA, Followill DS, Stingo FC, Kry SF. Examining credentialing criteria and poor performance indicators for IROC Houston’s anthropomorphic head and neck phantom. Med Phys. 2016;43(12):6491-6496. https://doi.org/10.1118/1.4967344

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2024-05-05

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Guía para el control de calidad y seguridad de los sistemas de planificación y planes de tratamiento de radioterapia externa. (2024). Revista De Física Médica, 25(1), 123-182. https://doi.org/10.37004/sefm/2024.25.1.008

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