Optimization of Geometric Components of Agility Multileaf to Improve Dose Delivery Accuracy

Authors

  • M.Sc Camila Trindade de Oliveira Nuclear Energy Research Institute image/svg+xml
    • Dra Maria da Penha Albuquerque Potiens Nuclear Energy Research Institute image/svg+xml

      DOI:

      https://doi.org/10.15392/2319-0612.2026.2985

      Keywords:

      Multileaf Collimators 1, Monaco 2, Modeling 3, Agility 4

      Abstract

      The Agility Multileaf Collimator (MLC) exhibits specific machining characteristics. These unique features, together with minor installation differences among various linear accelerators, produce dosimetric effects that are not accounted for by the Monaco Treatment Planning System (TPS). To address this, the manufacturer recommends that users perform post-modeling adjustments to better characterize the MLC according to the actual configuration of the clinical linear accelerator. Evidence in the literature indicates that, in techniques modulated by dynamic MLC motion, geometric positioning errors as small as 1 mm can result in dose delivery errors of 10% or more. Therefore, it is of great importance to study the behavior of the geometric factors of the MLC leaves through the concepts applied in radiation metrology. However, despite the widespread clinical use of Monaco, there is still limited literature with comprehensive information, which makes the work of medical physicists more challenging. Thus, the objectives of this study were to analyze the geometric components of the Agility MLC and to propose an efficient methodology for post-modeling—or fine-tuning—these components so that the calculated dose in the TPS is as close as possible to the dose delivered by the linear accelerator. The results showed that, with the post-modeling, for the same evaluation criteria, the calculated doses for the ExpressQA tests, TG-119 tests, and patient-specific cases were in closer agreement with the doses delivered by the linear accelerator in all situations. For the 7SegA and DMLCi fields the improvements in gamma pass rates were more than 10%. These results enable greater efficiency in dose delivery, leading to improved tumor control and reduced patient toxicity.

       

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      Author Biographies

      • M.Sc Camila Trindade de Oliveira, Nuclear Energy Research Institute

        Bachelor in Medical Physics from the Federal University of Sergipe (2010). Radiological protection supervisor in Radiotherapy by the National Nuclear Energy Commission (2013). Specialist in Medical Physics applied to Radiotherapy from the Faculty of Medicine of USP - FMUSP (2015). Master in Nuclear Technology from the Institute of Energy and Nuclear Research IPEN/CNEN - USP (2015). Medical Physics at Caruaru Oncology Center (2015-2015). Medical Physics at Hospital Sociedade Portuguesa de Beneficência de Santos (2016-2017). Coordinator of Medical Physics and Supervisor in Radiological Protection at CLINRADI (2017 to date). PhD student in Nuclear Technology at the Institute of Energy and Nuclear Research IPEN/CNEN - USP (2021 to date).

      • Dra Maria da Penha Albuquerque Potiens, Nuclear Energy Research Institute

        Graduated in Science, Bachelor in Physics - Faculdades Oswaldo Cruz (1984), Master's degree in Nuclear Technology from the University of São Paulo (1989) and PhD in Nuclear Technology from the University of São Paulo (1999). He is currently a full technologist III at the National Nuclear Energy Commission, being Technical Responsible for the Instrument Calibration Laboratory and Manager of the Radiation Metrology Center at IPEN -CNEN/SP.  He has experience in the area of Nuclear Engineering, with an emphasis on metrology of ionizing radiation. The main activity is linked to the development and updating of calibration and quality control methods for instrumentation used in procedures involving the measurement of ionizing radiation in the area of radiodiagnosis, radioprotection, radiotherapy and nuclear medicine. Master's and doctorate advisor for the Nuclear Technology (Applications) program at the University of São Paulo USP).

      References

      [1] Lee, J.; Choi, K.; Hong, S.; et al. Effects of static dosimetric leaf gap on MLC-based small-beam dose distribution for intensity-modulated radiosurgery. Journal of Applied Clinical Medical Physics, Hanguk-AB, vol. 8, n. 4, p. 54-64, 2007. DOI: https://doi.org/10.1120/jacmp.v8i4.2397

      [2] Snyder, M.; Halford, R.; Knill, C.; et al. Modeling the Agility MLC in the Monaco treatment planning system. Journal of Applied Clinical Medical Physics, Detroit-USA, v.17, n. 3, p.190-202, 2016. DOI: https://doi.org/10.1120/jacmp.v17i3.6044

      [3] Roche, M.; Crane, R.; Powers, M. and Crabtree, T. Agility MLC Transmission Optimization in the Monaco Treatment Planning System. Journal of Applied Clinical Medical Physics, Quuenslândia-AU, v.19, n. 5, p.473-482, 2018. DOI: https://doi.org/10.1002/acm2.12399

      [4] Elekta Medical Systems Inc. Monaco Post Modeling Adjustment of MLC Parameters. Document ID: LRMMON0003. 2013.

      [5] Katlapa, A. Post-modeling Agility MLC model in Monaco Treatment Planning System Using Different 2D Detectors. Master’s Degree Program in Medical Physics, Finland, 2023.

      [6] Elekta Medical Systems Inc., Monaco Technical Reference Post Modeling Adjustment of MLC Parameters. 2012.

      [7] Kry, S. F.; Molineau, A.; Kerns, J. R.; et.al. Institutional Patient-Specific IMRT QA does not Predict Unacceptable Plan Delivery. International Journal of Radiation Oncology, Biology, Physics. Texas-USA, v. 90, n. 5, p. 1195-201, 2014. DOI: https://doi.org/10.1016/j.ijrobp.2014.08.334

      [8] Khalid, E. O.; Mustapha, Z.; Yassine, H.; Raoui, Y. and Pandey, V. P. Validation of monaco TPS for an ELEKTA synergy MLCi2: Using gamma index for eElekta full package beams," Materials Today: Proceedings. Elsevier. Oujda- Morocco, vol. 45, p. 7685-7689, 2021. DOI: https://doi.org/10.1016/j.matpr.2021.03.180

      [9] Muñoz, L., McLoone, P., Metcalfe, P., Rosenfeld, A. B., & Biasi, G. Evaluating Monaco 6.2.2 in complex radiotherapy across matched LINACs: improved MLC modelling and dose accuracy with virtual source model 2.0. Physical and Engineering Sciences in Medicine. 2025. DOI: https://doi.org/10.1007/s13246-025-01602-5

      [10] Hernandez, V., Angerud, A., Bogaert, E., Hussein, M., Lemire, M., García-Miguel, J., Saez, J. Challenges in Modeling the Agility Multileaf Collimator in Treatment Planning Systems and Current Needs for Improvement. Medical Physics, vol. 49, n. 12, p. 7404-7416, Dec. 2022. DOI: https://doi.org/10.1002/mp.16016

      [11] Elekta Medical Systems Inc. Monaco Physics Training MLC Geometry Parameters. Power Point. Document ID: 20211129. 2021.

      [12] Wang, C.; Zhu, X.; Hong, J. C.; Zheng, D. Special Collection on Artificial Intelligence Based Treatment Planning for Radiotherapy–Review Artificial Intelligence in Radiotherapy Treatment Planning: Present and future. Technology in Cancer Research & Treatment, vol. 18, p. 1-11, sept. 8, 2019. DOI: https://doi.org/10.1177/1533033819873922

      [13] Mzenda, B.; Mugabe, K. V.; Sims, R.; Godwin, G.; Loria, D. Modeling and dosimetric performance evaluation of the Ray Station treatment planning system. Journal of Applied Clinical Medical Physics. vol. 8; 15, n. 5, 08 Sept. 2014. DOI: 10.1120/jacmp.v15i5.4787. DOI: https://doi.org/10.1120/jacmp.v15i5.4787

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      Published

      2026-07-10

      Issue

      Vol. 14 No. 3 (2026)

      Section

      Original Articles

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      Copyright (c) 2026 M.Sc Camila Trindade de Oliveira, Dra Maria da Penha Albuquerque Potiens

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