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Integration of an Independent Monitor Unit Check for High-Magnetic-Field MR-Guided Radiation Therapy System
PURPOSE: Commercial independent monitor unit (IMU) check systems for high-magnetic-field MR-guided radiation therapy (RT) systems are lacking. We investigated the feasibility of adopting an existing treatment planning system (TPS) as an IMU check for online adaptive radiotherapy using 1.5-Tesla MR-L...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963466/ https://www.ncbi.nlm.nih.gov/pubmed/35359395 http://dx.doi.org/10.3389/fonc.2022.747825 |
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author | Yang, Jie Zhang, Pengpeng Tyagi, Neelam Scripes, Paola Godoy Subashi, Ergys Liang, Jiayi Lovelock, Dale Mechalakos, James Li, Anyi Lim, Seng B. |
author_facet | Yang, Jie Zhang, Pengpeng Tyagi, Neelam Scripes, Paola Godoy Subashi, Ergys Liang, Jiayi Lovelock, Dale Mechalakos, James Li, Anyi Lim, Seng B. |
author_sort | Yang, Jie |
collection | PubMed |
description | PURPOSE: Commercial independent monitor unit (IMU) check systems for high-magnetic-field MR-guided radiation therapy (RT) systems are lacking. We investigated the feasibility of adopting an existing treatment planning system (TPS) as an IMU check for online adaptive radiotherapy using 1.5-Tesla MR-Linac. METHODS: The 7-MV flattening filter free (FFF) beam and multi-leaf collimator (MLC) models of a 1.5-T Elekta Unity MR-Linac within Monte Carlo-based Monaco TPS were used to generate an optimized beam model in Eclipse TPS. The MLC dosimetric leaf gap of the beam in Eclipse was determined by matching the dose distribution of Eclipse-generated intensity-modulated radiation therapy (IMRT) plans using the Analytical Anisotropic Algorithm (AAA) algorithm to Monaco plans. The plans were automatically adjusted for different source-to-axis distances (SADs) between the two systems. For IMU check, the treatment plans developed in Monaco were transferred to Eclipse to recalculate the dose using AAA. A plug-in within Eclipse was created to perform a 2D gamma analysis of the AAA and Monte Carlo dose distribution on a beam’s eye view parallel plane. Monaco dose distribution was shifted laterally by 2 mm during gamma analysis to account for the impact of magnetic field on electron trajectories. Eclipse doses for posterior beams were corrected for both the Unity couch and the posterior MR coil attenuation. Thirteen patients, each with 4–5 fractions for a variety of tumor sites (pancreas, rectum, and prostate), were tested. RESULTS: After thorough commissioning, the method was implemented as part of the standard clinical workflow. A total of 62 online plans, each with approximately 15 beams, were evaluated. The average per-beam gamma (3%/3 mm) pass rate for plans was 97.9% (range, 95.9% to 98.8%). The average pass rate per beam for all 932 beams used in these plans was 97.9% ± 1.9%, with the lowest per-beam gamma pass rate at 88.4%. The time for the process was within 3.2 ± 0.9 min. CONCLUSION: The use of a second planning system provides an efficient way to perform IMU checks with clinically acceptable accuracy for online adaptive plans on Unity MR-Linac. This is essential for meeting the safety requirements for second checks as outlined in American Association of Physicists in Medicine Task Group (AAPM TG) reports 114 and 219. |
format | Online Article Text |
id | pubmed-8963466 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89634662022-03-30 Integration of an Independent Monitor Unit Check for High-Magnetic-Field MR-Guided Radiation Therapy System Yang, Jie Zhang, Pengpeng Tyagi, Neelam Scripes, Paola Godoy Subashi, Ergys Liang, Jiayi Lovelock, Dale Mechalakos, James Li, Anyi Lim, Seng B. Front Oncol Oncology PURPOSE: Commercial independent monitor unit (IMU) check systems for high-magnetic-field MR-guided radiation therapy (RT) systems are lacking. We investigated the feasibility of adopting an existing treatment planning system (TPS) as an IMU check for online adaptive radiotherapy using 1.5-Tesla MR-Linac. METHODS: The 7-MV flattening filter free (FFF) beam and multi-leaf collimator (MLC) models of a 1.5-T Elekta Unity MR-Linac within Monte Carlo-based Monaco TPS were used to generate an optimized beam model in Eclipse TPS. The MLC dosimetric leaf gap of the beam in Eclipse was determined by matching the dose distribution of Eclipse-generated intensity-modulated radiation therapy (IMRT) plans using the Analytical Anisotropic Algorithm (AAA) algorithm to Monaco plans. The plans were automatically adjusted for different source-to-axis distances (SADs) between the two systems. For IMU check, the treatment plans developed in Monaco were transferred to Eclipse to recalculate the dose using AAA. A plug-in within Eclipse was created to perform a 2D gamma analysis of the AAA and Monte Carlo dose distribution on a beam’s eye view parallel plane. Monaco dose distribution was shifted laterally by 2 mm during gamma analysis to account for the impact of magnetic field on electron trajectories. Eclipse doses for posterior beams were corrected for both the Unity couch and the posterior MR coil attenuation. Thirteen patients, each with 4–5 fractions for a variety of tumor sites (pancreas, rectum, and prostate), were tested. RESULTS: After thorough commissioning, the method was implemented as part of the standard clinical workflow. A total of 62 online plans, each with approximately 15 beams, were evaluated. The average per-beam gamma (3%/3 mm) pass rate for plans was 97.9% (range, 95.9% to 98.8%). The average pass rate per beam for all 932 beams used in these plans was 97.9% ± 1.9%, with the lowest per-beam gamma pass rate at 88.4%. The time for the process was within 3.2 ± 0.9 min. CONCLUSION: The use of a second planning system provides an efficient way to perform IMU checks with clinically acceptable accuracy for online adaptive plans on Unity MR-Linac. This is essential for meeting the safety requirements for second checks as outlined in American Association of Physicists in Medicine Task Group (AAPM TG) reports 114 and 219. Frontiers Media S.A. 2022-03-11 /pmc/articles/PMC8963466/ /pubmed/35359395 http://dx.doi.org/10.3389/fonc.2022.747825 Text en Copyright © 2022 Yang, Zhang, Tyagi, Scripes, Subashi, Liang, Lovelock, Mechalakos, Li and Lim https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Yang, Jie Zhang, Pengpeng Tyagi, Neelam Scripes, Paola Godoy Subashi, Ergys Liang, Jiayi Lovelock, Dale Mechalakos, James Li, Anyi Lim, Seng B. Integration of an Independent Monitor Unit Check for High-Magnetic-Field MR-Guided Radiation Therapy System |
title | Integration of an Independent Monitor Unit Check for High-Magnetic-Field MR-Guided Radiation Therapy System |
title_full | Integration of an Independent Monitor Unit Check for High-Magnetic-Field MR-Guided Radiation Therapy System |
title_fullStr | Integration of an Independent Monitor Unit Check for High-Magnetic-Field MR-Guided Radiation Therapy System |
title_full_unstemmed | Integration of an Independent Monitor Unit Check for High-Magnetic-Field MR-Guided Radiation Therapy System |
title_short | Integration of an Independent Monitor Unit Check for High-Magnetic-Field MR-Guided Radiation Therapy System |
title_sort | integration of an independent monitor unit check for high-magnetic-field mr-guided radiation therapy system |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963466/ https://www.ncbi.nlm.nih.gov/pubmed/35359395 http://dx.doi.org/10.3389/fonc.2022.747825 |
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