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Identifying risk characteristics using failure mode and effect analysis for risk management in online magnetic resonance-guided adaptive radiation therapy

BACKGROUND AND PURPOSE: Online magnetic resonance-guided adaptive radiotherapy (MRgART) is a new technology of radiotherapy and requires a new quality control program in many aspects. This study aimed to gain a deeper understanding of risks in online MRgART through the application of failure mode an...

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Autores principales: Nishioka, Shie, Okamoto, Hiroyuki, Chiba, Takahito, Sakasai, Tatsuya, Okuma, Kae, Kuwahara, Junichi, Fujiyama, Daisuke, Nakamura, Satoshi, Iijima, Kotaro, Nakayama, Hiroki, Takemori, Mihiro, Tsunoda, Yuuki, Kaga, Keita, Igaki, Hiroshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9194450/
https://www.ncbi.nlm.nih.gov/pubmed/35712526
http://dx.doi.org/10.1016/j.phro.2022.06.002
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author Nishioka, Shie
Okamoto, Hiroyuki
Chiba, Takahito
Sakasai, Tatsuya
Okuma, Kae
Kuwahara, Junichi
Fujiyama, Daisuke
Nakamura, Satoshi
Iijima, Kotaro
Nakayama, Hiroki
Takemori, Mihiro
Tsunoda, Yuuki
Kaga, Keita
Igaki, Hiroshi
author_facet Nishioka, Shie
Okamoto, Hiroyuki
Chiba, Takahito
Sakasai, Tatsuya
Okuma, Kae
Kuwahara, Junichi
Fujiyama, Daisuke
Nakamura, Satoshi
Iijima, Kotaro
Nakayama, Hiroki
Takemori, Mihiro
Tsunoda, Yuuki
Kaga, Keita
Igaki, Hiroshi
author_sort Nishioka, Shie
collection PubMed
description BACKGROUND AND PURPOSE: Online magnetic resonance-guided adaptive radiotherapy (MRgART) is a new technology of radiotherapy and requires a new quality control program in many aspects. This study aimed to gain a deeper understanding of risks in online MRgART through the application of failure mode and effect analysis (FMEA) for more enhanced and effective quality assurance (QA) programs. MATERIALS AND METHODS: We present an FMEA conducted by a multidisciplinary team with more than two years of experience. A process map describing the whole process of online MRgART was developed and potential failure modes were identified. High-risk failure modes and their potential causes and corrective measures were also identified. Failure modes were classified into three categories, MRgRT, online ART, and conventional RT, to investigate their features. A comparison with previous studies was also conducted to gain a general perspective. RESULTS: In total, 153 failure modes and 49 high risks were identified. Among all failure modes, 51, 63, and 66 were related to MRgRT, online ART, and conventional RT, respectively. The hazardous processes were structure segmentation, treatment planning, and treatment beam delivery. Lists of failure modes identified in this study and previous studies were presented. Based on the results, characteristics and general aspects of the risks were discussed. CONCLUSION: Exploring the results of the FMEA enhanced our understanding of risk characteristics to improve QA program of online MRgART.
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spelling pubmed-91944502022-06-15 Identifying risk characteristics using failure mode and effect analysis for risk management in online magnetic resonance-guided adaptive radiation therapy Nishioka, Shie Okamoto, Hiroyuki Chiba, Takahito Sakasai, Tatsuya Okuma, Kae Kuwahara, Junichi Fujiyama, Daisuke Nakamura, Satoshi Iijima, Kotaro Nakayama, Hiroki Takemori, Mihiro Tsunoda, Yuuki Kaga, Keita Igaki, Hiroshi Phys Imaging Radiat Oncol Original Research Article BACKGROUND AND PURPOSE: Online magnetic resonance-guided adaptive radiotherapy (MRgART) is a new technology of radiotherapy and requires a new quality control program in many aspects. This study aimed to gain a deeper understanding of risks in online MRgART through the application of failure mode and effect analysis (FMEA) for more enhanced and effective quality assurance (QA) programs. MATERIALS AND METHODS: We present an FMEA conducted by a multidisciplinary team with more than two years of experience. A process map describing the whole process of online MRgART was developed and potential failure modes were identified. High-risk failure modes and their potential causes and corrective measures were also identified. Failure modes were classified into three categories, MRgRT, online ART, and conventional RT, to investigate their features. A comparison with previous studies was also conducted to gain a general perspective. RESULTS: In total, 153 failure modes and 49 high risks were identified. Among all failure modes, 51, 63, and 66 were related to MRgRT, online ART, and conventional RT, respectively. The hazardous processes were structure segmentation, treatment planning, and treatment beam delivery. Lists of failure modes identified in this study and previous studies were presented. Based on the results, characteristics and general aspects of the risks were discussed. CONCLUSION: Exploring the results of the FMEA enhanced our understanding of risk characteristics to improve QA program of online MRgART. Elsevier 2022-06-06 /pmc/articles/PMC9194450/ /pubmed/35712526 http://dx.doi.org/10.1016/j.phro.2022.06.002 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Research Article
Nishioka, Shie
Okamoto, Hiroyuki
Chiba, Takahito
Sakasai, Tatsuya
Okuma, Kae
Kuwahara, Junichi
Fujiyama, Daisuke
Nakamura, Satoshi
Iijima, Kotaro
Nakayama, Hiroki
Takemori, Mihiro
Tsunoda, Yuuki
Kaga, Keita
Igaki, Hiroshi
Identifying risk characteristics using failure mode and effect analysis for risk management in online magnetic resonance-guided adaptive radiation therapy
title Identifying risk characteristics using failure mode and effect analysis for risk management in online magnetic resonance-guided adaptive radiation therapy
title_full Identifying risk characteristics using failure mode and effect analysis for risk management in online magnetic resonance-guided adaptive radiation therapy
title_fullStr Identifying risk characteristics using failure mode and effect analysis for risk management in online magnetic resonance-guided adaptive radiation therapy
title_full_unstemmed Identifying risk characteristics using failure mode and effect analysis for risk management in online magnetic resonance-guided adaptive radiation therapy
title_short Identifying risk characteristics using failure mode and effect analysis for risk management in online magnetic resonance-guided adaptive radiation therapy
title_sort identifying risk characteristics using failure mode and effect analysis for risk management in online magnetic resonance-guided adaptive radiation therapy
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9194450/
https://www.ncbi.nlm.nih.gov/pubmed/35712526
http://dx.doi.org/10.1016/j.phro.2022.06.002
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