| Deng Juan,Liu Gaoyuan,Yin Chuou,et al.Patient-specific quality assurance for non-normal radiotherapy plans based on statistical process control[J].Chinese Journal of Radiological Medicine and Protection,2025,45(4):296-301 |
| Patient-specific quality assurance for non-normal radiotherapy plans based on statistical process control |
| Received:March 04, 2024 |
| DOI：10.3760/cma.j.cn112271-20240304-00083 |
| KeyWords:Radiotherapy Statistical process control Non-normal distribution Patient-specific quality assurance |
| FundProject:国家自然科学基金(12275012,12475309,12411530076,82202941);北京市自然科学基金(Z210008);中央高校基本科研业务费/北京大学临床医学+X 青年专项(PKU2024LCXQ033);国家重点研发计划(2019YFF01014405);教育部内地与港澳高等学校师生交流计划项目(万人计划7111400049);中国国际人才交流基金会国际青年人才来华交流项目(JC202502001F) |
| Author Name | Affiliation | E-mail | | Deng Juan | Department of Oncology, Deyang People's Hospital, Deyang 618000, China | | | Liu Gaoyuan | Department of Oncology, Deyang People's Hospital, Deyang 618000, China | | | Yin Chuou | Department of Oncology, Deyang People's Hospital, Deyang 618000, China | | | Liu Jiang | Department of Oncology, Deyang People's Hospital, Deyang 618000, China | | | Mei Guojian | Department of Oncology, Deyang People's Hospital, Deyang 618000, China | | | Hua Ling | Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142 China | | | Yu Shutong | Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142 China | | | Fu Xinhui | Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142 China | | | Lin Chen | State Key Laboratory of Nuclear Physics and Nuclear Technology, Institute of Heavy Ion Physics, Peking University, Beijing 100871, China | | | Li Tian | Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hong Kong 999077, China | | | Zhang Yibao | Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142 China | zhangyibao@pku.edu.cn |
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| Abstract:: |
| Objective To apply statistical process control (SPC) techniques to the quality assurance of non-normal radiotherapy plans through Johnson transformation, establishing patient-specific tolerance and action limits based on treatment sites and dose/distance assessment criteria, thereby enhancing the intensity-modulated radiation therapy (IMRT) verification accuracy and dose delivery precision. Methods In this study, 951 gamma analysis data of patient-specific quality assurance (PSQA) executed on the Halcyon accelerator platform were selected and categorized into six groups based on treatment sites, including brain (102 cases), head and neck (100 cases), breast (229 cases), lung (154 cases), esophagus (223 cases), and pelvic (143 cases) groups. The six groups of data were statistically analyzed through Anderson-Darling normality tests (α = 0.05) using Minitab 21 software. Non-normal data were transformed into normal data through Johnson transformation and then were used to establish treatment site-specific tolerance and action limits, which were compared with the Shewhart control charts based on normal distributions. Results The PSQA result of the six groups all exhibited non-normal distributions (P <0.05). Through Johnson transformation, the tolerance and action limits for the head and neck, breast, lung, esophagus, and pelvic areas under the 3%/2 mm criterion ranged from 95.13% to 96.16% and 94.19% to 95.91%, respectively. In contrast, the tolerance and action limits ranged from 91.15% to 94.86% and 89.94% to 94.78% under the 2%/2 mm criterion. Directly applying Shewhart control charts without normality assumptions yielded higher tolerance limits compared to the application of Johnson transformation, increasing the false positive rate in the non-normal PSQA process. Conclusions Applying the SPC techniques directly to a non-normal process can lead to an increased false alarm rate and wrong process interpretation. The SPC techniques combined with Johnson transformation enable more effective monitoring of a non-normal PSQA process, facilitating timely identification of potential factors that may lead to an out-of-control process based on the treatment site-specific limits. |
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