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Russo S, Saez J, Esposito M, Bruschi A, Ghirelli A, Pini S, Scoccianti S, Hernandez V. Incorporating plan complexity into the statistical process control of volumetric modulated arc therapy pre-treatment verifications. Med Phys 2024; 51:3961-3971. [PMID: 38630979 DOI: 10.1002/mp.17081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 03/14/2024] [Accepted: 03/30/2024] [Indexed: 04/19/2024] Open
Abstract
BACKGROUND Statistical process control (SPC) is a powerful statistical tool for process monitoring that has been highly recommended in healthcare applications, including radiation therapy quality assurance (QA). The AAPM TG-218 report described the clinical implementation of SPC for Volumetric Modulated Arc Therapy (VMAT) pre-treatment verifications, pointing out the need to adjust tolerance limits based on plan complexity. However, the quantification of plan complexity and its integration into SPC remains an unresolved challenge. PURPOSE The primary aim of this study is to investigate the incorporation of plan complexity into the SPC framework for VMAT pre-treatment verifications. The study explores and evaluates various strategies for this incorporation, discussing their merits and limitations, and provides recommendations for clinical application. METHODS A retrospective analysis was conducted on 309 VMAT plans from diverse anatomical sites using the PTW OCTAVIUS 4D device for QA measurements. Gamma Passing Rates (GPR) were obtained, and lower control limits were computed using both the conventional Shewhart method and three heuristic methods (scaled weighted variance, weighted standard deviations, and skewness correction) to accommodate non-normal data distributions. The 'Identify-Eliminate-Recalculate' method was employed for robust analysis. Eight complexity metrics were analyzed and two distinct strategies for incorporating plan complexity into SPC were assessed. The first strategy focused on establishing control limits for different treatment sites, while the second was based on the determination of control limits as a function of individual plan complexity. The study extensively examines the correlation between control limits and plan complexity and assesses the impact of complexity metrics on the control process. RESULTS The control limits established using SPC were strongly influenced by the complexity of treatment plans. In the first strategy, a clear correlation was found between control limits and average plan complexity for each site. The second approach derived control limits based on individual plan complexity metrics, enabling tailored tolerance limits. In both strategies, tolerance limits inversely correlated with plan complexity, resulting in all highly complex plans being classified as in control. In contrast, when plans were collectively analyzed without considering complexity, all the out-of-control plans were highly complex. CONCLUSIONS Incorporating plan complexity into SPC for VMAT verifications requires meticulous and comprehensive analysis. To ensure overall process control, we advocate for stringent control and minimization of plan complexity during treatment planning, especially when control limits are adjusted based on plan complexity.
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Affiliation(s)
- Serenella Russo
- Medical Physics Unit, Azienda USL Toscana Centro, Florence, Italy
| | - Jordi Saez
- Department of Radiation Oncology, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Marco Esposito
- Medical Physics Unit, Azienda USL Toscana Centro, Florence, Italy
- Medical Physics Program, The Abdus Salam International Centre for Theoretical Physics Trieste-Italy, Trieste, Italy
| | - Andrea Bruschi
- Medical Physics Unit, Azienda USL Toscana Centro, Florence, Italy
| | | | - Silvia Pini
- Medical Physics Unit, Azienda USL Toscana Centro, Florence, Italy
| | | | - Victor Hernandez
- Department of Medical Physics, Hospital Sant Joan de Reus, IISPV, Reus, Spain
- Universitat Rovira i Virgili (URV), Tarragona, Spain
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Xiao Q, Li G. Application and Challenges of Statistical Process Control in Radiation Therapy Quality Assurance. Int J Radiat Oncol Biol Phys 2024; 118:295-305. [PMID: 37604239 DOI: 10.1016/j.ijrobp.2023.08.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 07/21/2023] [Accepted: 08/08/2023] [Indexed: 08/23/2023]
Abstract
Quality assurance (QA) is important for ensuring precision in radiation therapy. The complexity and resource-intensive nature of QA has increased with the continual evolution of equipment and techniques. An effective approach is to improve the process control technology and resource optimization. Statistical process control is an economical and efficient tool that has been widely used to monitor, control, and improve quality management processes and is now being increasingly used for radiation therapy QA. This article reviews the development and methodology of statistical process control technology, evaluates its suitability in radiation therapy QA practices, and assesses its importance and challenges in optimizing radiation therapy QA processes.
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Affiliation(s)
- Qing Xiao
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Guangjun Li
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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Raveendran V, R GR, P T A, Bhasi S, C P R, Kinhikar RA. Moving towards process-based radiotherapy quality assurance using statistical process control. Phys Med 2023; 112:102651. [PMID: 37562233 DOI: 10.1016/j.ejmp.2023.102651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 07/16/2023] [Accepted: 08/01/2023] [Indexed: 08/12/2023] Open
Abstract
Monitoring Radiotherapy Quality Assurance (QA) using Statistical Process Control (SPC) methods has gained wide acceptance. The significance of understanding the SPC methodologies has increased among the medical physics community with the release of Task Group (TG) reports from the American Association of Physicists in Medicine (AAPM) on patient-specific QA (PSQA) (TG-218) and Proton therapy QA (TG-224). Even though these reports recommend using SPC for QA analysis, physicists have ambiguities and doubts in choosing proper SPC tools and methodologies. This review article summarises the utilisation of SPC methods for different Radiotherapy QAs published in the literature, such as PSQA, routine Linac QA and patient positional verification. QA analysis using SPC could assist the user in distinguishing between 'special' and 'routine' sources of variations in the QA, which can aid in reducing actions on false positive QA results. For improved PSQA monitoring, machine-specific, site-specific, and technique-specific Tolerance Limits and Action Limits derived from a two-stage SPC-based approach can be used. Adopting a combination of Shewhart's control charts and time-weighted control charts for routine Linac QA monitoring could add more insights to the QA process. Incorporating SPC tools into existing image review modules or introducing new SPC software packages specifically designed for clinical use can significantly enhance the image review process. Proper selection and having adequate knowledge of SPC tools are essential for efficient QA monitoring, which is a function of the type of QA data available, and the magnitude of process drift to be monitored.
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Affiliation(s)
- Vysakh Raveendran
- Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer, Tata Memorial Centre, Homi Bhabha National Institute, Navi Mumbai, Maharashtra, India.; Department of Physics, Noorul Islam Centre for Higher Education, Kumaracoil, Kanyakumari District, Tamil Nadu, India..
| | - Ganapathi Raman R
- Department of Physics, Saveetha Engineering College (Autonomous), Chennai, Tamil Nadu, India
| | - Anjana P T
- Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer, Tata Memorial Centre, Homi Bhabha National Institute, Navi Mumbai, Maharashtra, India
| | - Saju Bhasi
- Division of Radiation Physics, Regional Cancer Centre, Trivandrum, India
| | - Ranjith C P
- Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer, Tata Memorial Centre, Homi Bhabha National Institute, Navi Mumbai, Maharashtra, India
| | - Rajesh Ashok Kinhikar
- Department of Medical Physics, Tata Memorial Centre, Homi Bhabha National Institute Parel, Mumbai, India
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Li G, Xiao Q, Dai G, Wang Q, Bai L, Zhang X, Zhang X, Duan L, Zhong R, Bai S. Guaranteed performance of individual control chart used in gamma passing rate-based patient-specific quality assurance. Phys Med 2023; 109:102581. [PMID: 37084678 DOI: 10.1016/j.ejmp.2023.102581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 03/20/2023] [Accepted: 04/06/2023] [Indexed: 04/23/2023] Open
Abstract
PURPOSE To assess the effect of sampling variability on the performance of individual charts (I-charts) for PSQA and provide a robust and reliable method for unknown PSQA processes. MATERIALS AND METHODS A total of 1327 pretreatment PSQAs were analyzed. Different datasets with samples in the range of 20-1000 were used to estimate the lower control limit (LCL). Based on the iterative "Identify-Eliminate-Recalculate" and direct calculation without any outlier filtering procedures, five I-charts methods, namely the Shewhart, quantile, scaled weighted variance (SWV), weighted standard deviation (WSD), and skewness correction (SC) method, were used to compute the LCL. The average run length (ARL0) and false alarm rate (FAR0) were calculated to evaluate the performance of LCL. RESULTS The ground truth of the values of LCL, FAR0, and ARL0 obtained via in-control PSQAs were 92.31%, 0.135%, and 740.7, respectively. Further, for in-control PSQAs, the width of the 95% confidence interval of LCL values for all methods tended to decrease with the increase in sample size. In all sample ranges of in-control PSQAs, only the median LCL and ARL0 values obtained via WSD and SWV methods were close to the ground truth. For the actual unknown PSQAs, based on the "Identify-Eliminate-Recalculate" procedure, only the median LCL values obtained by the WSD method were closest to the ground truth. CONCLUSIONS Sampling variability seriously affected the I-chart performance in PSQA processes, particularly for small samples. For unknown PSQAs, the WSD method based on the implementation of the iterative "Identify-Eliminate-Recalculate" procedure exhibited sufficient robustness and reliability.
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Affiliation(s)
- Guangjun Li
- Radiotherapy Physics & Technology Center, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Qing Xiao
- Radiotherapy Physics & Technology Center, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Guyu Dai
- Radiotherapy Physics & Technology Center, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Qiang Wang
- Radiotherapy Physics & Technology Center, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Long Bai
- Radiotherapy Physics & Technology Center, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xiangbin Zhang
- Radiotherapy Physics & Technology Center, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xiangyu Zhang
- Radiotherapy Physics & Technology Center, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Lian Duan
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia 19104, United States
| | - Renming Zhong
- Radiotherapy Physics & Technology Center, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Sen Bai
- Radiotherapy Physics & Technology Center, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China; Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
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Simpson-Page E, Coogan P, Kron T, Lowther N, Murray R, Noble C, Smith I, Wilks R, Crowe SB. Webinar and survey on quality management principles within the Australian and New Zealand ACPSEM Workforce. Phys Eng Sci Med 2022; 45:679-685. [PMID: 35834171 DOI: 10.1007/s13246-022-01160-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Healthcare relies upon the accurate and safe delivery of patient care. This is only achievable when systems are developed to ensure high quality, robust outcomes, for instance quality management systems. The concept of quality management can take on a different meaning depending on the context in which it is found. To add complication, the amount of education required for quality management will vary depending on one's exposure to the implementation of quality systems. In part to address these issues, the Australasian College of Physical Scientists and Engineers in Medicine (ACPSEM) Queensland Branch held a quality management webinar for members and non-members across Australia and New Zealand. The purpose of the webinar was to educate and facilitate discussion regarding the application of quality management principles for the ACPSEM profession. In conjunction, a pre- and post-webinar survey was conducted to gain an insight into existing knowledge and attitudes within the professions governed by the ACPSEM and students undertaking related studies. This paper authored by the webinar speakers reintroduces the quality management principles that were discussed in webinar, exemplifies the importance of quality management skills within the ACPSEM professions and presents the results of the surveys, promoting the need for more educational resources on quality management tools.
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Affiliation(s)
- Emily Simpson-Page
- Cancer Care Services, Royal Brisbane and Women's Hospital, Brisbane, Australia.
| | - Paul Coogan
- Q-TRaCE, Department of Nuclear Medicine & Specialised PET Services Queensland, Royal Brisbane and Women's Hospital, Brisbane, Australia
| | - Tomas Kron
- Physical Sciences Department, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Nicholas Lowther
- Wellington Blood & Cancer Centre, Wellington Hospital, Wellington, New Zealand
| | - Rebecca Murray
- Herston Biofabrication Institute, Metro North Hospital and Health Service, Brisbane, Australia
| | - Christopher Noble
- Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane, Australia
| | - Ian Smith
- St. Andrews War Memorial Hospital, Brisbane, Australia
| | - Rachael Wilks
- Cancer Care Services, Royal Brisbane and Women's Hospital, Brisbane, Australia.,Herston Biofabrication Institute, Metro North Hospital and Health Service, Brisbane, Australia.,School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Scott B Crowe
- Cancer Care Services, Royal Brisbane and Women's Hospital, Brisbane, Australia.,Herston Biofabrication Institute, Metro North Hospital and Health Service, Brisbane, Australia.,School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia.,School of Chemistry and Physics, Queensland University of Technology, Brisbane, Australia
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