Statistical process control and process capability analysis for non‐normal volumetric modulated arc therapy patient‐specific quality assurance processes

Xiao, Qing; Bai, Song; Li, Guangjun; Yang, Kaixuan; Bai, Long; Li, Zhibin; Chen, Li; Xian, Lixun; Hu, Zhenyao; Xiang, Zhongyuan

doi:10.1002/mp.14399

Cited by 21 publications

(35 citation statements)

References 36 publications

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“…Previous studies have also found that PSQA processes are not normally distributed. 3,7,16,17,24,25 It was further found that, for a given linac, the optimal distribution models of GPRs varied by treatment site and gamma analysis criterion. There were also some inter-linac differences in the distributions of GPRs at the same treatment sites.…”

Section: F I G U R Ementioning

confidence: 98%

A robust approach to establish tolerance limits for the gamma passing rate‐based patient‐specific quality assurance using the heuristic control charts

Xiao

Bai

et al. 2021

Medical Physics

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Establishing the tolerance limits of patient-specific quality assurance (PSQA) processes based on the gamma passing rate (GPR) by using normal statistical process control (SPC) methods involves certain problems. The aim of this study was threefold: (a) to show that the heuristic SPC method can replace the quantile method for establishing tolerance limits in PSQA processes and is more robust, (b) to introduce an iterative procedure of "Identify-Eliminate-Recalculate" for establishing the tolerance limits in PSQA processes with unknown states based on retrospective GPRs, and (c) to recommend a workflow to define tolerance limits based on actual clinical retrospective GPRs. Materials and Methods: A total of 1671 volumetric-modulated arc therapy (VMAT) pretreatment plans were measured on four linear accelerators (linacs) and analyzed by treatment sites using the GPRs under the 2%/2 mm, 3%/2 mm, and 3%/3 mm criteria. Normality testing was performed using the Anderson-Darling (AD) statistic and the optimal distributions of GPRs were determined using the Fitter Python package. The iterative "Identify-Eliminate-Recalculate" procedure was used to identify the PSQA outliers. The tolerance limits of the initial PSQAs, remaining PSQAs after elimination, and in-control PSQAs after correction were calculated using the conventional Shewhart method, two transformation methods, three heuristic methods, and two quantile methods. The tolerance limits of PSQA processes with different states for the respective methods, linacs, and treatment sites were comprehensively compared and analyzed. Results: It was found that 75% of the initial PSQA processes and 63% of the in-control processes were non-normal (AD test, p < 0.05). The optimal distributions of GPRs for the initial and in-control PSQAs varied with different linacs and treatment sites. In the implementation of the "Identify-Eliminate-Recalculate" procedure, the quantile methods could not identify the out-of -control PSQAs effectively due to the influence of outliers. The tolerance limits of the in-control PSQAs, calculated using the quantile of optimal fitting distributions, represented the ground truth. The tolerance limits of the in-control PSQAs and remaining PSQAs after elimination calculated using the heuristic methods were considerably close to the ground truth (the maximum average absolute deviations were 0.50 and 1.03%, respectively). Some transformation failures occurred under both transformation methods. For the in-control PSQAs at 3%/2 mm gamma criteria, the maximum differences in the tolerance limits for four linacs and different treatment sites were 3.10 and 5.02%, respectively.

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Section: F I G U R Ementioning

confidence: 98%

A robust approach to establish tolerance limits for the gamma passing rate‐based patient‐specific quality assurance using the heuristic control charts

Xiao

Bai

et al. 2021

Medical Physics

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“…(). One of the most commonly used methods to empirically and automatically identify an appropriate transformation to apply on a skewed variable is the Box‐Cox transformation 7 . The Box‐Cox transformation for a positive response variable indexed by an unknown parameter

λ

is given as

y (λ) = \{\begin{matrix} \frac{y^{λ} ‐ 1}{λ}, & i f λ \neq 0 \\ \log y, & i f λ = 0 \end{matrix}),

where the optimal value of

λ

is computed by the maximum likelihood estimation.…”

Section: Methodsmentioning

confidence: 99%

“…5 In the clinic, quality control tools have been recommended for intensity-modulated radiation therapy (IMRT) quality assurance (QA) by the American Association of Physicists in Medicine Task Group 218. 6,7 However, quality control for plan evaluation has been restricted by the limited availability of tools capable of analyzing patient data and efficiently producing visualizations from a large batch of patient files. The most recent and commonly used state-of-the-art method that utilizes anatomical data from existing patients to estimate plan quality and makes planning decisions is referred to as knowledge-based planning (KBP).…”

Section: Introductionmentioning

confidence: 99%

“…In the clinic, quality control tools have been recommended for intensity‐modulated radiation therapy (IMRT) quality assurance (QA) by the American Association of Physicists in Medicine Task Group 218 6,7 . However, quality control for plan evaluation has been restricted by the limited availability of tools capable of analyzing patient data and efficiently producing visualizations from a large batch of patient files.…”

Section: Introductionmentioning

confidence: 99%

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Treatment plan quality control using multivariate control charts

et al. 2021

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Statistical process control tools such as control charts were recommended by the American Association of Physicists in Medicine (AAPM) Task Group 218 for radiotherapy quality assurance. However, the tools needed to analyze multivariate, correlated data that are often encountered in treatment plan quality measures, are lacking. In this study, we develop quality control tools that can model multivariate plan quality measures with correlations and account for patient-specific risk factors, without adding a significant burden to clinical workflow. Methods and Materials: A multivariate, quality control chart is developed that includes a risk-adjustment model, Hotelling's T 2 statistic, and principal component analysis (PCA). Principal component analysis accounts for correlations among a set of organ-at-risk (OAR) dose-volume histogram (DVH) points that serves as proxies for plan quality. Risk-adjustment models estimate the principal components from PCA using a set of patient-and treatment-specific risk factors. The resulting residuals from the risk-adjustment models are used to compute the Hotelling's T 2 statistic; the corresponding multivariate control chart is then plotted based on the beta distribution followed by the statistic. Further, the box-cox transformation is used to account for non-normality in DVH points. We investigate the application of the proposed methodology via three multivariate control chartsa conventional chart that ignores risk-adjustment and PCA, a risk-adjusted chart ignoring PCA, and a PCA-based, risk-adjusted chart. These control charts are evaluated on 69 head-and-neck cases. Results: The conventional multivariate control chart fails to account for important patient-specific risk factors, including volumes and cross-sectional areas of the tumor and OARs and distances in-between. This failure leads to a larger number of false alarms. While the multivariate risk-adjusted control chart is able to reduce false alarms, it fails to account for correlations in DVH points. The multivariate PCA-based, risk-adjusted control chart can detect unusual plans after accounting for the correlations. By replanning, improvements are shown on an unusual plan identified by both risk-adjusted methods. Conclusions: The multivariate risk-adjusted control chart developed here enables quality control of plans prior to delivery. This methodology is generic and can be readily applied for other radiotherapy quality assurance protocols, such as gamma analysis pass rates.

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“…The top three subspecialties are radiation imaging (218 papers), radiation therapy (70 papers), and magnetic resonance (42 papers). Within the subspecialty of radiation therapy, the number of publications are 15 papers in the field of clinical implementation [41][42][43][44][45][46][47][48][49][50][51][52][53][54][55], 11 papers in the field of plan optimization [56][57][58][59][60][61][62][63][64][65][66], 14 papers in the field of plan evaluation [67][68][69][70][71][72][73][74][75][76][77][78][79][80], and 12 papers in the field of quality assurance [81][82][83][84][85][86][87][88]…”

Section: Scientific Researchmentioning

confidence: 99%

The status of medical physics in radiotherapy in China

Yan

Huang

et al. 2021

Physica Medica

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To present an overview of the status of medical physics in radiotherapy in China, including facilities and devices, occupation, education, research, etc. Materials and methods: The information about medical physics in clinics was obtained from the 9-th nationwide survey conducted by the China Society for Radiation Oncology in 2019. The data of medical physics in education and research was collected from the publications of the official and professional organizations. Results: By 2019, there were 1463 hospitals or institutes registered to practice radiotherapy and the number of accelerators per million population was 1.5. There were 4172 medical physicists working in clinics of radiation oncology. The ratio between the numbers of radiation oncologists and medical physicists is 3.51. Approximately, 95% of medical physicists have an undergraduate or graduate degrees in nuclear physics and biomedical engineering. 86% of medical physicists have certificates issued by the Chinese Society of Medical Physics. There has been a fast growth of publications by authors from mainland of China in the top international medical physics and radiotherapy journals since 2018. Conclusions: Demand for medical physicists in radiotherapy increased quickly in the past decade. The distribution of radiotherapy facilities in China became more balanced. High quality continuing education and training programs for medical physicists are deficient in most areas. The role of medical physicists in the clinic has not been clearly defined and their contributions have not been fully recognized by the community.Prof. Xu Haichao in 1940s at Peking Union Medical College (PUMC). He worked with Prof. Marvin Williomus, an American medical physicist, to treat cancer patients using a 400 kV X-ray unit [7]. The department of radiology in Caner Institute of Chinese Academy of Medical Sciences (CICAMS) started to treat patients with a Cobalt-60 unit in 1958. At the same year, the division of radiation physics in CICAMS was founded. They made the manual multi-leaf collimator and installed it on Cobalt-60 machine in 1965. Later, they made the remote control system for brachytherapy machine using Cobalt-60 source ball in 1965Cobalt-60 source ball in -1967.From 1970, China began to build linear accelerators and on-board imaging devices. As a result, 25 MeV Betatron, Simulator and Cobalt-60 brachytherapy machine were produced by Tianjing therapeutic instrument factory [9]. Meanwhile, Beijing Medical Apparatus and Instruments Institute built the first linear accelerator [10]. Since 1976, the major hospitals started to purchase high-end linear accelerators, CT, Brachytron and planning software from USA and Europe [11]. Following the clinical application of the linear accelerators, text books in Chinese

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Statistical process control and process capability analysis for non‐normal volumetric modulated arc therapy patient‐specific quality assurance processes

Cited by 21 publications

References 36 publications

A robust approach to establish tolerance limits for the gamma passing rate‐based patient‐specific quality assurance using the heuristic control charts

A robust approach to establish tolerance limits for the gamma passing rate‐based patient‐specific quality assurance using the heuristic control charts

Treatment plan quality control using multivariate control charts

The status of medical physics in radiotherapy in China

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