Performance assessment of surface-guided radiation therapy and patient setup in head-and-neck and breast cancer patients based on statistical process control |
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| Institution: | 1. Department of Radiation Oncology, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China;2. Department of Oncology, The Affiliated Hospital of Panzhihua University, Panzhihua, China;1. Servicio de Radiofísica y Protección Radiológica, Consorcio Hospitalario Provincial de Castellón, Avda. Dr. Clará 19, Castellón de la Plana 12002, Castellón, Spain;2. Fundación Hospital Provincial de Castellón, Avda. Dr. Clará 19, Castellón de la Plana 12002, Castellón, Spain;3. Servicio de Oncología Radioterápica, Consorcio Hospitalario Provincial de Castellón, Avda. Dr. Clará 19, Castellón de la Plana 12002, Castellón, Spain;4. Facultad de Medicina, Universidad Cardenal Herrera-CEU, C/ Grecia 31, Castellón de la Plana 12006, Castellón, Spain;1. Department of Radiation Oncology, University of Washington, Seattle, WA, United States;2. Department of Radiation Oncology, Seattle Cancer Care Alliance, Seattle, WA, United States;1. Wellington Blood and Cancer Centre, Department of Radiation Oncology, Wellington, New Zealand;2. University of Otago, Department of Radiation Therapy, Wellington, New Zealand;1. Department of Radiotherapy Center, Shanxi Provincial Cancer Hospital, No. 3 of Zhigongxinjie Street, Xinghualing District, Taiyuan, 030000, China;2. Department of Cancer Center, Shanxi Bethune Hospital, Taiyuan, 030000, China |
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| Abstract: | PurposeTo assess the effectiveness of SGRT in clinical applications through statistical process control (SPC).MethodsTaking the patients’ positioning through optical surface imaging (OSI) as a process, the average level of process execution was defined as the process mean. Setup errors detected by cone-beam computed tomography (CBCT) and OSI were extracted for head-and-neck cancer (HNC) and breast cancer patients. These data were used to construct individual and exponentially weighted moving average (EWMA) control charts to analyze outlier fractions and small process shifts from the process mean. Using the control charts and process capability indices derived from this process, the patient positioning-related OSI performance and setup error were analyzed for each patient.ResultsOutlier fractions and small shifts from the process mean that are indicative of setup errors were found to be widely prevalent, with the outliers randomly distributed between fractions. A systematic error of up to 1.6 mm between the OSI and CBCT results was observed in all directions, indicating a significantly degraded OSI performance. Adjusting this systematic error for each patient using setup errors of the first five fractions could effectively mitigate these effects. Process capability analysis following adjustment for systematic error indicated that OSI performance was acceptable (process capability index Cpk = 1.0) for HNC patients but unacceptable (Cpk < 0.75) for breast cancer patients.ConclusionSPC is a powerful tool for detecting the outlier fractions and process changes. Our application of SPC to patient-specific evaluations validated the suitability of OSI in clinical applications involving patient positioning. |
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| Keywords: | Optical surface imaging Setup error Process capability index Exponentially weighted moving average |
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