Improving the gamma analysis comparison using an unbinned multivariate test
| Autor: | Verónica Moran-Velasco, Luis Isaac Ramos Garcia, Pedro-Borja Aguilar-Redondo, José Fernando Pérez Azorin |
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| Rok vydání: | 2017 |
| Předmět: |
Models
Statistical Statistical distance Radiological and Ultrasound Technology Phantoms Imaging Radiotherapy Planning Computer-Assisted Gamma ray Radiotherapy Dosage Square (algebra) 030218 nuclear medicine & medical imaging Test (assessment) Power (physics) 03 medical and health sciences Matrix (mathematics) 0302 clinical medicine Gamma Rays 030220 oncology & carcinogenesis Statistical significance Statistics Humans Radiology Nuclear Medicine and imaging Radiotherapy Intensity-Modulated Radiometry Mathematics Statistical hypothesis testing |
| Zdroj: | Physics in Medicine & Biology. 62:N417-N427 |
| ISSN: | 1361-6560 |
| Popis: | In this study, we present a new procedure for the comparison of two dose matrices by means of a statistical test. A statistical distance is proposed to decide whether the difference between the two matrices is statistically significant. This statistical test is based on the square difference between the experimental and expected gamma matrix results. The expected gamma matrix is calculated by simulating the measurement process. For comparison purposes, the significance level of the test was chosen to give the same statistical significance as 90% of gamma-pass rate. The performance of the statistical distance is checked against 53 VMAT. The power of the presented test was compared using simulations with the 90% gamma-pass rate criteria for two cases in which intentional errors are introduced. In both cases, the test is uniformly more powerful. According to the test, two of the measured plans have a significant difference with calculated matrices, although the gamma pass rate measured was always greater than 90%. |
| Databáze: | OpenAIRE |
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