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Updated: Feb 25, 2026

Basics of Multivariate Analysis in Neuroimaging Data
Published on: July 24, 2010
Improving the gamma analysis comparison using an unbinned multivariate test
Luis Isaac Ramos Garcia1, José Fernando Pérez Azorín2, Pedro-Borja Aguilar-Redondo1
1Department of Medical Physics, Clínica Universidad de Navarra, University of Navarra, Av. Pio XII s/n, Pamplona, Navarre, Spain.
Abstract:
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%.
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