Abstract

PurposeNovel irradiation techniques are continuously introduced in radiotherapy to optimize the accuracy, the security and the clinical outcome of treatments. These changes could raise the question of discontinuity in dosimetric presentation and the subsequent need for practice adjustments in case of significant modifications. This study proposes a comprehensive approach to compare different techniques and tests whether their respective dose calculation algorithms give rise to statistically significant differences in the treatment doses for the patient.MethodsStatistical investigation principles are presented in the framework of a clinical example based on 62 fields of radiotherapy for lung cancer. The delivered doses in monitor units were calculated using three different dose calculation methods: the reference method accounts the dose without tissues density corrections using Pencil Beam Convolution (PBC) algorithm, whereas new methods calculate the dose with tissues density correction for 1D and 3D using Modified Batho (MB) method and Equivalent Tissue air ratio (ETAR) method, respectively. The normality of the data and the homogeneity of variance between groups were tested using Shapiro-Wilks and Levene test, respectively, then non-parametric statistical tests were performed. Specifically, the dose means estimated by the different calculation methods were compared using Friedman’s test and Wilcoxon signed-rank test. In addition, the correlation between the doses calculated by the three methods was assessed using Spearman’s rank and Kendall’s rank tests.ResultsThe Friedman’s test showed a significant effect on the calculation method for the delivered dose of lung cancer patients (p <0.001). The density correction methods yielded to lower doses as compared to PBC by on average (−5 ± 4.4 SD) for MB and (−4.7 ± 5 SD) for ETAR. Post-hoc Wilcoxon signed-rank test of paired comparisons indicated that the delivered dose was significantly reduced using density-corrected methods as compared to the reference method. Spearman’s and Kendall’s rank tests indicated a positive correlation between the doses calculated with the different methods.ConclusionThis paper illustrates and justifies the use of statistical tests and graphical representations for dosimetric comparisons in radiotherapy. The statistical analysis shows the significance of dose differences resulting from two or more techniques in radiotherapy.

Highlights

  • Radiotherapy techniques The main challenge in radiation therapy for cancer treatment is to obtain the highest probability of tumor control or cure with the least amount of morbidity and toxicity to normal surrounding tissues

  • It is very easy to compare the spatial dose distribution of two DICOM RT files by using γ index or χ index [1,2]

  • This paper presents a series of statistical tests implemented in a step by step procedure that should help the radiation oncologist comparing the dosimetric outcome of different dose calculation algorithms

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Summary

Introduction

Radiotherapy techniques The main challenge in radiation therapy for cancer treatment is to obtain the highest probability of tumor control or cure with the least amount of morbidity and toxicity to normal surrounding tissues (organs at risk). Any difference between the computed dose will be visualized using γ or χ maps [3] If ignored, this alteration could endanger the clinical outcome of the treatment. Each department could perform the assessment tests without investing too much time and resources At this extend, radiotherapy offers the valuable situation in which each patient case could be recalculated in many different ways providing paired series of data. This paper presents a series of statistical tests implemented in a step by step procedure that should help the radiation oncologist comparing the dosimetric outcome of different dose calculation algorithms. The goal is to provide the radiation oncologist and the physicists interpretable results to help them to validate new dose calculation methods

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