Statistical methods to evaluate the correlation between measured and calculated dose using quality assurance method in IMRT

Abstract

The objective of this study is to validate a procedure based on a statistical method to assess the agreement and the correlation between measured and calculated dose in the process of quality assurance (QA) for intensity-modulated radiation therapy (IMRT). Methods: Fifty-six fields for head and neck cancer treatment from 10 patients were analyzed. For each patient a treatment plan was generated using Eclipse TPS ®. To compare the calculated dose with the measured dose a CT-scan of solid water slabs (30 × 30 × 15 cm 3) was used. Absolute dose was measured by a pinpoint ionization chamber and 2D dose distributions using electronic portal imaging device dosimetry. Six criteria levels were applied for each field case (3%, 3 mm), (4%, 3 mm), (5%, 3 mm), (4%, 4 mm), (5%, 4 mm) and (5%, 5 mm). The normality of the data and the variance homogeneity were tested using Shapiro-Wilk's test and Levene's test, respectively. The Wilcoxon signed-rank paired test was used to calculate p-values. The Bland-Altman method was used to calculate the limit of agreement between calculated and measured doses and to draw a scatter plot. The correlation between calculated and measured doses was assessed using Spearman's rank test. Results: The statistical tests indicate that the data were not normally distributed, p < 0.001, and had a homogenous variance, p = 0.85. The upper and lower limits of agreement for absolute dose measurements were 6.44% and-6.40%, respectively. The Wilcoxon test indicated a significant difference between calculated and dose measured with the ionization chamber, p = 0.01. Spearman's test indicated a strong correlation between calculated and absolute measured dose, with correlation coefficient ρ = 0.99. Therefore, there is a lack of correlation between dose difference for absolute dose measurements and gamma passing rates for 2D dose measurements. Conclusion: The statistical tests showed that the commonly accepted criteria using gamma evaluation are not able to predict the dose difference for a global treatment plan or per beam. The current QA method provides inadequate protection of the patient. The method described here provides an overall analysis for dosimetric data from calculation and measurement, and can be quickly integrated into QA systems for IMRT.

Interpretation of Gamma Index for Quality Assurance of Simultaneously Integrated Boost (SIB) IMRT Plans for Head and Neck Carcinoma

“…In Figure 4, percentage dose difference of most of H&N plans were negative which suggest under dosage, same results reported by Chung et al [22]. Figure 5 demonstrates that there is a lack of correlation between DD and γ passing rates, same results reported in literature [20], with R 2 of 0.0509.…”

“…Hence confidence limit for DD depends on the proper assessment of dose calculation. [20]. Previous studies suggest that positioning error of multileaf collimator, inadequate dosimetric data of MLC in treatment planning system, complexity of tumor site, mode of delivery, and mishandling of dosimeter by user may cause discrepancy in measurement of dose difference [27][28][29][30].…”

“…Local confidence limit was explored using mean percentage of gamma passing points and SD. In present study Lower Limit of Agreement (LLA) and Upper Limit of Agreement (ULA) for dose difference were calculated in terms of Count Units (CU) [20].…”

Statistical evaluation of dosimetric differences changes between the Modified Batho's density correction method and the Anisotropic Analytical Algorithm for clinical practice

“…23- 24 The gamma tool shows a visual representation of the difference in dose distribution to the patient. They reported that the only realistic dose distribution is that evaluated by the clinical results obtained to the benefit of the patient.…”

Statistical control process to compare and rank treatment plans in radiation oncology: impact of heterogeneity correction on treatment planning in lung cancer

“…In this context, a challenge in radiation therapy for cancer treatment is to deliver the physical dose as close as possible to the prescription dose, depending on the accuracy of the dose calculation algorithms. The planed dose, given by the TPS, for each field could be compared with measured dose using Quality Assurance (QA) protocols according to the international recommendations (1)(2)(3)(4). The gamma index (γ) tool allows to compare the spatial dose distribution displaying the dose difference with γ-maps (5)(6)(7).…”