ESTRO 2024 - Abstract Book

S4797

Physics - Quality assurance and auditing

ESTRO 2024

Figure 1. Schematic of the Spearman’s correlation coefficient matrix. The darker the red or blue color, the stronger the correlation between QA results and features of fluence map or complexity indices.

Figure 2. Schematic of the Spearman’s correlation coefficient matrix according to type of MLC and TPS. The darker the red or blue color, the stronger the correlation between QA results and features of fluence map or complexity indices.

Conclusion:

We conducted an analysis of CIs and radiomic features extracted from fluence maps, and determined their correlation with pre-treatment QA. Notably, we observed a statistically significant difference in classification based on MLC and a stronger correlation with QA results than classification by TPS. Given the strong correlation between radiomic features and QA results, the analysis of CIs and radiomic features can be employed to predict the accuracy of treatment delivery.

Keywords: Complexity analysis, Radiomic features, PTQA