Calvo-Ortega Juan-Francisco
Oncología Radioterápica, Hospital Quirónsalud Málaga, Malaga, Spain.
Oncología Radioterápica, Hospital Quirónsalud Barcelona, Barcelona, Spain.
Rep Pract Oncol Radiother. 2024 Mar 18;29(1):62-68. doi: 10.5603/rpor.99027. eCollection 2024.
The aim was to improve the portal dosimetry-based quality assurance results of conventional treatment plans by adjusting the multileaf collimator (MLC) dosimetric leaf gap (DLG) and transmission (T) values of the anisotropic analytic algorithm (AAA) used for portal dose image prediction (PDIP).
The AAA-based PDIP v. 16.1 algorithm (PDIP-AAA) of the Eclipse TPS was configured for 6 MV FFF energy. Optimal DLG and T values were achieved for this algorithm by comparing predicted versus measured portal images of the Chair pattern. Twenty clinical plans using 6 MV FFF beams were verified using the optimal PDIP-AAA algorithm and the standard PDIP v. 16 algorithm (PDIP-vE), configured using the van Esch package. The 3% global/2 mm gamma passing rates (GPRs) and average gamma indexes (AGIs) were computed for each acquired image. For each plan, the mean GPR (GPR) and mean GAI (GAI) were compared for both algorithms. A 2-tailed Student t-test (α = 0.05) was used to evaluate whether there was a statistically significant difference.
Optimal values of DLG = 0.1 mm and T = 0.01 were found for the PDIP-AAA algorithm, providing significantly better values of GPR and AGI than PDIP-vE (p < 0.001). All plans verified with PIDP-AAA showed GPR ≥ 95%. In contrast, only 45% of the plans reported GPR ≥ 95% with the PDIP-vE algorithm.
The MLC parameters available in the PDIP-AAA model must be tuned to improve the accuracy of the predicted dose image. This work-around is not possible using the standard PDIP algorithm. The adjusted PDIP-AAA resulted in significantly better results than PDIP-vE.
目的是通过调整用于射野剂量图像预测（PDIP）的各向异性解析算法（AAA）的多叶准直器（MLC）剂量叶间距（DLG）和透射率（T）值，来改善基于射野剂量测定的传统治疗计划的质量保证结果。
将Eclipse治疗计划系统（TPS）基于AAA的PDIP v. 16.1算法（PDIP - AAA）配置为6 MV FFF能量。通过比较椅子图案的预测射野图像与测量射野图像，为该算法确定最佳DLG和T值。使用最佳PDIP - AAA算法和使用范埃施软件包配置的标准PDIP v. 16算法（PDIP - vE），对20个使用6 MV FFF射束的临床计划进行验证。为每个采集的图像计算3%全局/2 mm伽马通过率（GPR）和平均伽马指数（AGI）。对于每个计划，比较两种算法的平均GPR（GPR）和平均GAI（GAI）。使用双尾学生t检验（α = 0.05）评估是否存在统计学上的显著差异。
发现PDIP - AAA算法的最佳DLG值为0.1 mm，T值为0.01，与PDIP - vE相比，GPR和AGI值显著更好（p < 0.001）。所有用PIDP - AAA验证的计划显示GPR≥95%。相比之下，使用PDIP - vE算法时，只有45%的计划报告GPR≥95%。
必须调整PDIP - AAA模型中的MLC参数，以提高预测剂量图像的准确性。使用标准PDIP算法无法实现此变通方法。调整后的PDIP - AAA比PDIP - vE产生了显著更好的结果。
