Quantified difference of the collapsed cone convolution (CCC) and Monte Carlo (MC) algorithms based on DVH and gamma analysis for cervical cancer radiation therapy

Abstract

ObjectiveTo quantify the difference between the (collapsed cone convolution) CCC algorithm and the (Monte Carlo) MC algorithm and remind that the planners should pay attention to some possible uncertainties of the two algorithms when employing the two algorithms. MethodsThirty patients’ cervical cancer VMAT plans were designed with a Pinnacle TPS (Philips) and divided equally into two groups: the simple group (SG, target volume was only the PTV) and the complex group (CG, target volume included the PTV and PGTV). The plans from the Pinnacle TPS were transferred to the Monaco TPS (Elekta).The plans’ parameters all remained unchanged, and the dose was recalculated. Gamma passing rates (GPRs) obtained from dose distribution from Pinnacle TPS compared with that from Monaco TPS with SNC software based on three triaxial planes (transverse, sagittal and coronal). GPRs and DVH were used to quantify the difference between the CCC algorithm in pinnacle TPS and the MC algorithm in Monaco TPS. ResultsAmong the statistical dose indexes in DVHs from the Pinnacle and Monaco TPSs, there were 7(7/15) dose indexes difference with statistically significant differences in the SG, and 10(10/18) dose indexes difference with statistically significant differences in the CG. With 3%/3 mm criterion, the most (5/6) GPRs were greater than 95% from the SG and CG. But with 2%/2 mm criterion, the most (5/6) GPRs were less than 90% from the two groups. In addition, we found that GPRs were also related to the selected triaxial planes and the complexity of the plan (GPRs varied with the SG and CG). ConclusionsObvious difference between the CCC and MC algorithms from Pinnacle and Monaco TPS. DVH maybe better than 2D gamma analysis on quantifying difference of the CCC and MC algorithms. Some attention should be paid to the uncertainty of the TPS algorithm, especially when the indicator on the DVH is at the critical point of the threshold value, because the algorithm used may overestimate or underestimate the DVH indicator.