UNASSIGNED: BackgroundThe accuracy of dose calculation is crucial to the quality of treatment planning and, consequently, to the dose delivered to @entity1 undergoing radiation therapy. Current general calculation algorithms such as Pencil Beam Convolution (PBC) and Collapsed Cone Convolution (CCC) have shortcomings in regard to severe inhomogeneities, particularly in those regions where charged particle equilibrium does not hold. The aim of this study was to evaluate the accuracy of the PBC and @entity6121 in @entity2 radiotherapy using Monte Carlo (MC) technology.Methods and materialsFour treatment plans were designed using Oncentra Masterplan TPS for each @entity1 . Two intensity-modulated radiation therapy (IMRT) plans were developed using the PBC and @entity6121 , and two three-dimensional conformal therapy (3DCRT) plans were developed using the PBC and @entity6121 . The DICOM-RT files of the treatment plans were exported to the Monte Carlo system to recalculate. The dose distributions of GTV, @entity343 and ipsilateral lung calculated by the TPS and MC were compared.ResultFor 3DCRT and IMRT plans, the mean dose differences for GTV between the CCC and MC increased with decreasing of the GTV volume. For IMRT, the mean dose differences were found to be higher than that of 3DCRT. The CCC algorithm overestimated the GTV mean dose by approximately 3% for IMRT. For 3DCRT plans, when the volume of the GTV was greater than 100 cm3, the mean doses calculated by CCC and MC almost have no difference. PBC shows large deviations from the MC algorithm. For the dose to the ipsilateral lung, the CCC algorithm overestimated the dose to the entire lung, and the PBC algorithm overestimated V20 but underestimated V5; the difference in V10 was not statistically significant.ConclusionsPBC substantially overestimates the dose to the @entity5 , but the CCC is similar to the MC simulation. It is recommended that the treatment plans for @entity2 be developed using an advanced dose calculation algorithm other than PBC. MC can accurately calculate the dose distribution in @entity2 and can provide a notably effective tool for benchmarking the performance of other dose calculation algorithms within @entity1 .

A clinical study of XXXX dose calculation accuracy with Monte Carlo simulation.

@entity1 :: ('9606', 'Species') :: ['patients', 'patient'] @entity5 :: ('MESH:D009369', 'Disease') :: ['tumour'] @entity2 :: ('MESH:D008175', 'Disease') :: ['lung cancer'] @entity343 :: ('187978', 'Species') :: ['PTV'] @entity6121 :: ('MESH:C566719', 'Disease') :: ['CCC algorithms']
@entity2 :: (MESH:D008175,Disease) :: ['lung cancer']
