Purpose: To assess the clinical impact of the Acuros XB algorithm (implemented in the Varian Eclipse treatment-planning system) in non-small-cell lung cancer (NSCLC) cases.
Methods And Materials: A CT dataset of 10 patients presenting with advanced NSCLC was selected and contoured for planning target volume, lungs, heart, and spinal cord. Plans were created for 6-MV and 15-MV beams using three-dimensional conformal therapy, intensity-modulated therapy, and volumetric modulated arc therapy with RapidArc. Calculations were performed with Acuros XB and the Anisotropic Analytical Algorithm. To distinguish between differences coming from the different heterogeneity management and those coming from the algorithm and its implementation, all the plans were recalculated assigning Hounsfield Unit (HU) = 0 (Water) to the CT dataset.
Results: Differences in dose distributions between the two algorithms calculated in Water were <0.5%. This suggests that the differences in the real CT dataset can be ascribed mainly to the different heterogeneity management, which is proven to be more accurate in the Acuros XB calculations. The planning target dose difference was stratified between the target in soft tissue, where the mean dose was found to be lower for Acuros XB, with a range of 0.4% ± 0.6% (intensity-modulated therapy, 6 MV) to 1.7% ± 0.2% (three-dimensional conformal therapy, 6 MV), and the target in lung tissue, where the mean dose was higher for 6 MV (from 0.2% ± 0.2% to 1.2% ± 0.5%) and lower for 15 MV (from 0.5% ± 0.5% to 2.0% ± 0.9%). Mean doses to organs at risk presented differences up to 3% of the mean structure dose in the worst case. No particular or systematic differences were found related to the various modalities. Calculation time ratios between calculation time for Acuros XB and the Anisotropic Analytical Algorithm were 7 for three-dimensional conformal therapy, 5 for intensity-modulated therapy, and 0.2 for volumetric modulated arc therapy with RapidArc.
Conclusion: The availability of Acuros XB could improve patient dose estimation, increasing the data consistency of clinical trials.
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