(Sunday, 7/12/2020) [Eastern Time (GMT-4)]
Room: AAPM ePoster Library
Purpose: Clinical trials for SBRT lung treatments have been developed using convolution-superposition and collapsed cone convolution algorithms, such as AAA. However, more accurate algorithms have become commercially available and are gaining use clinically. Acuros has rapidly been adopted as one of the more accurate algorithms. The increased accuracy is especially evident in heterogeneous regions, such as the lung. This difference is the most pronounced for island-type tumors. The aim of this study is to evaluate SBRT lung planning using AXB compared to AAA and determine how to apply the older protocols to AXB.
Methods: A cohort of 30 patients treated with plans calculated by AXB was retrospectively analyzed. The delivered plans were recalculated using AAA with two treatment techniques. The first case was done with modulated conformal arc beams only. The second used the same conformal arcs, but had 1-3 static oblique beams added to help achieve protocol recommendations. A subgroup of 13 patients with island-type tumors were evaluated separately. The plans were evaluated using the RTOG 0813 guidelines.
Results: In order achieve equal PTV coverage of V95 = 100% Rx AXB required 2% more MU, on average. When comparing AAA to AXB using the same MU, this lead to AXB having worse tumor coverage (V100=95.0% vs 91.4%) Due to the decrease in dose, AXB reported better results in maximum dose, high dose spillage, D2cm, and V50.
When the plans were renormalized to match PTV coverage, AXB did worse in all RTOG evaluation criteria. These results were more extreme for island-type tumors.
Conclusion: By switching over to a more accurate dose calculation algorithm, more MU are needed for PTV coverage and it is more difficult to achieve RTOG protocol guidelines upon renormalization. New guidelines regarding acceptable dose to the PTV and healthy tissues are recommended.
Keywords
Treatment Planning, Lung, Dosimetry Protocols
Taxonomy
TH- External Beam- Photons: treatment planning/virtual clinical studies
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