(Tuesday, 7/31/2018) 1:15 PM - 1:45 PM
Room: Exhibit Hall | Forum 7
Purpose: To investigate the applicability of using robust optimization to account for setup uncertainties on VMAT plan for SBRT lung treatment and to evaluate the potential normal tissue sparing benefit of robust optimized plan compared over conventional PTV-based optimized plan, and to identify factors associated with dose differences between the two approaches.
Methods: The study was carried out on both phantom and patient cases. For each patient or phantom, two SBRT lung VMAT plans were generated, including an optimized plan based on the PTV (PTV-based plan) with 5-mm ITV-to-PTV margin, and a second plan based on robust optimization of the ITV (ITV-based plan) with ±5 mm setup uncertainties. The target coverage was evaluated on ITV D99 in 15 scenarios that simulated a 5-mm setup error. Dose volume information on normal lung tissue, intermediate to high dose spillage and integral dose were evaluated. Linear regression analysis was performed to identify the cause of the dosimetric differences between ITV- and PTV-based plans.
Results: Compared with PTV-base plans, ITV-based robust optimized plans resulted in lower normal lung tissue dose, lower intermediate to high dose spillage to the body, and lower integral dose, while preserving the dose coverage under setup error scenarios, for both phantom and patient cases. The phantom study demonstrated that with the same tumor size, smaller motion amplitude had bigger relative dose reduction in lung V20Gy and in mean lung dose. Strong positive correlations were observed on dose reduction on lung V20Gy, mean lung dose, integral dose, V80% and V50% with the mean HU difference between the ITV and the PTV.
Conclusion: Robust optimization on ITV to account for setup uncertainties has been shown to be a possible new method for planning SBRT with VMAT. Clinical studies utilizing this approach are needed to confirm the effectiveness of this approach.
Keywords
Taxonomy
TH- External beam- photons: treatment planning/virtual clinical studies
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