Abstract
Robust optimization generates scenario‐based plans by a minimax optimization method to find optimal scenario for the trade‐off between target coverage robustness and organ‐at‐risk (OAR) sparing. In this study, 20 lung cancer patients with tumors located at various anatomical regions within the lungs were selected and robust optimization photon treatment plans including intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) plans were generated. The plan robustness was analyzed using perturbed doses with setup error boundary of ±3 mm in anterior/posterior (AP), ±3 mm in left/right (LR), and ±5 mm in inferior/superior (IS) directions from isocenter. Perturbed doses for D99, D98, and D95 were computed from six shifted isocenter plans to evaluate plan robustness. Dosimetric study was performed to compare the internal target volume‐based robust optimization plans (ITV‐IMRT and ITV‐VMAT) and conventional PTV margin‐based plans (PTV‐IMRT and PTV‐VMAT). The dosimetric comparison parameters were: ITV target mean dose (Dmean), R95(D95/Dprescription), Paddick's conformity index (CI), homogeneity index (HI), monitor unit (MU), and OAR doses including lung (Dmean, V20 Gy and V15 Gy), chest wall, heart, esophagus, and maximum cord doses. A comparison of optimization results showed the robust optimization plan had better ITV dose coverage, better CI, worse HI, and lower OAR doses than conventional PTV margin‐based plans. Plan robustness evaluation showed that the perturbed doses of D99, D98, and D95 were all satisfied at least 99% of the ITV to received 95% of prescription doses. It was also observed that PTV margin‐based plans had higher MU than robust optimization plans. The results also showed robust optimization can generate plans that offer increased OAR sparing, especially for normal lungs and OARs near or abutting the target. Weak correlation was found between normal lung dose and target size, and no other correlation was observed in this study.
Highlights
Robust optimization is primarily used to plan intensity modulated proton therapy (IMPT) 1 and it was not until recently that robust optimization techniques have been available for x-ray beam in radiation therapy treatment planning system.[2]
The robust optimization plans showed better conformity index (CI) and worse homogeneity index (HI) compared to planning target volume (PTV) margin-based plans
It was observed that there was no statistical difference for internal target volume (ITV) dose coverage and that there was a statistically significant difference with better HI and CI for ITV-intensity modulated radiotherapy (IMRT) compared to ITV-volumetric modulated arc therapy (VMAT) plans
Summary
Robust optimization is primarily used to plan intensity modulated proton therapy (IMPT) 1 and it was not until recently that robust optimization techniques have been available for x-ray beam in radiation therapy treatment planning system.[2]. Position uncertainties come from two sources: tumor motion and variations in tumor shapes, and patient setup uncertainties. One way to approach these uncertainties is to use minimax optimization.[3] Instead of expanding the internal target volume (ITV) with a fixed margin to create the planning target volume (PTV), robust optimization allows entering the setup uncertainties into the planning computer and discretizes them into multiple scenarios (shifts within the margin bounds). Robust optimization method generates scenario-based plans that have plan quality considered at least equivalent to static PTV margin-based plans.[4,5,6] This method has the potential to reduce the doses to healthy tissues, especially for tumors with substantially larger intrafraction motions in which there could be overlap between PTV and organ at risk (OAR)
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