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Updated: Feb 6, 2026

Dynamic Lung Tumor Tracking for Stereotactic Ablative Body Radiation Therapy
Published on: June 7, 2015
ITV-Based Robust Optimization for VMAT Planning of Stereotactic Body Radiation Therapy of Lung Cancer
Xiaoying Liang1, Dandan Zheng2, Maria Mamalui-Hunter1
1Department of Radiation Oncology, University of Florida, Gainesville, Florida.
Purpose:
Using planning target volume (PTV) to account for setup uncertainties in stereotactic body radiation therapy (SBRT) of lung cancer has been questioned because a significant portion of the PTV contains low-density lung tissue. The purpose of this study is to (1) investigate the feasibility of using robust optimization to account for setup uncertainties in volumetric modulated arc therapy plan for lung SBRT and (2) evaluate the potential normal tissue-sparing benefit of a robust optimized plan compared with a conventional PTV-based optimized plan.
Methods And Materials:
The study was conducted with both phantom and patient cases. For each patient or phantom, 2 SBRT lung volumetric modulated arc therapy plans were generated, including an optimized plan based on the PTV (PTV-based plan) with a 5-mm internal target volume (ITV)-to-PTV margin and a second plan based on robust optimization of 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 was evaluated.
Results:
Compared with PTV-based 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.
Conclusions:
Using ITV-based robust optimization, we have shown that accounting for setup uncertainty in SBRT planning is feasible. Further clinical studies are warranted to confirm the clinical effectiveness of this novel approach.
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