Background: The principal aim of this study was to evaluate the feasibility of incorporating four-dimensional (4D)-computed tomography (CT)-based functional information into treatment planning and to evaluate the potential benefits of individualized beam setups to better protect lung functionality in patients with non-small cell lung cancer (NSCLC).Methods: Peak-exhale and peak-inhale CT scans were carried out in 16 patients with NSCLC treated with intensity-modulated radiotherapy (IMRT). 4D-CT-based ventilation information was generated from the two sets of CT images using deformable image registration. Four kinds of IMRT plans were generated for each patient: two anatomic plans without incorporation of ventilation information, and two functional plans with ventilation information, using either five equally spaced beams (FESB) or five manually optimized beams (FMOB). The dosimetric parameters of the plans were compared in terms of target and normal tissue structures, with special focus on dose delivered to total lung and functional lung. Results: In both the anatomic and functional plans, the percentages of both the functional and total lung regions irradiated at V5, V10, and V20 (percentage volume irradiated to >5, >10 and >20 Gy, respectively) were significantly lower for FMOB compared with FESB (P < 0.05), but there was no significant difference for V30 (P > 0.05). Compared with FESB, a greater degree of sparing of the functional lung was achieved in functional IMRT plans with optimal beam arrangement, without compromising target volume coverage or the irradiated volume of organs at risk, such as the spinal cord, esophagus, and heart. Conclusions: Pulmonary ventilation image-guided IMRT planning with further optimization of beam arrangements improves the preservation of functional lung in patients with NSCLC.
CITATION STYLE
Wang, R., Zhang, S., Yu, H., Lin, S., Zhang, G., Tang, R., & Qi, B. (2014). Optimal beam arrangement for pulmonary ventilation image-guided intensity-modulated radiotherapy for lung cancer. Radiation Oncology, 9(1). https://doi.org/10.1186/1748-717X-9-184
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