Individualized gating windows based on four-dimensional CT information for respiration-gated radiotherapy.
The purpose of this work is to relate the gating window and displacement of a moving tumor target and develop a systematic method to individualize the gating window for respiration-gated radiation therapy (RT). As the relationship between patient anatomy and respiration phase is contained in 4D images, we aim to quantify this information and utilize the data to guide gated treatment planning. After 4D image acquisition, the target and organs at risk were delineated manually on the selected gating phase. The contours were propagated automatically onto every phase-specific image set using a control volume-based contour mapping technique. The mean and maximum distances between the contours in the gating phase and each of other phases were evaluated in three dimensions. The gating window was determined in such a way that the residual movement of the target within the window is smaller or equal to the patient's setup error. The proposed method was applied to plan the gated treatments of 12 lung cancer patients. As a result of this work, a method to calculate patient-specific gating windows has been developed. The general reference drawn from this study is that, with the aide of 4D images and automated 4D contour propagation, it is feasible to individualize the gating widow selection. As compared with the current practice, the proposed technique has a potential to eliminate the guesswork involved in choosing a gating window and avoid dosimetric error in planning gated RT. In conclusion, individualization of gating windows reduces the subjectivity in respiration-gated RT and improves the treatment of moving targets.
Wink
Nicole M
NM
Department of Radiation Oncology, Stanford University Medical Center, Stanford, CA, USA. nicole.wink@gmail.com
Chao
Ming
M
Antony
Jiji
J
Xing
Lei
L
D055592:Biophysical Phenomena; D001703:Biophysics; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging / Q000503:physiopathology / Q000532:radiotherapy; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000503:physiopathology* / Q000532:radiotherapy*; D009038:Motion; D049268:Positron-Emission Tomography; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods* / Q000706:statistics & numerical data; D015656:Respiratory Mechanics; D014057:Tomography, X-Ray Computed / Q000379:methods / Q000706:statistics & numerical data