Construction of Prediction Model of Radiotherapy Set-Up Errors in Patients with Lung Cancer

构建肺癌患者放射治疗摆位误差预测模型

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Abstract

OBJECTIVE: This study intends to construct an error distribution prediction model and analyze its parameters and analyzes the boundary size of CTV extension to PTV, so as to provide a reference for lung cancer patients to control clinical set-up errors and radiotherapy planning. METHODS: The prior SBRT set-up error data of 50 patients with lung cancer treated by medical linear accelerator were selected, the Gaussian mixture model was adopted to construct the error distribution prediction model, and the model parameters were solved, based on which the emission boundary from CTV to PTV was calculated. RESULTS: According to the analysis of the model parameters, the spatial distribution of set-up errors is mainly concentrated in the direction of four central points (μ (1) ~ μ (4)), and the error is smaller in the Vrt direction (-0.991~2.808 mm) and Lat direction (-0.447~1.337 mm) and larger in the Lng direction (-1.065~4,463 mm). The possibility of offset of set-up errors in μ (2) and μ (3) direction (0.4440, 02198) is greater than that of μ (1) and μ (4) (0.1767, 0.1595). The standard deviation of set-up errors can reach 0.538 mm. The theoretical expansion boundary of CTV to PTV in Vrt, Lng, and Lat can be calculated as 1.7963 mm, 2.3749 mm, and 0.6066 mm. CONCLUSION: The GMM Gaussian mixture model can quantitatively describe and predict the set-up errors distribution of lung cancer patients and can obtain the emission boundary of CTV to PTV, which provides a reference for radiotherapy set-up errors control and tumor planning target expansion of lung cancer patients without SBRT.

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