A Patients-Based Statistical Model of Radiotherapy Dose Distribution in Nasopharyngeal Cancer

• Main Authors: Gang Liu, Jing Yang, Xin Nie, Xiaohui Zhu, Xiaoqiang Li, Jun zhou, Peyman Kabolizadeh, Qin Li, Hong Quan, Xuanfeng Ding
• Format: Article
• Language: English
• Published: SAGE Publishing 2019-12-01
• Series: Dose-Response
• Online Access: https://doi.org/10.1177/1559325819892359

Purpose: To develop a patients-based statistical model of dose distribution among patients with nasopharyngeal cancer (NPC). Methods and Materials: The dose distributions of 75 patients with NPC were acquired and preprocessed to generate a dose-template library. Subsequently, the dominant modes of dose distribution were extracted using principal component analysis (PCA). Leave-one-out cross-validation (LOOCV) was performed for evaluation. Residual reconstruction errors between the doses reconstructed using different dominating eigenvectors and the planned dose distribution were calculated to investigate the convergence characteristics. Three-dimensional Gamma analysis was performed to investigate the accuracy of dose reconstruction. Results: The first 29 components contained 90% of the variance in dose distribution, and 45 components accounted for more than 95% of the variance on average. The residual error of the LOOCV model for the cumulative sum of components over all patients decreased from 8.16 to 4.79 Gy when 1 to 74 components were included in the LOOCV model. The 3-dimensional Gamma analysis results implied that the PCA model was capable of dose distribution reconstruction, and the accuracy was especially satisfactory in the high-dose area. Conclusions: A PCA-based model of dose distribution variations in patients with NPC was developed, and its accuracy was determined. This model could serve as a predictor of 3-dimensional dose distribution.