Affiliations: [a] Department of Oncology, the First People’s Hospital of Jingmen, Jingmen, Hubei, China | [b] Department of Radiation Oncology, Sichuan Cancer Hospital and Institution, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Radiation Oncology Key Laboratory of Sichuan, Chengdu, Sichuan, China
Correspondence:
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Corresponding authors: Qifeng Wang and Tao Li, Department of Radiation Oncology, Sichuan Cancer Hospital and Institution, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China. Tel.: +86 28 854 205 30; Fax: +86 28 854 201 73; E-mails: [email protected]; [email protected].
Abstract: INTRODUCTION: To study the relationship between the tumor heterogeneity based on CT and overall survival (OS) in oesophageal squamous cell carcinoma treated with chemotherapy and radiation therapy (CRT). METHODS: Fifty-seventh clinical patients who underwent definitive CRT were analyzed. The results were analyzed in terms of whole-tumor texture, with quantification of entropy, mean gray-level intensity for fine to coarse textures (filters 1.0–2.5, respectively). The association between texture parameters and survival time was assessed by Kaplan-Meier analysis and a Cox proportional hazards model. RESULTS: The median, 1 and 3 years OS, were 20.2 months, 75.4%, and 32.1%. In the univariate analysis performed using the log-rank test found global entropies (P= 0.0119), global mean (P= 0.088), global Std (P= 0.0209), and global uniformity (P= 0.0284) were found to be significant OS prognostic factors for filter value 1.0. Cox proportional hazards models that included a combination of pretreatment GlobalStd and post-treatment volume yields the best performance in predicting OS. Kaplan-Meier curves show that the patients in the high-risk group have significantly worse OS (log-rank test, P= 0.0009) and progression-free survival (PFS) (log-rank test, P= 0.0019) than those in the low-risk group. CONCLUSION: Pretreatment texture parameters are associated with survival time, and the combination of post volume performed better in survival models.
