Prognostic value of computed tomography texture features in non-small cell lung cancers treated with definitive concomitant chemoradiotherapy.
OBJECTIVES: The aim of this study was to investigate whether the computed tomography (CT) texture features of primary tumors are associated with the overall survival (OS) of non-small cell lung cancer (NSCLC) patients undergoing definitive concomitant chemoradiotherapy (CCRT). MATERIALS AND METHODS: In this retrospective study, 98 patients (83 men and 15 women; mean age, 61.9 ± 8.0 years) with unresectable NSCLCs (stage IIIA, 45; stage IIIB, 53) underwent definitive CCRT at our institution from January 2006 to December 2011. Patients were followed up for 3 years or until death. The CT texture parameters of primary tumors were extracted from contrast-enhanced CT images taken before CCRT using an in-house software program. Each texture parameter was dichotomized based on their optimal cutoff values obtained from receiver operating characteristics curve analysis. Three-year OS was compared between the dichotomized subgroups using Kaplan-Meier analysis and the log-rank test. Multivariate Cox regression analysis was performed to determine significant prognostic factors. RESULTS: The 3-year cumulative survival rate was 0.51. The mean 3-year OS was 24.0 months (95% confidence interval, 21.5-26.6 months). There were no significant differences in 3-year OS according to tumor stage or histologic subtypes. However, entropy (P = 0.030), skewness (P = 0.021), and mean attenuation (P = 0.030) were shown to be significantly associated with 3-year OS. Multivariate Cox regression analysis revealed that higher entropy (adjusted hazard ratio [HR],2.31; P = 0.040), higher skewness (adjusted HR,1.92; P = 0.046), and higher mean attenuation (adjusted HR,1.93; P = 0.028) were independent predictors of decreased 3-year OS. CONCLUSIONS: Computed tomography texture features have the potential to be used as prognostic biomarkers in unresectable NSCLC patients undergoing definitive CCRT.
Ahn, SY; Park, CM; Park, SJ; Kim, HJ; Song, C; Lee, SM; McAdams, HP; Goo, JM
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