A Predictor of Tumor Recurrence in Patients With Endometrial Carcinoma After Complete Resection of the Tumor: The Role of Pretreatment Apparent Diffusion Coefficient. Issue 5 (June 2018) - Kuwahara, Ryo; Kido, Aki; Tanaka, Shiro; Abiko, Kaoru; Nakao, Kyoko; Himoto, Yuki; Nishio, Naoko; Kurata, Yasuhisa; Mandai, Masaki; Togashi, Kaori
Abstract : Objectives: The aim of this study was to assess the prognostic and incremental value of pretreatment apparent diffusion coefficient (ADC) values of tumors for the prediction of tumor recurrence after complete resection of the tumor in patients with endometrial cancer. Methods: This study enrolled 210 patients with stages IA to IIIC endometrial cancer who had undergone complete resection of the tumor and pretreatment magnetic resonance imaging. The minimum and mean ADC values (ADCmin, ADCmean) of tumors and normalized ADC (nADCmin, nADCmean) were calculated from magnetic resonance imaging. The primary outcome was recurrence-free survival (RFS). Receiver operating characteristic analysis was performed to compare the diagnostic performance of ADC values of 4 types. The Kaplan-Meier method, log-rank tests, and Cox regression were used to explore associations between recurrence and the ADC values with adjustment for clinicopathological factors. Results: In receiver operating characteristic curve analysis, the areas under the curve were significant for ADCmean and nADCmean predicting tumor recurrence but were not significant for ADCmin and nADCmin. Regarding univariate analysis, ADCmean and nADCmean were significantly associated with increased risk of recurrence. Multivariate analysis showed that ADCmean and nADCmean remained independently associated with shorter RFS. In the high-risk group, the RFS of patients with lower ADC values (ADCmean and nADCmean) was significantly shorter than that of patients in the higher ADC value group. Conclusions: Pretreatment tumor ADCmean and nADCmean were important imaging biomarkers for predicting recurrence in patients after complete resection of the tumor. They might improve existing risk stratification. Abstract : Supplemental digital content is available in the text.