The prominent value of apparent diffusion coefficient in assessing high-risk factors and prognosis for patients with endometrial carcinoma before treatment

Autor: Yu Meng, Siling Ren, Shuwei Zhou, Yunfeng Lu, Jingxian Wu, Wanchun Yin, Beibei Xuan, Xiaoling Mu, Rongsheng Chen, Fenfen Zhang, Yi Hua, Quan Quan, Kunying Rao
Rok vydání: 2020
Předmět:
Zdroj: Acta radiologica (Stockholm, Sweden : 1987). 62(6)
ISSN: 1600-0455
Popis: Background To date, there are no consensus methods to evaluate the high-risk factors and prognosis for managing the personalized treatment schedule of patients with endometrial carcinoma (EC) before treatment. Apparent diffusion coefficient (ADC) is regarded as a kind of technique to assess heterogeneity of malignant tumor. Purpose To explore the role of ADC value in assessing the high-risk factors and prognosis of EC. Material and Methods A retrospective analysis was made on 185 patients with EC who underwent 1.5-T magnetic resonance imaging (MRI). Mean ADC (mADC), minimum ADC (minADC), and maximum ADC (maxADC) were measured and compared in different groups. Results Among the 185 patients with EC, the mADC and maxADC values in those with high-risk factors (type 2, deep myometrial invasion, and lymph node metastasis) were significantly lower than in those without. According to receiver operating characteristic (ROC) curve analysis, the areas under the curve (AUC) were significant for mADC, minADC, and maxADC predicting high-risk factors. Furthermore, the AUCs were significant for mADC and maxADC predicting lymph node metastasis but were not significant for minADC. Patients with lower mADC were associated with worse overall survival and disease-free survival; the opposite was true for patients with higher mADC. Conclusion Our study showed that ADC values could be applied to assess the high-risk factors of EC before treatment and might significantly relate to the prognosis of EC. It might contribute to managing initial individualized treatment schedule and improve outcome in patients with EC.
Databáze: OpenAIRE