医学
磁共振成像
逻辑回归
有效扩散系数
单变量分析
比例危险模型
病态的
回顾性队列研究
放射科
单变量
外科肿瘤学
阶段(地层学)
核医学
肿瘤科
多元分析
内科学
多元统计
古生物学
统计
生物
数学
作者
Kaiyue Zhang,Yu Zhang,Xin Fang,Jiangning Dong,Liting Qian
出处
期刊:BMC Cancer
[Springer Nature]
日期:2021-11-24
卷期号:21 (1)
被引量:17
标识
DOI:10.1186/s12885-021-08988-x
摘要
To identify predictive value of apparent diffusion coefficient (ADC) values and magnetic resonance imaging (MRI)-based radiomics for all recurrences in patients with endometrial carcinoma (EC).One hundred and seventy-four EC patients who were treated with operation and followed up in our institution were retrospectively reviewed, and the patients were divided into training and test group. Baseline clinicopathological features and mean ADC (ADCmean), minimum ADC (ADCmin), and maximum ADC (ADCmax) were analyzed. Radiomic parameters were extracted on T2 weighted images and screened by logistic regression, and then a radiomics signature was developed to calculate the radiomic score (radscore). In training group, Kaplan-Meier analysis was performed and a Cox regression model was used to evaluate the correlation between clinicopathological features, ADC values and radscore with recurrence, and verified in the test group.ADCmean showed inverse correlation with recurrence, while radscore was positively associated with recurrence. In univariate analyses, FIGO stage, pathological types, myometrial invasion, ADCmean, ADCmin and radscore were associated with recurrence. In the training group, multivariate Cox analysis showed that pathological types, ADCmean and radscore were independent risk factors for recurrence, which were verified in the test group.ADCmean value and radscore were independent predictors of recurrence of EC, which can supplement prognostic information in addition to clinicopathological information and provide basis for individualized treatment and follow-up plan.
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