Contrast-enhanced MRI and CT in evaluating treatment response for recurrent endometrial cancer: a retrospective case-control study

对比增强磁共振成像和CT在评估复发性子宫内膜癌治疗反应中的应用:一项回顾性病例对照研究

阅读:1

Abstract

OBJECTIVES: To compare the diagnostic performance of contrast-enhanced magnetic resonance imaging (CE-MRI) and computed tomography (CT) in evaluating treatment response for recurrent endometrial cancer (EC), and to assess the added value of integrating imaging findings with biomarker data. METHODS: This retrospective case-control study included 217 patients with recurrent EC treated between January 2020 and December 2023. Patients were divided into response (n = 102) and non-response (n = 115) based on Response Evaluation Criteria in Solid Tumors (RECIST) (1.1). An internal validation cohort (n = 142) and an external cohort (n = 168) were also analyzed. Preoperative CE-MRI and CT scans were reviewed by experienced radiologists. Biomarker positivity rates - including estrogen receptor (ER), progesterone receptor (PR), cancer antigen 125 (CA125), cancer antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), and ovarian cancer-related protein 1 (OVX1), were assessed. Multivariate logistic regression and receiver operating characteristic (ROC) analyses were performed to evaluate diagnostic performance, and an integrated model combining imaging and biomarkers was developed. RESULTS: CE-MRI achieved an AUC of 0.864, sensitivity of 78.3%, and specificity of 86.3%, while CT showed an AUC of 0.854, sensitivity of 81.2%, and specificity of 83.4%. The integrated model improved performance with an AUC of 0.889, sensitivity of 94.3%, and specificity of 81.2%. Internal and external validation models yielded AUCs of 0.859 and 0.918, respectively. CONCLUSIONS: Both CE-MRI and CT are effective in assessing treatment response, with CE-MRI offering slightly superior specificity. Integration of imaging and biomarker data significantly enhances diagnostic accuracy, supporting its potential in optimizing individualized treatment strategies for recurrent EC.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。