Multiparametric MRI Features of Seromucinous and Mucinous Benign and Borderline Ovarian Tumors.

IF 1.4 4区 医学 Q4 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Safa Özyılmaz, Fatma Kulalı
{"title":"Multiparametric MRI Features of Seromucinous and Mucinous Benign and Borderline Ovarian Tumors.","authors":"Safa Özyılmaz, Fatma Kulalı","doi":"10.1097/RCT.0000000000001930","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To evaluate morphologic and quantitative MRI features associated with seromucinous and mucinous ovarian tumors of benign and borderline histology, with emphasis on their complementary role within structured preoperative imaging assessment.</p><p><strong>Methods: </strong>This retrospective single-center study included 76 women with 79 histopathologically confirmed mucinous or seromucinous ovarian tumors of benign or borderline histology who underwent preoperative pelvic MRI between 2011 and 2025. Tumors were classified as mucinous benign, mucinous borderline, seromucinous benign, or seromucinous borderline. MRI evaluation included morphologic features (tumor size, loculation number, septal thickness, and mural nodule presence) and quantitative analyses using signal intensity ratios on T1- and T2-weighted images (SIR-T1, SIR-T2). Enhancement and diffusion metrics were assessed for mural nodules when present. Multinomial logistic regression identified independent imaging predictors, and receiver operating characteristic (ROC) analysis evaluated diagnostic performance.</p><p><strong>Results: </strong>Tumor subtypes demonstrated distinct morphologic and signal-based patterns. Borderline tumors showed a higher prevalence of mural nodules than benign tumors. SIR-T1 differed significantly among subgroups and remained associated with tumor subtype in exploratory multivariable analysis. Overall intergroup differences were observed for tumor size, loculation number, SIR-T1, and mural nodule presence; however, these findings should be interpreted cautiously given the limited subgroup sizes. ROC analysis showed that SIR-T1 differentiated seromucinous borderline from mucinous benign tumors (AUC=0.801), while tumor size differentiated seromucinous benign from mucinous borderline tumors (AUC=0.796). Inter- and intraobserver agreement was good to excellent.</p><p><strong>Conclusions: </strong>Multiparametric MRI assessment integrating morphologic features with selected signal-based metrics may provide complementary information for the preoperative characterization of mucinous and seromucinous ovarian tumors. These findings should be interpreted as exploratory and adjunctive to structured MRI assessment frameworks such as O-RADS MRI rather than as standalone diagnostic criteria.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer Assisted Tomography","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/RCT.0000000000001930","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: To evaluate morphologic and quantitative MRI features associated with seromucinous and mucinous ovarian tumors of benign and borderline histology, with emphasis on their complementary role within structured preoperative imaging assessment.

Methods: This retrospective single-center study included 76 women with 79 histopathologically confirmed mucinous or seromucinous ovarian tumors of benign or borderline histology who underwent preoperative pelvic MRI between 2011 and 2025. Tumors were classified as mucinous benign, mucinous borderline, seromucinous benign, or seromucinous borderline. MRI evaluation included morphologic features (tumor size, loculation number, septal thickness, and mural nodule presence) and quantitative analyses using signal intensity ratios on T1- and T2-weighted images (SIR-T1, SIR-T2). Enhancement and diffusion metrics were assessed for mural nodules when present. Multinomial logistic regression identified independent imaging predictors, and receiver operating characteristic (ROC) analysis evaluated diagnostic performance.

Results: Tumor subtypes demonstrated distinct morphologic and signal-based patterns. Borderline tumors showed a higher prevalence of mural nodules than benign tumors. SIR-T1 differed significantly among subgroups and remained associated with tumor subtype in exploratory multivariable analysis. Overall intergroup differences were observed for tumor size, loculation number, SIR-T1, and mural nodule presence; however, these findings should be interpreted cautiously given the limited subgroup sizes. ROC analysis showed that SIR-T1 differentiated seromucinous borderline from mucinous benign tumors (AUC=0.801), while tumor size differentiated seromucinous benign from mucinous borderline tumors (AUC=0.796). Inter- and intraobserver agreement was good to excellent.

Conclusions: Multiparametric MRI assessment integrating morphologic features with selected signal-based metrics may provide complementary information for the preoperative characterization of mucinous and seromucinous ovarian tumors. These findings should be interpreted as exploratory and adjunctive to structured MRI assessment frameworks such as O-RADS MRI rather than as standalone diagnostic criteria.

卵巢浆液性和黏液性良性和交界性肿瘤的多参数MRI特征。
目的:评价卵巢浆液粘液和黏液性肿瘤良性和交界性组织学的形态学和定量MRI特征,强调它们在结构化术前影像学评估中的补充作用。方法:这项回顾性单中心研究纳入了76名女性,其中79例组织病理学证实为良性或交界性组织学的粘液或浆液性卵巢肿瘤,并于2011年至2025年间行术前盆腔MRI检查。肿瘤分为黏液性良性、黏液性交界性、浆液性良性或浆液性交界性。MRI评估包括形态学特征(肿瘤大小、定位数量、间隔厚度和壁结节的存在)和定量分析,使用T1和t2加权图像(SIR-T1, SIR-T2)的信号强度比。当存在壁结节时,评估增强和扩散指标。多项逻辑回归确定了独立的影像学预测因子,受试者工作特征(ROC)分析评估了诊断性能。结果:肿瘤亚型表现出不同的形态和基于信号的模式。交界性肿瘤壁结节的发生率高于良性肿瘤。探索性多变量分析显示,SIR-T1在不同亚组间差异显著,且仍与肿瘤亚型相关。观察肿瘤大小、定位数量、SIR-T1和壁结节存在的总体组间差异;然而,考虑到有限的亚群规模,这些发现应该谨慎解释。ROC分析显示,SIR-T1能区分浆液黏液交界性肿瘤与粘液性良性肿瘤(AUC=0.801),而肿瘤大小能区分浆液黏液性良性肿瘤与粘液性交界性肿瘤(AUC=0.796)。观察员之间和内部的一致意见从好到好。结论:将形态学特征与选定的基于信号的指标相结合的多参数MRI评估可能为卵巢粘液性和浆液性肿瘤的术前特征提供补充信息。这些发现应该被解释为探索性的和辅助的结构化MRI评估框架,如O-RADS MRI,而不是作为独立的诊断标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
2.50
自引率
0.00%
发文量
230
审稿时长
4-8 weeks
期刊介绍: The mission of Journal of Computer Assisted Tomography is to showcase the latest clinical and research developments in CT, MR, and closely related diagnostic techniques. We encourage submission of both original research and review articles that have immediate or promissory clinical applications. Topics of special interest include: 1) functional MR and CT of the brain and body; 2) advanced/innovative MRI techniques (diffusion, perfusion, rapid scanning); and 3) advanced/innovative CT techniques (perfusion, multi-energy, dose-reduction, and processing).
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书