MRI Manifestations of Breast Cancer Stroma and their Role in Predicting Molecular Subtype: A Case-control Study.

IF 1.1 4区 医学 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Current Medical Imaging Reviews Pub Date : 2024-02-26 DOI:10.2174/0115734056287368240213135143
Lanyun Wang, Wenjing Li, Wenjun Yang, Xilin Sun, Yi Ding, Qian Zhao, Weiyan Liu, Xiaoli Xie, Jingjing Xu, Ran Wei, Shizhen Zhu, Yaqiong Ge, Pu-Yeh Wu, Bin Song
{"title":"MRI Manifestations of Breast Cancer Stroma and their Role in Predicting Molecular Subtype: A Case-control Study.","authors":"Lanyun Wang, Wenjing Li, Wenjun Yang, Xilin Sun, Yi Ding, Qian Zhao, Weiyan Liu, Xiaoli Xie, Jingjing Xu, Ran Wei, Shizhen Zhu, Yaqiong Ge, Pu-Yeh Wu, Bin Song","doi":"10.2174/0115734056287368240213135143","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This study explored whether breast MRI manifestations could be used to predict the stroma distribution of breast cancer (BC) and the role of tumor stroma-based MRI manifestations in molecular subtype prediction.</p><p><strong>Methods: </strong>57 patients with pathologically confirmed invasive BC (non-special type) who had lumpy BC on MRI within one week before surgery were retrospectively collected in the study. Stroma distributions were classified according to their characteristics in the pathological sections. The stromal distribution patterns among molecular subtypes were compared with the MRI manifestations of BC with different stroma distribution types (SDTs).</p><p><strong>Results: </strong>SDTs were significantly different and depended on the BC hormone receptor (HR) (P<0.001). There were also significant differences among five SDTs on T2WI, ADC map, internal delayed enhanced features (IDEF), marginal delayed enhanced features (MDEF), and time signal intensity (TSI) curves. Spiculated margin and the absence of type-I TSI were independent predictors for BC with star grid type stroma. The appearance frequency of hypo-intensity on T2WI in HR- BCs was significantly lower (P=0.043) than in HR+ BCs. Star grid stroma and spiculated margin were key factors in predicting HR+ BCs, and the AUC was 0.927 (95% CI: 0.867-0.987).</p><p><strong>Conclusion: </strong>Breast MRI can be used to predict BC's stromal distribution and molecular subtypes.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Medical Imaging Reviews","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/0115734056287368240213135143","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: This study explored whether breast MRI manifestations could be used to predict the stroma distribution of breast cancer (BC) and the role of tumor stroma-based MRI manifestations in molecular subtype prediction.

Methods: 57 patients with pathologically confirmed invasive BC (non-special type) who had lumpy BC on MRI within one week before surgery were retrospectively collected in the study. Stroma distributions were classified according to their characteristics in the pathological sections. The stromal distribution patterns among molecular subtypes were compared with the MRI manifestations of BC with different stroma distribution types (SDTs).

Results: SDTs were significantly different and depended on the BC hormone receptor (HR) (P<0.001). There were also significant differences among five SDTs on T2WI, ADC map, internal delayed enhanced features (IDEF), marginal delayed enhanced features (MDEF), and time signal intensity (TSI) curves. Spiculated margin and the absence of type-I TSI were independent predictors for BC with star grid type stroma. The appearance frequency of hypo-intensity on T2WI in HR- BCs was significantly lower (P=0.043) than in HR+ BCs. Star grid stroma and spiculated margin were key factors in predicting HR+ BCs, and the AUC was 0.927 (95% CI: 0.867-0.987).

Conclusion: Breast MRI can be used to predict BC's stromal distribution and molecular subtypes.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
乳腺癌基质的 MRI 表现及其在预测分子亚型中的作用:病例对照研究
目的:本研究探讨了乳腺磁共振成像表现是否可用于预测乳腺癌(BC)的基质分布以及基于肿瘤基质的磁共振成像表现在分子亚型预测中的作用:方法:该研究回顾性收集了57例经病理确诊的浸润性BC(非特殊类型)患者,这些患者在手术前一周内通过MRI检查发现BC有肿块。根据病理切片中基质分布的特征对其进行分类。将分子亚型间的基质分布模式与不同基质分布类型(SDTs)的BC的MRI表现进行比较:结果:SDTs存在明显差异,并取决于BC的激素受体(HR)(PC结论:乳腺MRI可用于预测乳腺癌:乳腺磁共振成像可用于预测BC的基质分布和分子亚型。
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 去求助
来源期刊
CiteScore
2.60
自引率
0.00%
发文量
246
审稿时长
1 months
期刊介绍: Current Medical Imaging Reviews publishes frontier review articles, original research articles, drug clinical trial studies and guest edited thematic issues on all the latest advances on medical imaging dedicated to clinical research. All relevant areas are covered by the journal, including advances in the diagnosis, instrumentation and therapeutic applications related to all modern medical imaging techniques. The journal is essential reading for all clinicians and researchers involved in medical imaging and diagnosis.
期刊最新文献
Advanced Lung Disease Detection: CBAM-Augmented, Lightweight EfficientNetB2 with Visual Insights. Multiple Pulmonary Sclerosing Haemangiomas with a Cavity: A Case Report and Review of the Literature. An Integrated Approach using YOLOv8 and ResNet, SeResNet & Vision Transformer (ViT) Algorithms based on ROI Fracture Prediction in X-ray Images of the Elbow. Combination of Different Sectional Elastography Techniques with Age to Optimize the Downgrading of Breast BI-RAIDS Class 4a Nodules. Prenatal Three-Dimensional Ultrasound Diagnosis of Dural Sinus Arteriovenous Malformation: An Unusual Case Report.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1