Special Types of Breast Cancer: Clinical Behavior and Radiological Appearance.

IF 2.7 Q3 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY Journal of Imaging Pub Date : 2024-07-29 DOI:10.3390/jimaging10080182
Marco Conti, Francesca Morciano, Silvia Amodeo, Elisabetta Gori, Giovanna Romanucci, Paolo Belli, Oscar Tommasini, Francesca Fornasa, Rossella Rella
{"title":"Special Types of Breast Cancer: Clinical Behavior and Radiological Appearance.","authors":"Marco Conti, Francesca Morciano, Silvia Amodeo, Elisabetta Gori, Giovanna Romanucci, Paolo Belli, Oscar Tommasini, Francesca Fornasa, Rossella Rella","doi":"10.3390/jimaging10080182","DOIUrl":null,"url":null,"abstract":"<p><p>Breast cancer is a complex disease that includes entities with different characteristics, behaviors, and responses to treatment. Breast cancers are categorized into subgroups based on histological type and grade, and these subgroups affect clinical presentation and oncological outcomes. The subgroup of \"special types\" encompasses all those breast cancers with insufficient features to belong to the subgroup \"invasive ductal carcinoma not otherwise specified\". These cancers account for around 25% of all cases, some of them having a relatively good prognosis despite high histological grade. The purpose of this paper is to review and illustrate the radiological appearance of each special type, highlighting insights and pitfalls to guide breast radiologists in their routine work.</p>","PeriodicalId":37035,"journal":{"name":"Journal of Imaging","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11355320/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/jimaging10080182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Breast cancer is a complex disease that includes entities with different characteristics, behaviors, and responses to treatment. Breast cancers are categorized into subgroups based on histological type and grade, and these subgroups affect clinical presentation and oncological outcomes. The subgroup of "special types" encompasses all those breast cancers with insufficient features to belong to the subgroup "invasive ductal carcinoma not otherwise specified". These cancers account for around 25% of all cases, some of them having a relatively good prognosis despite high histological grade. The purpose of this paper is to review and illustrate the radiological appearance of each special type, highlighting insights and pitfalls to guide breast radiologists in their routine work.

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
特殊类型的乳腺癌:临床表现和放射学外观。
乳腺癌是一种复杂的疾病,包括具有不同特征、行为和治疗反应的实体。乳腺癌根据组织学类型和分级被分为不同的亚组,这些亚组影响着临床表现和肿瘤治疗效果。特殊类型 "亚组包括所有特征不足以归入 "未另作说明的浸润性导管癌 "亚组的乳腺癌。这些癌症约占所有病例的 25%,其中一些尽管组织学分级较高,但预后相对较好。本文旨在回顾和说明每种特殊类型的放射学表现,重点介绍其见解和误区,以指导乳腺放射科医生的日常工作。
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
Journal of Imaging
Journal of Imaging Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
5.90
自引率
6.20%
发文量
303
审稿时长
7 weeks
期刊最新文献
Efficient End-to-End Convolutional Architecture for Point-of-Gaze Estimation. Comparison of Visual and Quantra Software Mammographic Density Assessment According to BI-RADS® in 2D and 3D Images. A Multi-Task Model for Pulmonary Nodule Segmentation and Classification. Convolutional Neural Network-Machine Learning Model: Hybrid Model for Meningioma Tumour and Healthy Brain Classification. Historical Blurry Video-Based Face Recognition.
×
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