文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

使用 T2 加权序列更准确地描述 MRI 上所见的乳腺肿块。

Using T2-weighted sequences to more accurately characterize breast masses seen on MRI.

机构信息

1 Harvard Medical School, Boston, MA.

出版信息

AJR Am J Roentgenol. 2014 Mar;202(3):W183-90. doi: 10.2214/AJR.13.11266.


DOI:10.2214/AJR.13.11266
PMID:24555613
Abstract

T2-weighted images are a valuable component of the MRI evaluation of breast masses. Edema, hemorrhage, mucus, and cystic fluid within a lesion are clearly depicted on T2-weighted sequences. In general, masses that have high signal intensity on T2-weighted images are benign; however, breast imagers must be aware of such important exceptions as mucinous carcinoma and necrotic tumors.

摘要

T2 加权图像是 MRI 评估乳腺肿块的重要组成部分。病变内的水肿、出血、黏液和囊液在 T2 加权序列上清晰显示。一般来说,在 T2 加权图像上具有高信号强度的肿块是良性的;然而,乳腺成像医师必须注意到一些重要的例外情况,如黏液癌和坏死性肿瘤。

相似文献

[1]
Using T2-weighted sequences to more accurately characterize breast masses seen on MRI.

AJR Am J Roentgenol. 2014-3

[2]
Radiologic and pathologic findings in breast tumors with high signal intensity on T2-weighted MR images.

Radiographics. 2010-3

[3]
Breast carcinomas with strong high-signal intensity on T2-weighted MR images: pathological characteristics and differential diagnosis.

J Magn Reson Imaging. 2007-3

[4]
Mucinous carcinoma of the breast: MRI features of pure and mixed forms with histopathologic correlation.

AJR Am J Roentgenol. 2009-3

[5]
Comparative utility of MRI perfusion with MSIDR and DWIBS for the characterization of breast tumors.

Acta Radiol. 2012-7

[6]
Relationship between contrast enhancement on fluid-attenuated inversion recovery MR sequences and signal intensity on T2-weighted MR images: visual evaluation of brain tumors.

J Magn Reson Imaging. 2005-6

[7]
Chemical shift MRI: is there any contribution to morphologic evaluation of solid breast masses?

Acad Radiol. 2009-10

[8]
Breast lesions: evaluation with dynamic contrast-enhanced T1-weighted MR imaging and with T2*-weighted first-pass perfusion MR imaging.

Radiology. 2000-8

[9]
Diffusion-weighted imaging of mucinous carcinoma of the breast: evaluation of apparent diffusion coefficient and signal intensity in correlation with histologic findings.

AJR Am J Roentgenol. 2009-7

[10]
Clinical significance of magnetic resonance imaging-guided core needle biopsies.

Top Magn Reson Imaging. 2014-12

引用本文的文献

[1]
Development of an Automated CAD System for Lesion Detection in DCE-MRI.

J Imaging Inform Med. 2025-2-20

[2]
External validation of multiparametric magnetic resonance imaging-based decision rules for characterizing breast lesions and comparison to Kaiser score and breast imaging reporting and data system (BI-RADS) category.

Quant Imaging Med Surg. 2025-1-2

[3]
Axillary Lymph Nodes T2 Signal Intensity Characterization in MRI of Patients With Mucinous Breast Cancer: A Pilot Study.

J Breast Imaging. 2025-3-18

[4]
[Importance of parametric and molecular imaging for therapeutic management of breast cancer].

Radiologie (Heidelb). 2025-3

[5]
Clinical-radiomics nomogram based on the fat-suppressed T2 sequence for differentiating luminal and non-luminal breast cancer.

Front Oncol. 2024-10-25

[6]
Study on the classification of benign and malignant breast lesions using a multi-sequence breast MRI fusion radiomics and deep learning model.

Eur J Radiol Open. 2024-10-21

[7]
The potential role of breast MRI in evaluation of triple-negative breast cancer and fibroadenoma of less than 3 cm.

Transl Cancer Res. 2024-8-31

[8]
The association of magnetic resonance imaging features with five molecular subtypes of breast cancer.

Eur J Radiol Open. 2024-6-28

[9]
Relaxation-Diffusion T2-ADC Correlations in Breast Cancer Patients: A Spatiotemporally Encoded 3T MRI Assessment.

Diagnostics (Basel). 2023-11-23

[10]
Identification of breast lesion through integrated study of gorilla troops optimization and rotation-based learning from MRI images.

Sci Rep. 2023-7-18

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索