Characteristics of Non-mass Enhancement in Contrast-enhanced Breast MRI and Associations with Malignancy

恶性肿瘤 对比度(视觉) 对比度增强 医学 乳房磁振造影 磁共振成像 放射科 肿瘤科 乳腺癌 内科学 乳腺摄影术 计算机科学 癌症 人工智能
作者
Kamber Göksu,Ahmet Vural,Ahmet Kahraman
出处
期刊:Journal of Cancer [Ivyspring International Publisher]
卷期号:16 (10): 3103-3111
标识
DOI:10.7150/jca.114087
摘要

Background: Magnetic resonance imaging (MRI) has a limited role in distinguishing non-mass enhancement (NME) lesions as benign or malignant and determining whether the lesions are invasive or not. In this study, we aimed to investigate the differences in MRI of benign and malignant NME lesions and to determine the relationship between the pattern of enhancement in NME lesions and histopathologic diagnosis. Materials and methods: Breast MRI examinations (n=5214) performed at the study institution between January 2018 and July 2024 were evaluated. We enrolled 460 patients in the study. NME lesions were classified according to the BI-RADS atlas. In addition, linear enhancements were divided into branching and non-branching. Factors showing significant associations in univariate analyses were evaluated with multivariate analyses using the logistic regression model. The assessments were performed by two radiologists who are experienced in breast imaging. Results: This study included 460 NME lesions (342 benign and 118 malignant). Focal and segmental distribution, dynamic enhancement features, Type I (persistent) and Type III (wash-out) dynamic curve modes, and clustered-ring internal enhancement pattern features showed statistically significant differences in terms of differentiating benign from malignant (P<0.05). Heterogeneous enhancement gave significant results in distinguishing invasive carcinoma from ductal carcinoma in situ (DCIS) (P<0.05). Wash-out type curve from dynamic enhancement curves was also seen at a higher rate in invasive carcinomas. Although the general results are similar to previous studies, in our study, unlike other studies, enhancements showing linear distribution were divided into two groups branching and non-branching, and lesion size was measured. It was observed that branching enhancements and lesion sizes greater than 15 mm significantly indicated malignancy (p<0.05). Conclusions: MRI is a valuable way to identify malignant NME lesions and may be useful in determining whether the lesions are invasive or not. Evaluating NME lesions with breast MRI can help decide on biopsy when branching types of lesions with linear distribution and lesions greater than 15 mm are detected.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
JamesPei应助蜗牛采纳,获得10
刚刚
yu发布了新的文献求助10
1秒前
小猪找库里完成签到,获得积分10
1秒前
量子星尘发布了新的文献求助10
1秒前
Lee发布了新的文献求助10
1秒前
capx完成签到,获得积分10
2秒前
Frankyu完成签到,获得积分10
2秒前
温与暖完成签到,获得积分10
2秒前
3秒前
匹夫完成签到,获得积分10
3秒前
勤奋花瓣完成签到 ,获得积分10
3秒前
keyanli完成签到,获得积分10
3秒前
三木埃尔完成签到,获得积分10
4秒前
传奇3应助Gaojin锦采纳,获得10
4秒前
4秒前
4秒前
元小夏完成签到,获得积分0
5秒前
小可爱123456完成签到,获得积分10
5秒前
油条发布了新的文献求助10
5秒前
rr发布了新的文献求助10
5秒前
Present完成签到,获得积分10
5秒前
柒_l完成签到,获得积分10
6秒前
程小柒发布了新的文献求助10
6秒前
阳光悟空完成签到,获得积分10
6秒前
完美世界应助栀子采纳,获得10
7秒前
研友_ZzaKqn完成签到,获得积分0
7秒前
liz发布了新的文献求助10
8秒前
尘中磨镜人完成签到,获得积分10
8秒前
中科路2020完成签到,获得积分10
8秒前
菜菜就爱玩完成签到,获得积分10
8秒前
失眠雨完成签到,获得积分10
9秒前
淡淡白枫完成签到,获得积分20
10秒前
无极微光应助rhrhn采纳,获得20
11秒前
祥辉NCU完成签到,获得积分10
11秒前
Chole完成签到 ,获得积分10
11秒前
Shirley完成签到,获得积分10
11秒前
11秒前
雨姐科研应助匹夫采纳,获得10
12秒前
依古比古完成签到 ,获得积分10
12秒前
xueerbx发布了新的文献求助10
12秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
List of 1,091 Public Pension Profiles by Region 1001
EEG in Childhood Epilepsy: Initial Presentation & Long-Term Follow-Up 500
Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences 500
On the application of advanced modeling tools to the SLB analysis in NuScale. Part I: TRACE/PARCS, TRACE/PANTHER and ATHLET/DYN3D 500
L-Arginine Encapsulated Mesoporous MCM-41 Nanoparticles: A Study on In Vitro Release as Well as Kinetics 500
Haematolymphoid Tumours (Part A and Part B, WHO Classification of Tumours, 5th Edition, Volume 11) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5470764
求助须知:如何正确求助?哪些是违规求助? 4573616
关于积分的说明 14339604
捐赠科研通 4500701
什么是DOI,文献DOI怎么找? 2465922
邀请新用户注册赠送积分活动 1454143
关于科研通互助平台的介绍 1428858