Differentiating axillary lymph node metastasis in invasive breast cancer patients: A comparison of radiomic signatures from multiparametric breast MR sequences

乳腺癌 医学 淋巴结 精确检验 转移 曼惠特尼U检验 磁共振成像 接收机工作特性 乳房磁振造影 腋窝淋巴结 前哨淋巴结 动态增强MRI 线性判别分析 放射科 核医学 癌症 乳腺摄影术 病理 内科学 计算机科学 人工智能
作者
Ruimei Chai,He Ma,Mingjie Xu,Dooman Arefan,Xiaoyu Cui,Yi Liu,Lina Zhang,Shandong Wu,Ke Xu
出处
期刊:Journal of Magnetic Resonance Imaging [Wiley]
卷期号:50 (4): 1125-1132 被引量:64
标识
DOI:10.1002/jmri.26701
摘要

Background The axillary lymph node status is critical for breast cancer staging and individualized treatment planning. Purpose To assess the effect of determining axillary lymph node (ALN) metastasis by breast MRI‐derived radiomic signatures, and compare the discriminating abilities of different MR sequences. Study Type Retrospective. Population In all, 120 breast cancer patients, 59 with ALN metastasis and 61 without metastasis, all confirmed by pathology. Field Strength/Sequence 3 .0T scanner with T 1 ‐weighted imaging, T 2 ‐weighted imaging, diffusion‐weighted imaging, and dynamic contrast‐enhanced (DCE) sequences. Assessment Typical morphological and texture features of the segmented tumor were extracted from four sequences, ie, T 1 WI, T 2 WI, DWI, and the second postcontrast phase (CE2) of the dynamic contrast‐enhanced sequences. Additional contrast enhancement kinetic features were extracted from all DCE sequences (one pre‐ and seven postcontrast phases). Linear discriminant analysis classifiers were built and compared when using features from an individual sequence or the combination of the sequences in differentiating the ALN metastasis status. Statistical Tests Mann–Whitney U ‐test, Fisher's exact test, least absolute shrinkage selection operator (LASSO) regression, and receiver operating characteristic analysis were performed. Results The accuracy/AUC of the four sequences was 79%/0.87, 77%/0.85, 74%/0.79, and 79%/0.85 for the T 1 WI, CE2, T 2 WI, and DWI, respectively. When CE2 was augmented by adding kinetic features, the model achieved the highest performance (accuracy = 0.86 and AUC = 0.91). When all features from the four sequences and the kinetics were combined, it did not lead to a further increase in the performance ( P = 0.48). Data Conclusion Breast tumor's radiomic signatures from preoperative breast MRI sequences are associated with the ALN metastasis status, where CE2 phase and the contrast enhancement kinetic features lead to the highest classification effect. Level of Evidence 3 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2019;50:1125–1132.
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
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
yang发布了新的文献求助10
1秒前
平淡的灵竹完成签到,获得积分10
1秒前
852应助花卷采纳,获得10
1秒前
1秒前
嗷嗷发布了新的文献求助10
2秒前
舒心海白发布了新的文献求助10
2秒前
萍p发布了新的文献求助10
2秒前
AARON完成签到,获得积分10
2秒前
清脆烙完成签到,获得积分10
3秒前
树德完成签到,获得积分10
3秒前
莹Y完成签到,获得积分10
3秒前
3秒前
言笑晏晏发布了新的文献求助30
4秒前
4秒前
5秒前
映雪发布了新的文献求助10
5秒前
6秒前
看不懂发布了新的文献求助10
6秒前
7秒前
7秒前
缥缈的谷雪完成签到,获得积分10
8秒前
WN发布了新的文献求助10
9秒前
今后应助MiyaGuo采纳,获得10
9秒前
10秒前
舒心海白完成签到,获得积分10
10秒前
land发布了新的文献求助10
11秒前
萧骞应助ychope采纳,获得10
11秒前
完美世界应助jjjddyy采纳,获得10
11秒前
501757473发布了新的文献求助30
11秒前
11秒前
杨xy完成签到,获得积分10
11秒前
甜美的莫茗完成签到,获得积分10
11秒前
科研通AI6.4应助Eunice采纳,获得10
12秒前
12秒前
13秒前
跳跃靖发布了新的文献求助10
13秒前
13秒前
Hello应助echo采纳,获得10
13秒前
生动的厉发布了新的文献求助10
14秒前
仟111完成签到 ,获得积分10
15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
Geist der Kunst und Kultur 1000
Resistance Spot Welding Dataset for Automobile Body-in-White Quality Analysis 748
日本現代怪異事典 副読本 700
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 650
Machine Learning for Asset Management and Pricing 600
Numerical analysis of the coupled atmosphere-ocean models (CAO II). II 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7395964
求助须知:如何正确求助?哪些是违规求助? 9001996
关于积分的说明 19160546
捐赠科研通 7031569
什么是DOI,文献DOI怎么找? 3229946
关于科研通互助平台的介绍 2392416
邀请新用户注册赠送积分活动 2211578