The association between molecular biomarkers and ultrasonographic radiomics features for triple negative invasive breast carcinoma

医学 病态的 免疫组织化学 三阴性乳腺癌 超声波 特征(语言学) 乳腺超声检查 乳腺癌 乳腺癌 无线电技术 接收机工作特性 放射科 病理 肿瘤科 人工智能 内科学 癌症 乳腺摄影术 计算机科学 语言学 哲学
作者
Jiawei Li,Zhou Fang,Jin Zhou,Yuyang Tong,Zhaoting Shi,Cai Chang,Yi Guo,Jinhua Yu,Yuanyuan Wang
出处
期刊:Chinese Journal of Ultrasonography [Chinese Medical Association]
卷期号:28 (2): 137-143 被引量:2
标识
DOI:10.3760/cma.j.issn.1004-4477.2019.02.010
摘要

Objective To evaluate the association between quantitative ultrasonographic features and clinical, pathological and immunohistochemical features of triple negative invasive breast carcinoma(TNBC). Methods With the ethical approval, 96 patients who were pathologically confirmed as TNBC were retrospectively reviewed. All patients were sub-grouped according to age, tumor size, pathological grade, Ki67 expression level and human epidermal growth factor receptor 2 (HER-2) score.Ultrasound images were segmented for the breast carcinoma mass using a phase-based active contour model. The high-throughput radiomics features were extracted based on the two-dimensional sonographic features. There were 460 features extracted from each ultrasound image. A series of computer aided algorithms including K-svd algorithm, sparse representation, support vector machine (SVM) and radial basis function were used to determine the high-throughput sonographic features that were highly correlated to clinical, pathological and immunohistochemical features of TNBC. The performance efficacy was expressed by accuracy and area under curve (AUC) of the ROC curve. Results The high-throughput ultrasonographic features of invasive TNBC could predict its pathological grade, Ki67 level and HER-2 score with the accuracy 92.2%-96.9% and AUC 98.7%-99.9%. There were 82 radiomics features selected for predicting the pathological grade of TNBC, the feature with the maximum weight was the elliptic-normalized eccentricity based on morphological features. There were 100 features selected for predicting the Ki67 expression level, the feature with the maximum weight was the standard deviation of the annular region based on the boundary texture features. There were 85 features selected for the prediction of HER-2 score, the most powerful parameter was the intensity based on NGTDM texture features. Conclusions Quantitative high-throughput ultrasonographic features are correlated with the pathological and immunohistochemical characteristics of invasive TNBC. High-throughput ultrasonographic features are valuable in predicting biological behavior of TNBC. Key words: Ultrasonography; Breast neoplasms; Pathology; Radiomics; Immunohistochemistry

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
朱晖完成签到 ,获得积分10
1秒前
3秒前
852应助涛哥来科研采纳,获得10
3秒前
3秒前
v2发布了新的文献求助10
4秒前
4秒前
背后中心完成签到,获得积分10
5秒前
5秒前
MYC007完成签到 ,获得积分10
6秒前
xurui_s完成签到 ,获得积分10
7秒前
阳光发布了新的文献求助10
8秒前
沈茜发布了新的文献求助10
9秒前
9秒前
小小牛马应助减简采纳,获得10
9秒前
科研通AI6.3应助减简采纳,获得10
9秒前
小小牛马应助减简采纳,获得10
9秒前
科研通AI6.4应助减简采纳,获得10
9秒前
科研通AI6.3应助减简采纳,获得10
9秒前
科研通AI6.4应助减简采纳,获得10
10秒前
烟花应助减简采纳,获得10
10秒前
小小牛马应助减简采纳,获得10
10秒前
小小牛马应助减简采纳,获得10
10秒前
科研通AI6.3应助减简采纳,获得10
10秒前
FashionBoy应助热心果汁采纳,获得10
11秒前
流光闪过的线完成签到 ,获得积分10
13秒前
v2完成签到,获得积分10
14秒前
14秒前
MoonByul完成签到,获得积分10
15秒前
Akim应助聪慧的盼夏采纳,获得10
16秒前
16秒前
星辉的斑斓完成签到 ,获得积分0
17秒前
20秒前
20秒前
小白完成签到 ,获得积分0
21秒前
科研小裴完成签到,获得积分10
21秒前
yun完成签到,获得积分10
21秒前
22秒前
24秒前
ToMoTT完成签到,获得积分10
25秒前
万能图书馆应助怕黑若云采纳,获得10
25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
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场规模及竞争格局分析报告 1000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Resiliency Scale for Adolescents--Chinese Version 600
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
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 7319933
求助须知:如何正确求助?哪些是违规求助? 8935611
关于积分的说明 18942805
捐赠科研通 6978421
什么是DOI,文献DOI怎么找? 3214430
关于科研通互助平台的介绍 2382311
邀请新用户注册赠送积分活动 2193521