Non-contrast CT-based radiomic signature of pericoronary adipose tissue for screening non-calcified plaque

医学 无线电技术 接收机工作特性 放射科 脂肪组织 对比度(视觉) 核医学 内科学 人工智能 计算机科学
作者
Xingyuan Jiang,Zhiqing Shao,Yating Chai,Yingnan Liu,Ye Li
出处
期刊:Physics in Medicine and Biology [IOP Publishing]
卷期号:67 (10): 105004-105004 被引量:5
标识
DOI:10.1088/1361-6560/ac69a7
摘要

Objective.To develop two combined clinical-radiomics models of pericoronary adipose tissue (PCAT) for the presence and characterization of non-calcified plaques on non-contrast CT scan.Approach.Altogether, 431 patients undergoing Coronary Computed Tomography Angiography from March 2019 to June 2021 who had complete data were enrolled, including 173 patients with non-calcified plaques of the right coronary artery(RCA) and 258 with no abnormality. PCAT was segmented around the proximal RCA on non-contrast CT scan (calcium score acquisition). Two best models were established by screening features and classifiers respectively using FeAture Explorer software. Model 1 distinguished normal coronary arteries from those with non-calcified plaques, and model 2 distinguished vulnerable plaques in non-calcified plaques. Performance was assessed by the area under the receiver operating characteristic curve (AUC-ROC).Main results.4 and 9 features were selected for the establishment of the radiomics model respectively through Model 1 and 2. In the test group, the AUC values, sensitivity, specificity and accuracy were 0.833%, 78.3%, 80.8%, 76.6% and 0.7467%, 75.0%, 77.8%, 73.5%, respectively. The combined model including radiomics features and independent clinical factors yielded an AUC, sensitivity, specificity and accuracy of 0.896%, 81.4%, 86.5%, 77.9% for model 1 and 0.752%, 75.0%, 77.8%, 73.5% for model 2.Significance.The combined clinical-radiomics models based on non-contrast CT images of PCAT had good diagnostic efficacy for non-calcified and vulnerable plaques.
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
1秒前
yegechuanqi发布了新的文献求助10
1秒前
鱼鱼完成签到,获得积分10
1秒前
2秒前
2秒前
2秒前
ZZ完成签到,获得积分10
4秒前
4秒前
正直的文涛完成签到,获得积分10
5秒前
minifox发布了新的文献求助10
5秒前
6秒前
6秒前
7秒前
9秒前
阳光沛柔发布了新的文献求助10
9秒前
鱼鱼鱼完成签到,获得积分20
9秒前
善学以致用应助TingtingGZ采纳,获得10
9秒前
易拉罐罐发布了新的文献求助10
10秒前
超级翰完成签到 ,获得积分10
10秒前
10秒前
pp‘s完成签到,获得积分10
11秒前
minifox完成签到,获得积分10
11秒前
壮观的涵柏完成签到,获得积分10
11秒前
12秒前
量子星尘发布了新的文献求助10
12秒前
鱼鱼鱼发布了新的文献求助10
13秒前
14秒前
知槿发布了新的文献求助10
16秒前
17秒前
欣__发布了新的文献求助10
19秒前
小螃蟹发布了新的文献求助10
20秒前
情怀应助ll采纳,获得10
21秒前
21秒前
加油完成签到 ,获得积分10
22秒前
认真元灵发布了新的文献求助10
23秒前
23秒前
zechinlee完成签到 ,获得积分10
24秒前
战斗大排排完成签到,获得积分20
24秒前
英俊的铭应助yegechuanqi采纳,获得10
25秒前
量子星尘发布了新的文献求助10
26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
Alloy Phase Diagrams 1000
Introduction to Early Childhood Education 1000
2025-2031年中国兽用抗生素行业发展深度调研与未来趋势报告 1000
List of 1,091 Public Pension Profiles by Region 901
Item Response Theory 600
Historical Dictionary of British Intelligence (2014 / 2nd EDITION!) 500
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 5425342
求助须知:如何正确求助?哪些是违规求助? 4539399
关于积分的说明 14167889
捐赠科研通 4456910
什么是DOI,文献DOI怎么找? 2444339
邀请新用户注册赠送积分活动 1435316
关于科研通互助平台的介绍 1412740