斑块分析划分冠状动脉疾病报告和数据系统(CAD-RADS)狭窄和斑块负担类别:斑块特征、脂肪衰减指数、冠状动脉计算机断层扫描分流储备以及狭窄和钙化组合的关联。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-06-17 DOI:10.1002/clc.24305
Wenxi Chen, Jiyan Nie, Mingyu Zhang, Zhi Zhu, Yuanyong Zhou, Qingde Wu, Xuxia He
{"title":"斑块分析划分冠状动脉疾病报告和数据系统(CAD-RADS)狭窄和斑块负担类别:斑块特征、脂肪衰减指数、冠状动脉计算机断层扫描分流储备以及狭窄和钙化组合的关联。","authors":"Wenxi Chen,&nbsp;Jiyan Nie,&nbsp;Mingyu Zhang,&nbsp;Zhi Zhu,&nbsp;Yuanyong Zhou,&nbsp;Qingde Wu,&nbsp;Xuxia He","doi":"10.1002/clc.24305","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>The coronary artery disease-reporting and data system (CAD-RADS) 2.0 is used to standardize the reporting of coronary computed tomography angiography (CCTA) results. Artificial intelligence software can quantify the plaque composition, fat attenuation index, and fractional flow reserve.</p>\n </section>\n \n <section>\n \n <h3> Objective</h3>\n \n <p>To analyze plaque features of varying severity in patients with a combination of CAD-RADS stenosis and plaque burden categorization and establish a random forest classification model.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>The data of 100 patients treated between April 2021 and February 2022 were retrospectively collected. The most severe plaque observed in each patient was the target lesion. Patients were categorized into three groups according to CAD-RADS: CAD-RADS 1−2 + P0−2, CAD-RADS 3−4B + P0−2, and CAD-RADS 3−4B + P3−4. Differences and correlations between variables were assessed between groups. AUC, accuracy, precision, recall, and F1 score were used to evaluate the diagnostic performance.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>A total of 100 patients and 178 arteries were included. The differences of computed tomography fractional flow reserve (CT-FFR) (<i>H</i> = 23.921, <i>p</i> &lt; 0.001), the volume of lipid component (<i>H</i> = 12.996, <i>p</i> = 0.002), the volume of fibro-lipid component (<i>H</i> = 8.692, <i>p</i> = 0.013), the proportion of lipid component volume (<i>H</i> = 22.038, <i>p</i> &lt; 0.001), the proportion of fibro-lipid component volume (<i>H</i> = 11.731, <i>p</i> = 0.003), the proportion of calcification component volume (<i>H</i> = 11.049, <i>p</i> = 0.004), and plaque type (<i>χ</i><sup>2</sup> = 18.110, <i>p</i> = 0.001) was statistically significant.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>CT-FFR, volume and proportion of lipid and fibro-lipid components of plaques, the proportion of calcified components, and plaque type were valuable for CAD-RADS stenosis + plaque burden classification, especially CT-FFR, volume, and proportion of lipid and fibro-lipid components. The model built using the random forest was better than the clinical model (AUC: 0.874 vs. 0.647).</p>\n </section>\n </div>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11181293/pdf/","citationCount":"0","resultStr":"{\"title\":\"The Plaque Analysis Classifies the Coronary Artery Disease-Reporting and Data System (CAD-RADS) Stenosis and Plaque Burden Categories: Association of the Plaque Features, Fat Attenuation Index, Coronary Computed Tomography Fractional Flow Reserve, and the Combination of Stenosis and Calcification\",\"authors\":\"Wenxi Chen,&nbsp;Jiyan Nie,&nbsp;Mingyu Zhang,&nbsp;Zhi Zhu,&nbsp;Yuanyong Zhou,&nbsp;Qingde Wu,&nbsp;Xuxia He\",\"doi\":\"10.1002/clc.24305\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>The coronary artery disease-reporting and data system (CAD-RADS) 2.0 is used to standardize the reporting of coronary computed tomography angiography (CCTA) results. Artificial intelligence software can quantify the plaque composition, fat attenuation index, and fractional flow reserve.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Objective</h3>\\n \\n <p>To analyze plaque features of varying severity in patients with a combination of CAD-RADS stenosis and plaque burden categorization and establish a random forest classification model.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>The data of 100 patients treated between April 2021 and February 2022 were retrospectively collected. The most severe plaque observed in each patient was the target lesion. Patients were categorized into three groups according to CAD-RADS: CAD-RADS 1−2 + P0−2, CAD-RADS 3−4B + P0−2, and CAD-RADS 3−4B + P3−4. Differences and correlations between variables were assessed between groups. AUC, accuracy, precision, recall, and F1 score were used to evaluate the diagnostic performance.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>A total of 100 patients and 178 arteries were included. The differences of computed tomography fractional flow reserve (CT-FFR) (<i>H</i> = 23.921, <i>p</i> &lt; 0.001), the volume of lipid component (<i>H</i> = 12.996, <i>p</i> = 0.002), the volume of fibro-lipid component (<i>H</i> = 8.692, <i>p</i> = 0.013), the proportion of lipid component volume (<i>H</i> = 22.038, <i>p</i> &lt; 0.001), the proportion of fibro-lipid component volume (<i>H</i> = 11.731, <i>p</i> = 0.003), the proportion of calcification component volume (<i>H</i> = 11.049, <i>p</i> = 0.004), and plaque type (<i>χ</i><sup>2</sup> = 18.110, <i>p</i> = 0.001) was statistically significant.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>CT-FFR, volume and proportion of lipid and fibro-lipid components of plaques, the proportion of calcified components, and plaque type were valuable for CAD-RADS stenosis + plaque burden classification, especially CT-FFR, volume, and proportion of lipid and fibro-lipid components. The model built using the random forest was better than the clinical model (AUC: 0.874 vs. 0.647).</p>\\n </section>\\n </div>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11181293/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/clc.24305\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/clc.24305","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0

摘要

背景:冠状动脉疾病报告和数据系统(CAD-RADS)2.0 用于规范冠状动脉计算机断层扫描血管造影(CCTA)结果的报告。人工智能软件可量化斑块成分、脂肪衰减指数和分数血流储备:结合 CAD-RADS 狭窄程度和斑块负荷分类,分析患者不同严重程度的斑块特征,并建立随机森林分类模型:回顾性收集2021年4月至2022年2月期间接受治疗的100名患者的数据。每位患者观察到的最严重斑块为靶病变。根据 CAD-RADS 将患者分为三组:CAD-RADS 1-2 + P0-2、CAD-RADS 3-4B + P0-2、CAD-RADS 3-4B + P3-4。对各组之间变量的差异和相关性进行了评估。采用AUC、准确度、精确度、召回率和F1评分来评估诊断性能:结果:共纳入 100 名患者和 178 条动脉。结果:共纳入 100 名患者和 178 条动脉,计算机断层扫描血流储备分数(CT-FFR)(H = 23.921,P 2 = 18.110,P = 0.001)差异具有统计学意义:结论:CT-FFR、斑块中脂质和纤维脂质成分的体积和比例、钙化成分的比例以及斑块类型对CAD-RADS狭窄+斑块负荷分类有价值,尤其是CT-FFR、体积以及脂质和纤维脂质成分的比例。使用随机森林建立的模型优于临床模型(AUC:0.874 对 0.647)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
The Plaque Analysis Classifies the Coronary Artery Disease-Reporting and Data System (CAD-RADS) Stenosis and Plaque Burden Categories: Association of the Plaque Features, Fat Attenuation Index, Coronary Computed Tomography Fractional Flow Reserve, and the Combination of Stenosis and Calcification

Background

The coronary artery disease-reporting and data system (CAD-RADS) 2.0 is used to standardize the reporting of coronary computed tomography angiography (CCTA) results. Artificial intelligence software can quantify the plaque composition, fat attenuation index, and fractional flow reserve.

Objective

To analyze plaque features of varying severity in patients with a combination of CAD-RADS stenosis and plaque burden categorization and establish a random forest classification model.

Methods

The data of 100 patients treated between April 2021 and February 2022 were retrospectively collected. The most severe plaque observed in each patient was the target lesion. Patients were categorized into three groups according to CAD-RADS: CAD-RADS 1−2 + P0−2, CAD-RADS 3−4B + P0−2, and CAD-RADS 3−4B + P3−4. Differences and correlations between variables were assessed between groups. AUC, accuracy, precision, recall, and F1 score were used to evaluate the diagnostic performance.

Results

A total of 100 patients and 178 arteries were included. The differences of computed tomography fractional flow reserve (CT-FFR) (H = 23.921, p < 0.001), the volume of lipid component (H = 12.996, p = 0.002), the volume of fibro-lipid component (H = 8.692, p = 0.013), the proportion of lipid component volume (H = 22.038, p < 0.001), the proportion of fibro-lipid component volume (H = 11.731, p = 0.003), the proportion of calcification component volume (H = 11.049, p = 0.004), and plaque type (χ2 = 18.110, p = 0.001) was statistically significant.

Conclusion

CT-FFR, volume and proportion of lipid and fibro-lipid components of plaques, the proportion of calcified components, and plaque type were valuable for CAD-RADS stenosis + plaque burden classification, especially CT-FFR, volume, and proportion of lipid and fibro-lipid components. The model built using the random forest was better than the clinical model (AUC: 0.874 vs. 0.647).

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
期刊最新文献
A Systematic Review of Sleep Disturbance in Idiopathic Intracranial Hypertension. Advancing Patient Education in Idiopathic Intracranial Hypertension: The Promise of Large Language Models. Anti-Myelin-Associated Glycoprotein Neuropathy: Recent Developments. Approach to Managing the Initial Presentation of Multiple Sclerosis: A Worldwide Practice Survey. Association Between LACE+ Index Risk Category and 90-Day Mortality After Stroke.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1