二维冠状动脉造影图像计算血流储备分数的有效性和诊断性能。

IF 0.8 4区 医学 Q4 CARDIAC & CARDIOVASCULAR SYSTEMS
Vahid Mohammadi, Massoud Ghasemi, Reza Rahmani, Maryam Mehrpooya, Hamidreza Babakhani, Akbar Shafiee, Mohammad Sadeghian
{"title":"二维冠状动脉造影图像计算血流储备分数的有效性和诊断性能。","authors":"Vahid Mohammadi,&nbsp;Massoud Ghasemi,&nbsp;Reza Rahmani,&nbsp;Maryam Mehrpooya,&nbsp;Hamidreza Babakhani,&nbsp;Akbar Shafiee,&nbsp;Mohammad Sadeghian","doi":"10.14503/THIJ-20-7410","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Measurement of fractional flow reserve (FFR) is the gold standard for determining the physiologic significance of coronary artery stenosis, but newer software programs can calculate the FFR from 2-dimensional angiography images.</p><p><strong>Methods: </strong>A retrospective analysis was conducted using the records of patients with intermediate coronary stenoses who had undergone adenosine FFR (aFFR). To calculate the computed FFR, a software program used simulated coronary blood flow using computational geometry constructed using at least 2 patient-specific angiographic images. Two cardiologists reviewed the angiograms and determined the computational FFR independently. Intraobserver variability was measured using κ analysis and the intraclass correlation coefficient. The correlation coefficient and Bland-Altman plots were used to assess the agreement between the calculated FFR and the aFFR.</p><p><strong>Results: </strong>A total of 146 patients were included, with 95 men and 51 women, with a mean (SD) age of 61.1 (9.5) y. The mean (SD) aFFR was 0.847 (0.072), and 41 patients (27.0%) had an aFFR of 0.80 or less. There was a strong intraobserver correlation between the computational FFRs (r = 0.808; P < .001; κ = 0.806; P < .001). There was also a strong correlation between aFFR and computational FFR (r = 0.820; P < .001) and good agreement on the Bland-Altman plot. The computational FFR had a high sensitivity (95.1%) and specificity (90.1%) for detecting an aFFR of 0.80 or less.</p><p><strong>Conclusion: </strong>A novel software program provides a feasible method of calculating FFR from coronary angiography images without resorting to pharmacologically induced hyperemia.</p>","PeriodicalId":22352,"journal":{"name":"Texas Heart Institute journal","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969768/pdf/i1526-6702-50-1-e207410.pdf","citationCount":"0","resultStr":"{\"title\":\"Validity and Diagnostic Performance of Computing Fractional Flow Reserve From 2-Dimensional Coronary Angiography Images.\",\"authors\":\"Vahid Mohammadi,&nbsp;Massoud Ghasemi,&nbsp;Reza Rahmani,&nbsp;Maryam Mehrpooya,&nbsp;Hamidreza Babakhani,&nbsp;Akbar Shafiee,&nbsp;Mohammad Sadeghian\",\"doi\":\"10.14503/THIJ-20-7410\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Measurement of fractional flow reserve (FFR) is the gold standard for determining the physiologic significance of coronary artery stenosis, but newer software programs can calculate the FFR from 2-dimensional angiography images.</p><p><strong>Methods: </strong>A retrospective analysis was conducted using the records of patients with intermediate coronary stenoses who had undergone adenosine FFR (aFFR). To calculate the computed FFR, a software program used simulated coronary blood flow using computational geometry constructed using at least 2 patient-specific angiographic images. Two cardiologists reviewed the angiograms and determined the computational FFR independently. Intraobserver variability was measured using κ analysis and the intraclass correlation coefficient. The correlation coefficient and Bland-Altman plots were used to assess the agreement between the calculated FFR and the aFFR.</p><p><strong>Results: </strong>A total of 146 patients were included, with 95 men and 51 women, with a mean (SD) age of 61.1 (9.5) y. The mean (SD) aFFR was 0.847 (0.072), and 41 patients (27.0%) had an aFFR of 0.80 or less. There was a strong intraobserver correlation between the computational FFRs (r = 0.808; P < .001; κ = 0.806; P < .001). There was also a strong correlation between aFFR and computational FFR (r = 0.820; P < .001) and good agreement on the Bland-Altman plot. The computational FFR had a high sensitivity (95.1%) and specificity (90.1%) for detecting an aFFR of 0.80 or less.</p><p><strong>Conclusion: </strong>A novel software program provides a feasible method of calculating FFR from coronary angiography images without resorting to pharmacologically induced hyperemia.</p>\",\"PeriodicalId\":22352,\"journal\":{\"name\":\"Texas Heart Institute journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969768/pdf/i1526-6702-50-1-e207410.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Texas Heart Institute journal\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.14503/THIJ-20-7410\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Texas Heart Institute journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.14503/THIJ-20-7410","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

背景:血流储备分数(FFR)测量是确定冠状动脉狭窄生理意义的金标准,但较新的软件程序可以从二维血管造影图像中计算FFR。方法:回顾性分析中期冠状动脉狭窄患者行腺苷FFR (aFFR)治疗的资料。为了计算计算出的FFR,一个软件程序使用至少2张患者特异性血管造影图像构建的计算几何来模拟冠状动脉血流。两位心脏病专家检查了血管造影并独立确定了计算FFR。使用κ分析和类内相关系数测量观察者内变异性。使用相关系数和Bland-Altman图来评估计算的FFR与aFFR之间的一致性。结果:共纳入146例患者,其中男性95例,女性51例,平均(SD)年龄61.1岁(9.5岁),平均(SD) aFFR为0.847 (0.072),aFFR为0.80及以下的患者41例(27.0%)。计算ffr之间存在很强的观察者内相关性(r = 0.808;P < .001;κ = 0.806;P < 0.001)。aFFR与计算FFR也有很强的相关性(r = 0.820;P < 0.001),在Bland-Altman图上有很好的一致性。计算FFR在检测aFFR为0.80或更低时具有很高的灵敏度(95.1%)和特异性(90.1%)。结论:一种新的软件程序提供了一种可行的方法,可以从冠状动脉造影图像中计算FFR,而无需诉诸药物诱导充血。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Validity and Diagnostic Performance of Computing Fractional Flow Reserve From 2-Dimensional Coronary Angiography Images.

Background: Measurement of fractional flow reserve (FFR) is the gold standard for determining the physiologic significance of coronary artery stenosis, but newer software programs can calculate the FFR from 2-dimensional angiography images.

Methods: A retrospective analysis was conducted using the records of patients with intermediate coronary stenoses who had undergone adenosine FFR (aFFR). To calculate the computed FFR, a software program used simulated coronary blood flow using computational geometry constructed using at least 2 patient-specific angiographic images. Two cardiologists reviewed the angiograms and determined the computational FFR independently. Intraobserver variability was measured using κ analysis and the intraclass correlation coefficient. The correlation coefficient and Bland-Altman plots were used to assess the agreement between the calculated FFR and the aFFR.

Results: A total of 146 patients were included, with 95 men and 51 women, with a mean (SD) age of 61.1 (9.5) y. The mean (SD) aFFR was 0.847 (0.072), and 41 patients (27.0%) had an aFFR of 0.80 or less. There was a strong intraobserver correlation between the computational FFRs (r = 0.808; P < .001; κ = 0.806; P < .001). There was also a strong correlation between aFFR and computational FFR (r = 0.820; P < .001) and good agreement on the Bland-Altman plot. The computational FFR had a high sensitivity (95.1%) and specificity (90.1%) for detecting an aFFR of 0.80 or less.

Conclusion: A novel software program provides a feasible method of calculating FFR from coronary angiography images without resorting to pharmacologically induced hyperemia.

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
Texas Heart Institute journal
Texas Heart Institute journal 医学-心血管系统
CiteScore
1.10
自引率
11.10%
发文量
131
审稿时长
2 months
期刊介绍: For more than 45 years, the Texas Heart Institute Journal has been published by the Texas Heart Institute as part of its medical education program. Our bimonthly peer-reviewed journal enjoys a global audience of physicians, scientists, and healthcare professionals who are contributing to the prevention, diagnosis, and treatment of cardiovascular disease. The Journal was printed under the name of Cardiovascular Diseases from 1974 through 1981 (ISSN 0093-3546). The name was changed to Texas Heart Institute Journal in 1982 and was printed through 2013 (ISSN 0730-2347). In 2014, the Journal moved to online-only publication. It is indexed by Index Medicus/MEDLINE and by other indexing and abstracting services worldwide. Our full archive is available at PubMed Central. The Journal invites authors to submit these article types for review: -Clinical Investigations- Laboratory Investigations- Reviews- Techniques- Coronary Anomalies- History of Medicine- Case Reports/Case Series (Submission Fee: $70.00 USD)- Images in Cardiovascular Medicine (Submission Fee: $35.00 USD)- Guest Editorials- Peabody’s Corner- Letters to the Editor
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信