• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

相似文献

1
Machine learning-based CT fractional flow reserve assessment in acute chest pain: first experience.基于机器学习的急性胸痛患者CT血流储备分数评估:初步经验
Cardiovasc Diagn Ther. 2020 Aug;10(4):820-830. doi: 10.21037/cdt-20-381.
2
Non-invasive fractional flow reserve derived from coronary computed tomography angiography in patients with acute chest pain: Subgroup analysis of the ROMICAT II trial.基于冠状动脉计算机断层扫描血管造影的无创性分数流量储备在急性胸痛患者中的应用:ROMICAT II 试验的亚组分析。
J Cardiovasc Comput Tomogr. 2019 Jul-Aug;13(4):196-202. doi: 10.1016/j.jcct.2019.05.009. Epub 2019 May 15.
3
Impact of machine learning-based coronary computed tomography angiography fractional flow reserve on treatment decisions and clinical outcomes in patients with suspected coronary artery disease.基于机器学习的冠状动脉计算机断层扫描血管造影血流储备分数对疑似冠心病患者治疗决策和临床结局的影响。
Eur Radiol. 2020 Nov;30(11):5841-5851. doi: 10.1007/s00330-020-06964-w. Epub 2020 May 28.
4
Clinical Use of CT-Derived Fractional Flow Reserve in the Emergency Department.CT 衍生的血流储备分数在急诊科的临床应用。
JACC Cardiovasc Imaging. 2020 Feb;13(2 Pt 1):452-461. doi: 10.1016/j.jcmg.2019.05.025. Epub 2019 Jul 17.
5
The best predictor of ischemic coronary stenosis: subtended myocardial volume, machine learning-based FFR, or high-risk plaque features?缺血性冠状动脉狭窄的最佳预测因子:受心肌体积、基于机器学习的 FFR 还是高危斑块特征?
Eur Radiol. 2019 Jul;29(7):3647-3657. doi: 10.1007/s00330-019-06139-2. Epub 2019 Mar 22.
6
Noninvasive FFR Derived From Coronary CT Angiography: Management and Outcomes in the PROMISE Trial.基于冠状动脉 CT 血管造影的无创血流储备分数:PROMISE 试验的处理和结果。
JACC Cardiovasc Imaging. 2017 Nov;10(11):1350-1358. doi: 10.1016/j.jcmg.2016.11.024. Epub 2017 Apr 12.
7
Late Outcomes of Patients in the Emergency Department With Acute Chest Pain Evaluated With Computed Tomography-Derived Fractional Flow Reserve.采用 CT 计算的血流储备分数评估的急诊科急性胸痛患者的远期结局。
Am J Cardiol. 2024 Sep 1;226:65-71. doi: 10.1016/j.amjcard.2024.06.008. Epub 2024 Jun 13.
8
Non-invasive fractional flow reserve (FFR) in the evaluation of acute chest pain - Concepts and first experiences.无创性分比流量储备值(FFR)在急性胸痛评估中的应用:概念和初步经验。
Eur J Radiol. 2021 May;138:109633. doi: 10.1016/j.ejrad.2021.109633. Epub 2021 Mar 8.
9
Prognostic Value and Risk Continuum of Noninvasive Fractional Flow Reserve Derived from Coronary CT Angiography.基于冠状动脉 CT 血管造影的无创性血流储备分数的预后价值和风险连续统。
Radiology. 2019 Aug;292(2):343-351. doi: 10.1148/radiol.2019182264. Epub 2019 Jun 11.
10
Non-invasive fractional flow reserve in vessels without severe obstructive stenosis is associated with coronary plaque burden.无严重狭窄病变血管的无创性血流储备分数与冠状动脉斑块负荷相关。
J Cardiovasc Comput Tomogr. 2018 Sep-Oct;12(5):379-384. doi: 10.1016/j.jcct.2018.05.003. Epub 2018 May 7.

引用本文的文献

1
Increasing the rate of datasets amenable to CT and quantitative plaque analysis: Value of software for reducing stair-step artifacts demonstrated in photon-counting detector CT.提高适用于CT和定量斑块分析的数据集速率:光子计数探测器CT中用于减少阶梯状伪影的软件的价值。
Eur J Radiol Open. 2024 Jun 4;12:100574. doi: 10.1016/j.ejro.2024.100574. eCollection 2024 Jun.
2
Early Diagnosis of Cardiovascular Diseases in the Era of Artificial Intelligence: An In-Depth Review.人工智能时代心血管疾病的早期诊断:深入综述
Cureus. 2024 Mar 9;16(3):e55869. doi: 10.7759/cureus.55869. eCollection 2024 Mar.
3
Evaluating the Efficacy of ChatGPT in Navigating the Spanish Medical Residency Entrance Examination (MIR): Promising Horizons for AI in Clinical Medicine.评估ChatGPT在应对西班牙医学住院医师入学考试(MIR)中的效果:人工智能在临床医学中的广阔前景。
Clin Pract. 2023 Nov 20;13(6):1460-1487. doi: 10.3390/clinpract13060130.
4
Predictive value of coronary artery computed tomography-derived fractional flow reserve for cardiovascular events in patients with coronary artery disease.冠状动脉 CT 衍生的血流储备分数对冠心病患者心血管事件的预测价值。
Herz. 2024 Aug;49(4):296-301. doi: 10.1007/s00059-023-05220-3. Epub 2023 Nov 3.
5
AI Algorithm to Predict Acute Coronary Syndrome in Prehospital Cardiac Care: Retrospective Cohort Study.用于预测院前心脏护理中急性冠状动脉综合征的人工智能算法:回顾性队列研究。
JMIR Cardio. 2023 Oct 31;7:e51375. doi: 10.2196/51375.
6
Artificial Intelligence - Advisory or Adversary?人工智能——顾问还是对手?
Interv Cardiol. 2023 Apr 24;18:e17. doi: 10.15420/icr.2022.22. eCollection 2023.
7
In search of new gatekeepers: coronary CT (Computed Tomography) in acute coronary syndrome.寻找新的把关者:急性冠状动脉综合征中的冠状动脉CT(计算机断层扫描)
Eur Heart J Suppl. 2023 Apr 21;25(Suppl B):B1-B6. doi: 10.1093/eurheartjsupp/suad076. eCollection 2023 Apr.
8
Deep Learning Model for Coronary Angiography.用于冠状动脉造影的深度学习模型。
J Cardiovasc Transl Res. 2023 Aug;16(4):896-904. doi: 10.1007/s12265-023-10368-8. Epub 2023 Mar 16.
9
Deep learning applications in coronary anatomy imaging: a systematic review and meta-analysis.深度学习在冠状动脉解剖成像中的应用:一项系统评价与荟萃分析。
J Med Artif Intell. 2022 Dec;5:11. doi: 10.21037/jmai-22-36.
10
Clinical Applications of Artificial Intelligence-An Updated Overview.人工智能的临床应用——最新综述。
J Clin Med. 2022 Apr 18;11(8):2265. doi: 10.3390/jcm11082265.

本文引用的文献

1
Deep Learning Analysis of Coronary Arteries in Cardiac CT Angiography for Detection of Patients Requiring Invasive Coronary Angiography.基于 CT 冠状动脉造影的深度学习分析在需要进行有创冠状动脉造影的患者检测中的应用。
IEEE Trans Med Imaging. 2020 May;39(5):1545-1557. doi: 10.1109/TMI.2019.2953054. Epub 2019 Nov 12.
2
Factors influencing physician risk estimates for acute cardiac events in emergency patients with suspected acute coronary syndrome.影响疑似急性冠脉综合征急诊患者急性心脑血管事件风险评估的因素。
Emerg Med J. 2020 Jan;37(1):2-7. doi: 10.1136/emermed-2019-208916. Epub 2019 Nov 12.
3
Effects of complete revascularization on long-term treatment outcomes in patients with multivessel coronary artery disease over 80 years of age admitted for acute coronary syndrome.完全血运重建对80岁以上因急性冠脉综合征入院的多支冠状动脉疾病患者长期治疗结局的影响。
Cardiovasc Diagn Ther. 2019 Aug;9(4):301-309. doi: 10.21037/cdt.2018.12.04.
4
2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes.2019年欧洲心脏病学会慢性冠状动脉综合征诊断和管理指南
Eur Heart J. 2020 Jan 14;41(3):407-477. doi: 10.1093/eurheartj/ehz425.
5
Determinants of Rejection Rate for Coronary CT Angiography Fractional Flow Reserve Analysis.冠状动脉 CT 血管成像血流储备分数分析的排斥率的决定因素。
Radiology. 2019 Sep;292(3):597-605. doi: 10.1148/radiol.2019182673. Epub 2019 Jul 23.
6
Clinical Use of CT-Derived Fractional Flow Reserve in the Emergency Department.CT 衍生的血流储备分数在急诊科的临床应用。
JACC Cardiovasc Imaging. 2020 Feb;13(2 Pt 1):452-461. doi: 10.1016/j.jcmg.2019.05.025. Epub 2019 Jul 17.
7
Non-invasive fractional flow reserve derived from coronary computed tomography angiography in patients with acute chest pain: Subgroup analysis of the ROMICAT II trial.基于冠状动脉计算机断层扫描血管造影的无创性分数流量储备在急性胸痛患者中的应用:ROMICAT II 试验的亚组分析。
J Cardiovasc Comput Tomogr. 2019 Jul-Aug;13(4):196-202. doi: 10.1016/j.jcct.2019.05.009. Epub 2019 May 15.
8
High-risk atherosclerotic plaque features for cardiovascular risk assessment in the Prospective Multicenter Imaging Study for Evaluation of Chest Pain trial.胸痛评估前瞻性多中心成像研究中用于心血管风险评估的高危动脉粥样硬化斑块特征。
Cardiovasc Diagn Ther. 2019 Feb;9(1):89-93. doi: 10.21037/cdt.2018.08.09.
9
Non obstructive high-risk plaque but not calcified by coronary CTA, and the G-score predict ischemia.非阻塞性高危斑块但冠脉 CTA 未见钙化,以及 G 评分预测缺血。
J Cardiovasc Comput Tomogr. 2019 Nov-Dec;13(6):305-314. doi: 10.1016/j.jcct.2019.01.010. Epub 2019 Jan 4.
10
Chest pain CT in the emergency department: Watch out for the myocardium.急诊科胸痛的CT检查:警惕心肌情况。
Eur J Radiol Open. 2018 Nov 10;5:202-208. doi: 10.1016/j.ejro.2018.10.001. eCollection 2018.

基于机器学习的急性胸痛患者CT血流储备分数评估:初步经验

Machine learning-based CT fractional flow reserve assessment in acute chest pain: first experience.

作者信息

Eberhard Matthias, Nadarevic Tin, Cousin Andrej, von Spiczak Jochen, Hinzpeter Ricarda, Euler Andre, Morsbach Fabian, Manka Robert, Keller Dagmar I, Alkadhi Hatem

机构信息

Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.

Department of Radiology, Clinical Hospital Center Rijeka, Rijeka, Croatia.

出版信息

Cardiovasc Diagn Ther. 2020 Aug;10(4):820-830. doi: 10.21037/cdt-20-381.

DOI:10.21037/cdt-20-381
PMID:32968637
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7487397/
Abstract

BACKGROUND

Computed tomography (CT)-derived fractional flow reserve (FFR) enables the non-invasive functional assessment of coronary artery stenosis. We evaluated the feasibility and potential clinical role of FFR in patients presenting to the emergency department with acute chest pain who underwent chest-pain CT (CPCT).

METHODS

For this retrospective IRB-approved study, we included 56 patients (median age: 62 years, 14 females) with acute chest pain who underwent CPCT and who had at least a mild (≥25% diameter) coronary artery stenosis. CPCT was evaluated for the presence of acute plaque rupture and vulnerable plaque features. FFR measurements were performed using a machine learning-based software. We assessed the agreement between the results from FFR and patient outcome (including results from invasive catheter angiography and from any non-invasive cardiac imaging test, final clinical diagnosis and revascularization) for a follow-up of 3 months.

RESULTS

FFR was technically feasible in 38/56 patients (68%). Eleven of the 38 patients (29%) showed acute plaque rupture in CPCT; all of them underwent immediate coronary revascularization. Of the remaining 27 patients (71%), 16 patients showed vulnerable plaque features (59%), of whom 11 (69%) were diagnosed with acute coronary syndrome (ACS) and 10 (63%) underwent coronary revascularization. In patients with vulnerable plaque features in CPCT, FFRCT had an agreement with outcome in 12/16 patients (75%). In patients without vulnerable plaque features (n=11), one patient showed myocardial ischemia (9%). In these patients, FFR and patient outcome showed an agreement in 10/11 patients (91%).

CONCLUSIONS

Our preliminary data show that FFR is feasible in patients with acute chest pain who undergo CPCT provided that image quality is sufficient. FFR has the potential to improve patient triage by reducing further downstream testing but appears of limited value in patients with CT signs of acute plaque rupture.

摘要

背景

计算机断层扫描(CT)衍生的血流储备分数(FFR)能够对冠状动脉狭窄进行无创功能评估。我们评估了FFR在因急性胸痛到急诊科就诊并接受胸痛CT(CPCT)检查的患者中的可行性及潜在临床作用。

方法

对于这项经机构审查委员会批准的回顾性研究,我们纳入了56例因急性胸痛接受CPCT检查且至少有轻度(直径≥25%)冠状动脉狭窄的患者(中位年龄:62岁,14例女性)。评估CPCT是否存在急性斑块破裂和易损斑块特征。使用基于机器学习的软件进行FFR测量。我们评估了FFR结果与患者结局(包括有创导管血管造影和任何无创心脏成像检查结果、最终临床诊断和血运重建)在3个月随访期内的一致性。

结果

FFR在38/56例患者(68%)中技术上可行。38例患者中有11例(29%)在CPCT中显示急性斑块破裂;他们均接受了即刻冠状动脉血运重建。其余27例患者(71%)中,16例患者显示易损斑块特征(59%),其中11例(69%)被诊断为急性冠状动脉综合征(ACS),10例(63%)接受了冠状动脉血运重建。在CPCT中有易损斑块特征的患者中,FFRCT与12/16例患者(75%)的结局一致。在无易损斑块特征的患者(n = 11)中,1例患者出现心肌缺血(9%)。在这些患者中,FFR与患者结局在10/11例患者(91%)中一致。

结论

我们的初步数据表明,对于接受CPCT检查的急性胸痛患者,只要图像质量足够,FFR是可行的。FFR有可能通过减少进一步的下游检查来改善患者分诊,但在有急性斑块破裂CT征象的患者中似乎价值有限。