Diagnostic performance of computed tomography-based fraction flow reserve in identifying myocardial ischemia caused by coronary artery stenosis: A meta-analysis

被引:5
|
作者
Luo, Yue [1 ]
Mao, Min [1 ]
Xiang, Rui [1 ]
Han, Baoru [1 ]
Chang, Jing [1 ]
Zuo, Zhong [1 ]
Wu, Fan [1 ]
Ma, Kanghua [1 ]
机构
[1] Chongqing Med Univ, Dept Cardiol, Affiliated Hosp 1, Chongqing 400016, Peoples R China
关键词
Noninvasive fraction flow reserve; Coronary computed tomography; angiography; Diagnostic performance; Meta-analysis; CT ANGIOGRAPHY; OUTCOMES; INTERVENTION; MULTICENTER; PERFUSION; MISMATCH; DISEASE; FFR;
D O I
10.1016/j.hjc.2021.05.004
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: As a new noninvasive diagnostic technique, computed tomography (CT)-based fraction flow reserve (FFR) has been used to identify hemodynamically significant coronary artery stenosis. This meta analysis used invasive FFR as the standard to evaluate the diagnostic performance of FFRCT. Methods: We searched the PubMed, Cochrane library, and EMBASE for articles published between January 2009 and January 2021. The synthesized sensitivity and specificity of invasive FFR and FFRCT were analyzed at both the patient and vessel levels. We generated a summary receiver operating characteristic curve (SROC) and then calculated the area under the curve (AUC). Results: We included a total of 23 studies, including 2,178 patients and 3,029 vessels or lesions. Analysis at each patient level demonstrated a synthesized sensitivity of 88%, specificity of 79%, LR+ of 4.16, LR-of 0.15, and AUC of 0.89 for FFRCT. Analysis at the level of each vessel or lesion showed a synthesized sensitivity of 85%, specificity of 81%, LR+ of 4.44, LR-of 0.19, and AUC of 0.87 for FFRCT. Conclusion: Our research reveals that FFRCT has high diagnostic performance in patients with coronary artery stenosis, regardless of whether it is at the patient level or the vessel level. (c) 2021 Hellenic Society of Cardiology. Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:1 / 7
页数:7
相关论文
共 50 条
  • [41] A study of noninvasive fractional flow reserve derived from a simplified method based on coronary computed tomography angiography in suspected coronary artery disease
    Shi, Changzheng
    Zhang, Dong
    Cao, Kunlin
    Zhang, Tao
    Luo, Liangping
    Liu, Xin
    Zhang, Heye
    BIOMEDICAL ENGINEERING ONLINE, 2017, 16
  • [42] Radiation dose and diagnostic accuracy of multidetector computed tomography for the detection of significant coronary artery stenoses A meta-analysis
    Pontone, Gianluca
    Andreini, Daniele
    Bartorelli, Antonio L.
    Bertella, Erika
    Mushtaq, Saima
    Annoni, Andrea
    Formenti, Alberto
    Chiappa, Luisa
    Cortinovis, Sarah
    Baggiano, Andrea
    Conte, Edoardo
    Bovis, Francesca
    Veglia, Fabrizio
    Foti, Claudia
    Ballerini, Giovanni
    Fiorentini, Cesare
    Pepi, Mauro
    INTERNATIONAL JOURNAL OF CARDIOLOGY, 2012, 160 (03) : 155 - 164
  • [43] The Effect of Severe Coronary Calcification on Diagnostic Performance of Computed Tomography-Derived Fractional Flow Reserve Analyses in People with Coronary Artery Disease
    Zuza, Iva
    Nadarevic, Tin
    Jakljevic, Tomislav
    Bartolovic, Nina
    Kovacic, Slavica
    DIAGNOSTICS, 2024, 14 (16)
  • [44] Accuracy of subtraction fractional flow reserve with computed tomography in identifying early revascularization in patients with coronary artery disease
    Zhu, Tingting
    Li, Defu
    Qiao, Jinhan
    Li, Qian
    Xu, Yinghao
    Ge, Bing
    Xia, Liming
    SCANDINAVIAN CARDIOVASCULAR JOURNAL, 2024, 58 (01)
  • [45] Performance of computed tomography-derived fractional flow reserve using reduced-order modelling and static computed tomography stress myocardial perfusion imaging for detection of haemodynamically significant coronary stenosis
    Ihdayhid, Abdul Rahman
    Sakaguchi, Takuya
    Linde, Jesper J.
    Sorgaard, Mathias H.
    Kofoed, Klaus F.
    Fujisawa, Yasuko
    Hislop-Jambrich, Jacqui
    Nerlekar, Nitesh
    Cameron, James D.
    Munnur, Ravi K.
    Crosset, Marcus
    Wong, Dennis T. L.
    Seneviratne, Sujith K.
    Ko, Brian S.
    EUROPEAN HEART JOURNAL-CARDIOVASCULAR IMAGING, 2018, 19 (11) : 1234 - 1243
  • [46] Anatomical and Functional Computed Tomography for Diagnosing Hemodynamically Significant Coronary Artery Disease A Meta-Analysis
    Celeng, Csilla
    Leiner, Tim
    Maurovich-Horvat, Pal
    Merkely, Bela
    de Jong, Pim
    Dankbaar, Jan W.
    van Es, Hendrik W.
    Ghoshhajra, Brian B.
    Hoffmann, Udo
    Takx, Richard A. P.
    JACC-CARDIOVASCULAR IMAGING, 2019, 12 (07) : 1316 - 1325
  • [47] Diagnostic performance of machine-learning-based computed fractional flow reserve (FFR) derived from coronary computed tomography angiography for the assessment of myocardial ischemia verified by invasive FFR
    Xiuhua Hu
    Minglei Yang
    Lu Han
    Yujiao Du
    The International Journal of Cardiovascular Imaging, 2018, 34 : 1987 - 1996
  • [48] Clinical application of computed tomography angiography and fractional flow reserve computed tomography in patients with coronary artery disease: A meta-analysis based on pre- and post-test probability
    Zhou, Tao
    Wang, Xiu
    Wu, Ting
    Yang, Zhen
    Li, Shuai
    Li, Ying
    He, Fu
    Zhang, Min
    Yang, Chenxiao
    Jia, Shouqiang
    Li, Min
    EUROPEAN JOURNAL OF RADIOLOGY, 2021, 139
  • [49] Diagnostic performance of myocardial perfusion imaging with conventional and CZT single-photon emission computed tomography in detecting coronary artery disease: A meta-analysis
    Valeria Cantoni
    Roberta Green
    Wanda Acampa
    Emilia Zampella
    Roberta Assante
    Carmela Nappi
    Valeria Gaudieri
    Teresa Mannarino
    Renato Cuocolo
    Eugenio Di Vaia
    Mario Petretta
    Alberto Cuocolo
    Journal of Nuclear Cardiology, 2021, 28 : 698 - 715
  • [50] Coronary Flow and Reserve by Enhanced Transthoracic Doppler Trumps Coronary Anatomy by Computed Tomography in Assessing Coronary Artery Stenosis
    Caiati, Carlo
    Scardapane, Arnaldo
    Iacovelli, Fortunato
    Pollice, Paolo
    Achille, Teresa Immacolata
    Favale, Stefano
    Lepera, Mario Erminio
    DIAGNOSTICS, 2021, 11 (02)