The effect of coronary calcification on diagnostic performance of machine learning–based CT-FFR: a Chinese multicenter study

被引:0
|
作者
Meng Di Jiang
Xiao Lei Zhang
Hui Liu
Chun Xiang Tang
Jian Hua Li
Yi Ning Wang
Peng Peng Xu
Chang Sheng Zhou
Fan Zhou
Meng Jie Lu
Jia Yin Zhang
Meng Meng Yu
Yang Hou
Min Wen Zheng
Bo Zhang
Dai Min Zhang
Yan Yi
Lei Xu
Xiu Hua Hu
Jian Yang
Guang Ming Lu
Qian Qian Ni
Long Jiang Zhang
机构
[1] Jinling Hospital,Department of Medical Imaging
[2] Medical School of Nanjing University,Department of Radiology
[3] Guangdong General Hospital,Department of Cardiology
[4] Jinling Hospital,Department of Radiology
[5] Medical School of Nanjing University,Institute of Diagnostic and Interventional Radiology and Department of Cardiology
[6] Peking Union Medical College Hospital,Department of Radiology
[7] Chinese Academy of Medical Sciences and Peking Union Medical College,Department of Radiology
[8] Shanghai Jiao Tong University Affiliated Sixth People’s Hospital,Department of Radiology
[9] Shengjing Hospital of China Medical University,Department of Cardiology
[10] Xijing Hospital,Department of Radiology
[11] Fourth Military Medical University,Department of Radiology
[12] Jiangsu Taizhou People’s Hospital,Department of Radiology
[13] Nanjing First Hospital,undefined
[14] Nanjing Medical University,undefined
[15] Beijing Anzhen Hospital,undefined
[16] Capital Medical University,undefined
[17] Shaoyifu Hospital Affiliated to Medical College of Zhejiang University,undefined
[18] the First Affiliated Hospital of Medical School,undefined
[19] Xi’an Jiaotong University,undefined
来源
European Radiology | 2021年 / 31卷
关键词
Computed tomography angiography; Coronary disease; Calcium; Ischemia; Data accuracy;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:1482 / 1493
页数:11
相关论文
共 50 条
  • [1] The effect of coronary calcification on diagnostic performance of machine learning-based CT-FFR: a Chinese multicenter study
    Di Jiang, Meng
    Zhang, Xiao Lei
    Liu, Hui
    Tang, Chun Xiang
    Li, Jian Hua
    Wang, Yi Ning
    Xu, Peng Peng
    Zhou, Chang Sheng
    Zhou, Fan
    Lu, Meng Jie
    Zhang, Jia Yin
    Yu, Meng Meng
    Hou, Yang
    Zheng, Min Wen
    Zhang, Bo
    Zhang, Dai Min
    Yi, Yan
    Xu, Lei
    Hu, Xiu Hua
    Yang, Jian
    Lu, Guang Ming
    Ni, Qian Qian
    Zhang, Long Jiang
    EUROPEAN RADIOLOGY, 2021, 31 (03) : 1482 - 1493
  • [2] Effect of Coronary Calcification Severity on Measurements and Diagnostic Performance of CT-FFR With Computational Fluid Dynamics: Results From CT-FFR CHINA Trial
    Zhao, Na
    Gao, Yang
    Xu, Bo
    Yang, Weixian
    Song, Lei
    Jiang, Tao
    Xu, Li
    Hu, Hongjie
    Li, Lin
    Chen, Wenqiang
    Li, Dumin
    Zhang, Feng
    Fan, Lijuan
    Lu, Bin
    FRONTIERS IN CARDIOVASCULAR MEDICINE, 2022, 8
  • [3] Influence of Coronary Calcium on Diagnostic Performance of Machine Learning CT-FFR Results From MACHINE Registry
    Tesche, Christian
    Otani, Katharina
    De Cecco, Carlo N.
    Coenen, Adriaan
    De Geer, Jakob
    Kruk, Mariusz
    Kim, Young-Hak
    Albrecht, Moritz H.
    Baumann, Stefan
    Renker, Matthias
    Bayer, Richard R.
    Duguay, Taylor M.
    Litwin, Sheldon E.
    Varga-Szemes, Akos
    Steinberg, Daniel H.
    Yang, Dong Hyun
    Kepka, Cezary
    Persson, Anders
    Nieman, Koen
    Schoepf, U. Joseph
    JACC-CARDIOVASCULAR IMAGING, 2020, 13 (03) : 760 - 770
  • [4] Impact of Coronary Artery Calcification on the Accuracy of CT-FFR
    Tran, J. S.
    Han, H.
    Ibrahim, R.
    Kolimas, A. M.
    Shanmugasundaram, M.
    JACC-CARDIOVASCULAR INTERVENTIONS, 2024, 17 (04) : S44 - S45
  • [5] Diagnostic Performance of Machine Learning Based CT-FFR in Detecting Ischemia in Myocardial Bridging and Concomitant Proximal Atherosclerotic Disease
    Zhou, Fan
    Wang, Yi Ning
    Schoepf, U. Joseph
    Tesche, Christian
    Tang, Chun Xiang
    Zhou, Chang Sheng
    Xu, Lei
    Hou, Yang
    Zheng, Min Wen
    Yan, Jing
    Lu, Meng Jie
    Lu, Guang Ming
    Zhang, Dai Min
    Zhang, Bo
    Zhang, Jia Yin
    Zhang, Long Jiang
    CANADIAN JOURNAL OF CARDIOLOGY, 2019, 35 (11) : 1523 - 1533
  • [6] Diagnostic accuracy of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) in patients before liver transplantation using CT-FFR machine learning algorithm
    Schuessler, Maximilian
    Saner, Fuat
    Al-Rashid, Fadi
    Schlosser, Thomas
    EUROPEAN RADIOLOGY, 2022, 32 (12) : 8761 - 8768
  • [7] Diagnostic accuracy of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) in patients before liver transplantation using CT-FFR machine learning algorithm
    Maximilian Schuessler
    Fuat Saner
    Fadi Al-Rashid
    Thomas Schlosser
    European Radiology, 2022, 32 : 8761 - 8768
  • [8] Validation and diagnostic performance of a fast on-site deep learning-based CT-FFR algorithm
    Giannopoulos, A.
    Keller, L. K.
    Sepulcri, D. S.
    Boehm, R. B.
    Garefa, C. G.
    Tsinaridis, A. T.
    Sager, D. S.
    Venugopal, P. V.
    Mitra, J. M.
    Ghose, S. G.
    Pack, J. D. P.
    Davis, C. L. D.
    Edic, P. M. E.
    Kaufmann, P. A. K.
    Buechel, R. R. B.
    EUROPEAN HEART JOURNAL, 2022, 43 : 203 - 203
  • [9] Diagnostic performance of the quantitative flow ratio and CT-FFR for coronary lesion-specific ischemia
    Han, Wenqi
    Liang, Lei
    Han, Tuo
    Wang, Zhenyu
    Shi, Lei
    Li, Yuan
    Chang, Fengjun
    Cao, Yiwei
    Zhang, Chunyan
    Wu, Haoyu
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [10] CT morphological index provides incremental value to machine learning based CT-FFR for predicting hemodynamically significant coronary stenosis
    Yu, Mengmeng
    Lu, Zhigang
    Li, Wenbin
    Wei, Meng
    Yan, Jing
    Zhang, Jiayin
    INTERNATIONAL JOURNAL OF CARDIOLOGY, 2018, 265 : 256 - 261