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      The best predictor of ischemic coronary stenosis: subtended myocardial volume, machine learning-based FFRCT, or high-risk plaque features?

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          Abstract

          The present study aimed to compare the diagnostic performance of a machine learning (ML)-based FFRCT algorithm, quantified subtended myocardial volume, and high-risk plaque features for predicting if a coronary stenosis is hemodynamically significant, with reference to FFRICA.

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          Author and article information

          Journal
          Journal ID (iso-abbrev): Eur Radiol
          Title: European radiology
          Publisher: Springer Science and Business Media LLC
          ISSN (Electronic): 1432-1084
          ISSN (Print): 0938-7994
          Publication date (Electronic): Jul 2019
          Volume: 29
          Issue: 7
          Affiliations
          [1 ] Institute of Diagnostic and Interventional Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, #600, Yishan Rd, Shanghai, 200233, China.
          [2 ] Department of Cardiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, #600, Yishan Rd, Shanghai, China.
          [3 ] Siemens Healthineers, #278, Zhouzhugong Rd, Shanghai, China.
          [4 ] Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China.
          [5 ] Department of Radiology, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Centre for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
          [6 ] Institute of Diagnostic and Interventional Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, #600, Yishan Rd, Shanghai, 200233, China. andrewssmu@msn.com.
          Article
          Publisher Item ID: 10.1007/s00330-019-06139-2
          DOI: 10.1007/s00330-019-06139-2
          PubMed ID: 30903334
          SO-VID: c4812b71-5a32-465c-8fce-f322b11f5dd7
          History

          Keywords: Coronary artery disease,Myocardial fractional flow reserve,Multidetector computed tomography,Percutaneous coronary intervention,Angiography
          Data availability:
          Keywords: Coronary artery disease, Myocardial fractional flow reserve, Multidetector computed tomography, Percutaneous coronary intervention, Angiography

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