Wijnand J Stuijfzand1,2, Alexander R van Rosendael1,3, Fay Y Lin1, Hyuk-Jae Chang4, Inge J van den Hoogen1,3, Umberto Gianni1,5, Jung Hyun Choi6, Joon-Hyung Doh7, Ae-Young Her8, Bon-Kwon Koo9, Chang-Wook Nam10, Hyung-Bok Park11, Sang-Hoon Shin12, Jason Cole13, Alessia Gimelli14, Muhammad Akram Khan15, Bin Lu16, Yang Gao16, Faisal Nabi17, Ryo Nakazato18, U Joseph Schoepf19, Roel S Driessen2, Michiel J Bom2, Randall Thompson20, James J Jang21, Michael Ridner22, Chris Rowan23, Erick Avelar24, Philippe Généreux25, Paul Knaapen2, Guus A de Waard2, Gianluca Pontone26, Daniele Andreini26, Mouaz H Al-Mallah27, Yao Lu1, Daniel S Berman28, Jagat Narula29, James K Min1, Jeroen J Bax3, Leslee J Shaw1. 1. Dalio Institute of Cardiovascular Imaging, Department of Radiology, New York-Presbyterian Hospital and the Weill Cornell Medical College, New York. 2. Amsterdam University Medical Center, VU University Medical Center, Amsterdam, the Netherlands. 3. Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands. 4. Division of Cardiology, Severance Cardiovascular Hospital and Severance Biomedical Science Institute, Yonsei University College of Medicine, Yonsei University Health System, Seoul, South Korea. 5. Department of Molecular Medicine, Section of Cardiology, University of Pavia, Pavia, Italy. 6. Pusan National University Hospital, Busan, South Korea. 7. Division of Cardiology, Inje University Ilsan Paik Hospital, Goyang, South Korea. 8. Kang Won National University Hospital, Chuncheon, South Korea. 9. Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea. 10. Cardiovascular Center, Keimyung University Dongsan Hospital, Daegu, South Korea. 11. Division of Cardiology, Department of Internal Medicine, International St Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon, South Korea. 12. Division of Cardiology, Department of Internal Medicine, Ewha Women's University Seoul Hospital, Seoul, South Korea. 13. Mobile Cardiology Associates, Mobile, Alabama. 14. Department of Imaging, Fondazione Toscana Gabriele Monasterio, Pisa, Italy. 15. Cardiac Center of Texas, McKinney. 16. State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Beijing, China. 17. Houston Methodist Hospital, Houston, Texas. 18. Cardiovascular Center, St. Luke's International Hospital, Tokyo, Japan. 19. Medical University of South Carolina, Charleston. 20. St Luke's Mid America Heart Institute, Kansas City, Missouri. 21. Kaiser Permanente Hospital, Oakland, California. 22. Heart Center Research, LLC, Huntsville, Alabama. 23. Renown Heart and Vascular Institute, Reno, Nevada. 24. Oconee Heart and Vascular Center, St Mary's Hospital, Athens, Georgia. 25. Gagnon Cardiovascular Institute at Morristown Medical Center, Morristown, New Jersey. 26. Centro Cardiologico Monzino, IRCCS Milan, Italy. 27. Houston Methodist DeBakey Heart and Vascular Center, Houston Methodist Hospital, Houston, Texas. 28. Department of Imaging and Medicine, Cedars Sinai Medical Center, Los Angeles, California. 29. Mount Sinai Heart, Zena and Michael A. Wiener Cardiovascular Institute, Marie-Josée and Henry R. Kravis Center for Cardiovascular Health, Icahn School of Medicine at Mount Sinai, New York, New York.
Abstract
Importance: Stress imaging has been the standard for diagnosing functionally significant coronary artery disease. It is unknown whether novel, atherosclerotic plaque measures improve accuracy beyond coronary stenosis for diagnosing invasive fractional flow reserve (FFR) measurement. Objective: To compare the diagnostic accuracy of comprehensive anatomic (obstructive and nonobstructive atherosclerotic plaque) vs functional imaging measures for estimating vessel-specific FFR. Design, Setting, and Participants: Controlled clinical trial of diagnostic accuracy with a multicenter derivation-validation cohort of patients referred for nonemergent invasive coronary angiography. A total of 612 patients (64 [10] years; 30% women) with signs and symptoms suggestive of myocardial ischemia from 23 sites were included. Patients were recruited from 2014 to 2017. Data analysis began in August 2018. Interventions: Patients underwent invasive coronary angiography with measurement of invasive FFR, coronary computed tomographic angiography (CCTA) quantification of atherosclerotic plaque and FFR by CT (FFR-CT), and semiquantitative scoring of rest/stress myocardial perfusion imaging (by magnetic resonance, positron emission tomography, or single photon emission CT). Multivariable generalized linear mixed models were derived and validated calculating the area under the receiver operating characteristics curve. Main Outcomes and Measures: The primary end point was invasive FFR of 0.80 or less. Results: Of the 612 patients, the mean (SD) age was 64 (10) years, and 426 (69.9%) were men. An invasive FFR of 0.80 or less was measured in 26.5% of 1727 vessels. In the derivation cohort, CCTA vessel-specific factors associated with FFR 0.80 or less were stenosis severity, percentage of noncalcified atheroma volume, lumen volume, the number of lesions with high-risk plaque (≥2 of low attenuation plaque, positive remodeling, napkin ring sign, or spotty calcification), and the number of lesions with stenosis greater than 30%. Fractional flow reserve-CT was not additive to this model including stenosis and atherosclerotic plaque. Significant myocardial perfusion imaging predictors were the summed rest and difference scores. In the validation cohort, the areas under the receiver operating characteristic curve were 0.81 for CCTA vs 0.67 for myocardial perfusion imaging (P < .001). Conclusions and Relevance: A comprehensive anatomic interpretation with CCTA, including quantification of obstructive and nonobstructive atherosclerotic plaque, was superior to functional imaging in the diagnosis of invasive FFR. Comprehensive CCTA measures improve prediction of vessel-specific coronary physiology more so than stress-induced alterations in myocardial perfusion. Trial Registration: ClinicalTrials.gov Identifier: NCT02173275.
Importance: Stress imaging has been the standard for diagnosing functionally significant coronary artery disease. It is unknown whether novel, atherosclerotic plaque measures improve accuracy beyond coronary stenosis for diagnosing invasive fractional flow reserve (FFR) measurement. Objective: To compare the diagnostic accuracy of comprehensive anatomic (obstructive and nonobstructive atherosclerotic plaque) vs functional imaging measures for estimating vessel-specific FFR. Design, Setting, and Participants: Controlled clinical trial of diagnostic accuracy with a multicenter derivation-validation cohort of patients referred for nonemergent invasive coronary angiography. A total of 612 patients (64 [10] years; 30% women) with signs and symptoms suggestive of myocardial ischemia from 23 sites were included. Patients were recruited from 2014 to 2017. Data analysis began in August 2018. Interventions: Patients underwent invasive coronary angiography with measurement of invasive FFR, coronary computed tomographic angiography (CCTA) quantification of atherosclerotic plaque and FFR by CT (FFR-CT), and semiquantitative scoring of rest/stress myocardial perfusion imaging (by magnetic resonance, positron emission tomography, or single photon emission CT). Multivariable generalized linear mixed models were derived and validated calculating the area under the receiver operating characteristics curve. Main Outcomes and Measures: The primary end point was invasive FFR of 0.80 or less. Results: Of the 612 patients, the mean (SD) age was 64 (10) years, and 426 (69.9%) were men. An invasive FFR of 0.80 or less was measured in 26.5% of 1727 vessels. In the derivation cohort, CCTA vessel-specific factors associated with FFR 0.80 or less were stenosis severity, percentage of noncalcified atheroma volume, lumen volume, the number of lesions with high-risk plaque (≥2 of low attenuation plaque, positive remodeling, napkin ring sign, or spotty calcification), and the number of lesions with stenosis greater than 30%. Fractional flow reserve-CT was not additive to this model including stenosis and atherosclerotic plaque. Significant myocardial perfusion imaging predictors were the summed rest and difference scores. In the validation cohort, the areas under the receiver operating characteristic curve were 0.81 for CCTA vs 0.67 for myocardial perfusion imaging (P < .001). Conclusions and Relevance: A comprehensive anatomic interpretation with CCTA, including quantification of obstructive and nonobstructive atherosclerotic plaque, was superior to functional imaging in the diagnosis of invasive FFR. Comprehensive CCTA measures improve prediction of vessel-specific coronary physiology more so than stress-induced alterations in myocardial perfusion. Trial Registration: ClinicalTrials.gov Identifier: NCT02173275.
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