Prognostic value of CT myocardial perfusion imaging and CT-derived fractional flow reserve for major adverse cardiac events in patients with coronary artery disease期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

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Prognostic value of CT myocardial perfusion imaging and CT-derived fractional flow reserve for major adverse cardiac events in patients with coronary artery disease

Institution:	1. Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA;2. University of Groningen, University Medical Center Groningen, Center for Medical Imaging - North East Netherlands, Groningen, the Netherlands;3. University of Groningen, University Medical Center Groningen, Departments of Radiology, Groningen, the Netherlands;4. Department of Diagnostic and Interventional Radiology, Hong Kong Sanatorium and Hospital, Happy Valley, Hong Kong, China;5. Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea;6. Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China;7. Siemens Medical Solutions, Malvern, PA, USA;8. Department of Cardiology and Intensive Care Medicine, Heart Center Munich-Bogenhausen, Munich, Germany;9. Department of Radiology, Emory University, Atlanta, Georgia, USA;1. Division of Cardiovascular Imaging, Medical University of South Carolina, Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Charleston, SC, USA;2. University of Groningen, University Medical Center Groningen, Center for Medical Imaging - North East Netherlands, Groningen, the Netherlands;3. Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), Cagliari, Italy;4. Department of Cardiology, Royal Liverpool and Broadgreen University Hospital, Liverpool, UK;5. University of Groningen, University Medical Center Groningen, Dept of Radiology, Groningen, the Netherlands;6. Emory University, Department of Radiology and Imaging Sciences, Atlanta, GA, USA;1. Department of Cardiology, The Heart Centre, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100 Copenhagen-Ø, Denmark;2. Department of Radiology, The Diagnostic Centre, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100 Copenhagen-Ø, Denmark;3. Department of Medicine, Division of Cardiology, John Hopkins University School of Medicine, 600 N. Wolfe Street, Blalock 524, Baltimore, USA;4. Heart Institute, Incor, University of São Paulo Medical School, Avenida Dr. Eneas de Carvalho Aguiar, 44 – Pinheiros, São Paulo, SP 05403-900, Brazil;5. Medical University Innsbruck, Department of Radiology, Innrain 52, Christoph-Probst-Platz, 6020 Innsbruck, Austria;6. Department of Medicine, Division of Cardiology, Glostrup University Hospital, Nordre Ringvej 57, 2600 Glostrup, Denmark;1. Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, United States;2. Scuola di Specializzazione di Radiodiagnostica, Università degli Studi di Milano, Milan, Italy;3. Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, SC, United States;4. Department of Medical–Surgical Sciences and Translational Medicine, University of Rome “Sapienza”, Rome, Italy;5. Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt, Germany;6. Department of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy;7. Department of Radiological Sciences, Oncology and Pathology, University of Rome “Sapienza” – Polo Pontino, Latina, Italy;1. Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA;2. Department of Cardiology and Intensive Care Medicine, Heart Center Munich-Bogenhausen, Munich, Germany;3. Department of Radiological Sciences, Oncology and Pathology, University of Rome “Sapienza”, Rome, Italy;4. First Department of Medicine, Faculty of Medicine Mannheim, University Medical Centre Mannheim (UMM), University of Heidelberg, Mannheim, Germany;5. Department of Internal Medicine I, Cardiology/Angiology, Giessen University, Giessen, Germany;6. Department of Diagnostic and Interventional Radiology, Eberhard-Karls University, Tuebingen, Tuebingen, Germany;7. Department of Cardiology, Hospital of the Ludwig-Maximilians-University, Munich, Germany;8. Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, SC, USA;1. Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA;2. Department of Radiology, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea;3. Department of Radiological Sciences, Oncology and Pathology, University of Rome “Sapienza”, Rome, Italy;4. Department of Cardiology and Intensive Care Medicine, Heart Center Munich-Bogenhausen, Munich, Germany;5. Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, SC, USA;1. Department of Radiology, Mie University Hospital, Tsu, Mie, Japan;2. Faculty of Radiological Technology, Fujita Health University School of Health Science, Toyoake, Aichi, Japan

Abstract:	ObjectivesThe purpose of this study was to analyze the prognostic value of dynamic CT perfusion imaging (CTP) and CT derived fractional flow reserve (CT-FFR) for major adverse cardiac events (MACE).Methods81 patients from 4 institutions underwent coronary computed tomography angiography (CCTA) with dynamic CTP imaging and CT-FFR analysis. Patients were followed-up at 6, 12, and 18 months after imaging. MACE were defined as cardiac death, nonfatal myocardial infarction, unstable angina requiring hospitalization, or revascularization. CT-FFR was computed for each major coronary artery using an artificial intelligence-based application. CTP studies were analyzed per vessel territory using an index myocardial blood flow, the ratio between territory and global MBF. The prognostic value of CCTA, CT-FFR, and CTP was investigated with a univariate and multivariate Cox proportional hazards regression model.Results243 vessels in 81 patients were interrogated by CCTA with CT-FFR and 243 vessel territories (1296 segments) were evaluated with dynamic CTP imaging. Of the 81 patients, 25 (31%) experienced MACE during follow-up. In univariate analysis, a positive index-MBF resulted in the largest risk for MACE (HR 11.4) compared to CCTA (HR 2.6) and CT-FFR (HR 4.6). In multivariate analysis, including clinical factors, CCTA, CT-FFR, and index-MBF, only index-MBF significantly contributed to the risk of MACE (HR 10.1), unlike CCTA (HR 1.2) and CT-FFR (HR 2.2).ConclusionOur study provides initial evidence that dynamic CTP alone has the highest prognostic value for MACE compared to CCTA and CT-FFR individually or a combination of the three, independent of clinical risk factors.

Keywords:	Perfusion imaging Fractional flow reserve Coronary artery disease Myocardial ischemia Arterial input function"} {"#name":"keyword" "$":{"id":"kwrd0035"} "$$":[{"#name":"text" "_":"(AIF) Coronary artery disease"} {"#name":"keyword" "$":{"id":"kwrd0045"} "$$":[{"#name":"text" "_":"(CAD) Coronary computed tomography angiography"} {"#name":"keyword" "$":{"id":"kwrd0055"} "$$":[{"#name":"text" "_":"(CCTA) CT-derived fractional flow reserve"} {"#name":"keyword" "$":{"id":"kwrd0065"} "$$":[{"#name":"text" "_":"(CT-FFR) Fractional Flow Reserve"} {"#name":"keyword" "$":{"id":"kwrd0075"} "$$":[{"#name":"text" "_":"(FFR) Interquartile range"} {"#name":"keyword" "$":{"id":"kwrd0085"} "$$":[{"#name":"text" "_":"(IQR) Major adverse cardiac events"} {"#name":"keyword" "$":{"id":"kwrd0095"} "$$":[{"#name":"text" "_":"(MACE) Myocardial blood flow"} {"#name":"keyword" "$":{"id":"kwrd0105"} "$$":[{"#name":"text" "_":"(MBF) Myocardial perfusion CT"} {"#name":"keyword" "$":{"id":"kwrd0115"} "$$":[{"#name":"text" "_":"(CTP) Standard deviation"} {"#name":"keyword" "$":{"id":"kwrd0125"} "$$":[{"#name":"text" "_":"(SD) Tissue attenuation curves"} {"#name":"keyword" "$":{"id":"kwrd0135"} "$$":[{"#name":"text" "_":"(TAC)
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