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J Cardiovasc Comput Tomogr ; 13(3): 26-33, 2019.
Article in English | MEDLINE | ID: mdl-30796003

ABSTRACT

OBJECTIVES: The 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). METHODS: 81 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. RESULTS: 243 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). CONCLUSION: Our 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.


Subject(s)
Computed Tomography Angiography/methods , Coronary Angiography/methods , Coronary Artery Disease/diagnostic imaging , Coronary Vessels/diagnostic imaging , Fractional Flow Reserve, Myocardial , Myocardial Perfusion Imaging/methods , Aged , Artificial Intelligence , Asia , Coronary Artery Disease/mortality , Coronary Artery Disease/physiopathology , Coronary Artery Disease/therapy , Coronary Vessels/physiopathology , Europe , Female , Humans , Male , Middle Aged , Predictive Value of Tests , Prognosis , Prospective Studies , Radiographic Image Interpretation, Computer-Assisted , Registries , Risk Assessment , Risk Factors , United States
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