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Coronary Artery Calcium Is Associated with Left Ventricular Diastolic Function Independent of Myocardial Ischemia Advances in Coronary No-Reflow Phenomenon-a Contemporary Review A Randomized Trial Comparing the NeoVas Sirolimus-Eluting Bioresorbable Scaffold and Metallic Everolimus-Eluting Stents Homeostatic Chemokines and Prognosis in Patients With Acute Coronary Syndromes Better Prognosis After Complete Revascularization Using Contemporary Coronary Stents in Patients With Chronic Kidney Disease Long-Term Effect of Ultrathin-Strut Versus Thin-Strut Drug-Eluting Stents in Patients With Small Vessel Coronary Artery Disease Undergoing Percutaneous Coronary Intervention: A Subgroup Analysis of the BIOSCIENCE Randomized Trial Radionuclide Image-Guided Repair of the Heart Management of Patients With NSTE-ACS: A Comparison of the Recent AHA/ACC and ESC Guidelines Left Ventricular Assist Devices for Lifelong Support Optimal Stenting Technique for Complex Coronary Lesions Intracoronary Imaging-Guided Pre-Dilation, Stent Sizing, and Post-Dilation
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Review ArticleVolume 12, Issue 6, June 2019

JOURNAL：JACC: Cardiovascular Imaging Article Link

The Future of Cardiovascular Computed Tomography Advanced Analytics and Clinical Insights

ED Nicol, BL Norgaard, P Blanke et al. Keywords: atherosclerosis; cardiac CT; FFRCT; machine learning; radiomics; TMVR

ABSTRACT

Cardiovascular computed tomography (CCT) has undergone rapid maturation over the last decade and is now of proven clinical utility in the diagnosis and management of coronary artery disease, in guiding structural heart disease intervention, and in the diagnosis and treatment of congenital heart disease. The next decade will undoubtedly witness further advances in hardware and advanced analytics that will potentially see an increasingly core role for CCT at the center of clinical cardiovascular practice. In coronary artery disease assessment this may be via improved hemodynamic adjudication, and shear stress analysis using computational flow dynamics, more accurate and robust plaque characterization with spectral or photon-counting CT, or advanced quantification of CT data via artificial intelligence, machine learning, and radiomics. In structural heart disease, CCT is already pivotal to procedural planning with adjudication of gradients before and following intervention, whereas in congenital heart disease CCT is already used to support clinical decision making from neonates to adults, often with minimal radiation dose. In both these areas the role of computational flow dynamics, advanced tissue printing, and image modelling has the potential to revolutionize the way these complex conditions are managed, and CCT is likely to become an increasingly critical enabler across the whole advancing field of cardiovascular medicine.

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