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CT Angiographic and Plaque Predictors of Functionally Significant Coronary Disease and Outcome Using Machine Learning A Randomized Controlled Trial to Evaluate the Safety and Efficacy of Cardiac Contractility Modulation Usefulness of minimum stent cross sectional area as a predictor of angiographic restenosis after primary percutaneous coronary intervention in acute myocardial infarction (from the HORIZONS-AMI Trial IVUS substudy) Longitudinal Change in Galectin-3 and Incident Cardiovascular Outcomes Clinical Impact of Valvular Heart Disease in Elderly Patients Admitted for Acute Coronary Syndrome: Insights From the Elderly-ACS 2 Study Coronary artery imaging with intravascular high-frequency ultrasound Short-Term Progression of Multiterritorial Subclinical Atherosclerosis Cardiac resynchronization therapy with a defibrillator (CRTd) in failing heart patients with type 2 diabetes mellitus and treated by glucagon-like peptide 1 receptor agonists (GLP-1 RA) therapy vs. conventional hypoglycemic drugs: arrhythmic burden, hospitalizations for heart failure, and CRTd responders rate Intravascular Ultrasound Assessment of In-Stent Restenosis in Saphenous Vein Grafts Usefulness of intravascular ultrasound guidance in percutaneous coronary intervention with second-generation drug-eluting stents for chronic total occlusions (from the Multicenter Korean-Chronic Total Occlusion Registry)
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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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