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A Fully Magnetically Levitated Circulatory Pump for Advanced Heart Failure SPECT and PET in ischemic heart failure Meta-analysis of outcomes after intravascular ultrasound-guided versus angiography-guided drug-eluting stent implantation in 26,503 patients enrolled in three randomized trials and 14 observational studies Association Between Functional Impairment and Medication Burden in Adults with Heart Failure The Prevalence of Myocardial Bridging Associated with Coronary Endothelial Dysfunction in Patients with Chest Pain and Non-Obstructive Coronary Artery Disease Timing of Intervention in Aortic Stenosis Universal Definition and Classification of Heart Failure: A Report of the Heart Failure Society of America, Heart Failure Association of the European Society of Cardiology, Japanese Heart Failure Society and Writing Committee of the Universal Definition of Heart Failure Operator Experience and Outcomes After Left Main Percutaneous Coronary Intervention Angiotensin–Neprilysin Inhibition in Heart Failure with Preserved Ejection Fraction Baseline Features of the VICTORIA (Vericiguat Global Study in Subjects With Heart Failure With Reduced Ejection Fraction) Trial
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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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