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Safety of six-month dual antiplatelet therapy after second-generation drug-eluting stent implantation: OPTIMA-C Randomised Clinical Trial and OCT Substudy 6-Month Versus 12-Month Dual-Antiplatelet Therapy Following Long Everolimus-Eluting Stent Implantation: The IVUS-XPL Randomized Clinical Trial Phenotypic Refinement of Heart Failure in a National Biobank Facilitates Genetic Discovery Cost-Effectiveness of Different Durations of Dual-Antiplatelet Use After Percutaneous Coronary Intervention Consensus from the 5th European Bifurcation Club meeting Intravascular ultrasound predictors for edge restenosis after newer generation drug-eluting stent implantation Positive recommendation for angiotensin receptor/neprilysin inhibitor: First medication approval for heart failure without "reduced ejection fraction" SPECT and PET in ischemic heart failure Effect of Luseogliflozin on Heart Failure With Preserved Ejection Fraction in Patients With Diabetes Mellitus Myofibroblast Phenotype and Reversibility of Fibrosis in Patients With End-Stage Heart Failure
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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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