CBS 2019
CBSMD教育中心
English

科学研究

科研文章

荐读文献

Efficacy and Safety of Dapagliflozin in Heart Failure With Reduced Ejection Fraction According to Age: Insights From DAPA-HF The pyruvate-lactate axis modulates cardiac hypertrophy and heart failure Prdm16 Deficiency Leads to Age-Dependent Cardiac Hypertrophy, Adverse Remodeling, Mitochondrial Dysfunction, and Heart Failure Age-Related Characteristics and Outcomes of Patients With Heart Failure With Preserved Ejection Fraction In patients with stable coronary heart disease, low-density lipoprotein-cholesterol levels < 70 mg/dL and glycosylated hemoglobin A1c < 7% are associated with lower major cardiovascular events Mechanical circulatory support devices in advanced heart failure: 2020 and beyond Mechanical circulatory support devices for acute right ventricular failure Natriuretic Peptide-Guided Heart Failure Therapy After the GUIDE-IT Study Type 2 Diabetes Mellitus and Heart Failure: A Scientific Statement From the American Heart Association and the Heart Failure Society of America Association of Left Ventricular Systolic Function With Incident Heart Failure in Late Life
|<<... 83 84 85 86 87 88 89 ...>>|

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.

>CBS CBS 2019

> CBS 2019

> CBS 2019 注册

> CBS 2019 会议日程

> CBS 2019 学术征集

> CBS 2019 热点

 CBSMD

> CBSMD 网站注册

> 教育中心

> 荐读文献

> Top 10 阅读文献

> 文献导读
CBS 2019 CBS 2019 主席团 教育中心 科研动态
Copyright ⓒ CBS MD Nanjing China. All rights reserved. 京ICP备16025898号-11
联系我们| Top