Quantitative cardiovascular imaging

Cardiovascular computed tomography in cardiovascular disease: An overview of its applications from diagnosis to prediction

Cardiovascular computed tomography angiography (CTA) is a widely used imaging modality in the diagnosis of cardiovascular disease. Advancements in CT imaging technology have further advanced its applications from high diagnostic value to minimising radiation exposure to patients. In addition to the standard application of assessing vascular lumen changes, CTA-derived applications including 3D printed personalised models, 3D visualisations such as virtual endoscopy, virtual reality, augmented reality and mixed reality, as well as CT-derived hemodynamic flow analysis and fractional flow reserve (FFRCT) greatly enhance the diagnostic performance of CTA in cardiovascular disease. The widespread application of artificial intelligence in medicine also significantly contributes to the clinical value of CTA in cardiovascular disease. Clinical value of CTA has extended from the initial diagnosis to identification of vulnerable lesions, and prediction of disease extent, hence improving patient care and management. In this review article, as an active researcher in cardiovascular imaging for more than 20 years, I will provide an overview of cardiovascular CTA in cardiovascular disease. It is expected that this review will provide readers with an update of CTA applications, from the initial lumen assessment to recent developments utilising latest novel imaging and visualisation technologies. It will serve as a useful resource for researchers and clinicians to judiciously use the cardiovascular CT in clinical practice.

Correlations between the abdominal fat-related parameters and severity of coronary artery disease assessed by computed tomography

Background

Obesity is considered a challenging public problem, which has been proven to be closely associated with coronary artery disease (CAD). Each risk factor of CAD has been separately studied many times in the past, but very few have comprehensively and quantitatively evaluated the relationship between the abdominal fat-related parameters and severity of CAD. The aim of this study was to analyze whether the abdominal fat-related parameters were associated with severity of CAD using abdominal non-enhanced computed tomography (NECT).

Methods

Patients who went through both abdominal NECT and invasive coronary angiography (ICA) were included and retrospectively analyzed. The abdominal fat-related parameters [the ratio of visceral adipose tissue to subcutaneous adipose tissue (VAT/SAT ratio)] and traditional cardiovascular risk factors were evaluated in the participants with or without obstructive CAD. The correlations between the abdominal fat-related parameters and severity of CAD were assessed, and the multivariable logistic regression analysis was performed to investigate the parameters that could be used to predict the severity of CAD.

Results

A total of 223 consecutive subjects (obstructive CAD group, n=117; non-obstructive CAD group, n=106) were analyzed. The VAT/SAT ratio was significantly higher (0.95±0.33 vs. 0.70±0.25, P<0.001) in obstructive CAD (O-CAD) patients than that in non-obstructive CAD (NO-CAD) patients. There was a trend to having nonalcoholic fatty liver disease (NAFLD) in the O-CAD patients than that of NO-CAD (P=0.002); the abdominal aortic calcification (AAC) score in O-CAD patients were higher than that in NO-CAD patients (P<0.001). The multivariable logistic regression analysis demonstrated that VAT/SAT ratio, NAFLD, and AAC score were independent predictors of O-CAD after adjusting the traditional cardiovascular risk factors. The area under the curve (AUC) of the combination of the above risk factors is 0.85, which leads to an increase in AUC than each risk factor alone in differentiating patients with or without O-CAD.

Conclusions

VAT/SAT ratio, NAFLD, and AAC score are correlated with the severity of CAD, indicating their characteristics of being independent risk factors for O-CAD, irrespective of the traditional cardiovascular risk factors. Those CT-derived parameters may make positive contributions to the differentiation of the patients with increased risk of O-CAD.