In current clinical practice, qualitative or semi-quantitative measures are primarily used to report coronary artery disease on cardiac CT. With advancements in cardiac CT technology and automated post-processing tools, quantitative measures of coronary disease severity have become more broadly available. Quantitative coronary CT angiography has great potential value for clinical management of patients, but also for research. This document aims to provide definitions and standards for the performance and reporting of quantitative measures of coronary artery disease by cardiac CT.

The coronary artery disease reporting and data system (CAD-RADS™) was recently introduced to standardise reporting. We aimed to evaluate the utility of an automatic postprocessing and reporting system based on CAD-RADS™ in suspected coronary artery disease (CAD) patients.
Clinical evaluation was performed in 346 patients who underwent coronary computed tomography angiography (CCTA). We compared deep learning (DL)-based CCTA with human readers for evaluation of CAD-RADS™ with commercially-available automated segmentation and manual postprocessing in a retrospective validation cohort.
Compared with invasive coronary angiography, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the DL model for diagnosis of CAD were 79.02%, 86.52%, 89.50%, 73.94%, and 82.08%, respectively. There was no significant difference between the DL-based and the reader-based CAD-RADS™ grading of CCTA results. Consistency testing showed that the Kappa value between the model and the readers was 0.775 (95% confidence interval [CI]: 0.728-0.823, p < 0.001), 0.802 (95% CI: 0.756-0.847, p < 0.001), and 0.796 (95% CI: 0.750-0.843, p < 0.001), respectively. This system reduces the time taken from 14.97 ± 1.80 min to 5.02 ± 0.8 min (p < 0.001).
The standardised reporting of DL-based CAD-RADS™ in CCTA can accurately and rapidly evaluate suspected CAD patients, and has good consistency with grading by radiologists.

BACKGROUND: High mannose has previously associated with insulin resistance and cardiovascular disease (CVD). Our objective is to establish whether mannose is associated with anatomical evidence of coronary artery disease (CAD).
METHODS: Plasma mannose concentrations were measured by liquid chromatography/tandem mass spectrometry in a discovery cohort (n = 513) and a validation cohort (n = 221) of carefully phenotyped individuals. In both cohorts CAD was quantitated using state-of-the-art imaging techniques (coronary computed coronary tomography angiography (CCTA), invasive coronary angiography and optical coherence tomography). Information on subsequent CVD events/death was collected. Associations of mannose with angiographic variables and biomarkers were tested using univariate and multivariate regression models. Survival analysis was performed using the Kaplan-Meier estimator.
RESULTS: Mannose was related to indices of CAD and features of plaque vulnerability. In the discovery cohort, mannose was a marker of quantity and quality of CCTA-proven CAD and subjects with a mannose level in the top quartile had a significantly higher risk of CVD events/death (p = 3.6e-5). In the validation cohort, mannose was significantly associated with fibrous cap thickness < 65 μm (odds ratio = 1.32 per each 10 μmol/L mannose change [95% confidence interval, 1.05-1.65]) and was an independent predictor of death (hazard ratio for mannose≥vs < 84.6 μmol/L: 4.0(95%CI, 1.4-11.3), p = 0.006).
CONCLUSIONS: The current data add novel evidence that high mannose is a signature of CAD with a vulnerable plaque phenotype, consistently across measures of severity of vessel involvement and independent of the traditional correlates of CVD, and that it is an independent predictor of incident adverse outcomes.

BACKGROUND: Coronary computed tomography angiography (CCTA) is a well-known method for evaluating anatomic coronary stenosis, but the reliability of CCTA to predict cardiovascular events is an issue of controversy.
METHODS: In this prospective observational study, 58 patients with acute chest pain and low-to-moderate risk were selected and CCTA was performed on them. During follow up, the occurrence of major adverse cardiac events (MACE), defined as, cardiac death, myocardial infarction or coronary revascularization, were evaluated. Sensitivity, specificity, and positive and negative predictive values of CCTA for the occurrence of MACE, at the six-month follow up, were also evaluated.
RESULTS: A total of nine (15.5 %) were positive in terms of the MACE criteria and they all had positive CCTA results. It seemed that there was 100% sensitivity for CCTA in predicting the occurrence of MACE. Forty-nine patients had no MACE, among whom 48 patients had negative CCTA. The specificity of CCTA in predicting the occurrence of MACE was 98%. All patients with positive CCTA showed significant stenosis in angiography.
CONCLUSIONS: It appears that CCTA allows us to predict the prognosis of patients with acute chest pain and low-to moderate-risk in terms of MACE occurrence.

Perioperative cardiac events can be a major consequence of surgery. The American College of Cardiology Foundation/American Heart Association has set out guidelines to aid physicians in identifying patients at the highest risk for these events. The guidelines do recommend for some patients to undergo non-invasive cardiac stress testing for further risk stratification, but their sensitivity and specificity for predicting cardiac events is not optimal. With more data emerging of the superior performance of computed coronary tomography angiography (CCTA) compared to non-invasive stress testing, CCTA could be more useful in risk stratification for these patients.