Coronary Artery Disease Reporting and Data System: A Comprehensive Review

Non-contrast CT-based radiomics nomogram of pericoronary adipose tissue for predicting haemodynamically significant coronary stenosis in patients with type 2 diabetes

BACKGROUND

Type 2 diabetes mellitus (T2DM) patients have a higher incidence of coronary artery disease than the general population. The aim of this study was to develop a radiomics nomogram of pericoronary adipose tissue (PCAT) based on non-contrast CT to predict haemodynamically significant coronary stenosis in T2DM patients.

METHODS

The study enrolled 215 T2DM patients who underwent non-contrast CT and coronary computed tomography angiography (CCTA). CCTA derived fractional flow reserve (FFR_CT) ≤ 0.80 was defined as hemodynamically significant stenosis.1691 radiomics features were extracted from PCAT on non-contrast CT. Minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) were used to select useful radiomics features to construct Radscore. Logistic regression was applied to select significant factors among Radscore, fat attenuation index (FAI) and coronary artery calcium score (CACS) to construct radiomics nomogram.

RESULTS

Radscore [odds ratio (OR) = 2.84; P < 0.001] and CACS (OR = 1.00; P = 0.023) were identified as independent predictors to construct the radiomics nomogram. The radiomics nomogram showed excellent performance [training cohort: area under the curve (AUC) = 0.81; 95% CI: 0.76-0.86; validation cohort: AUC = 0.83; 95%CI: 0.76-0.90] to predict haemodynamically significant coronary stenosis in patients with T2DM. Decision curve analysis demonstrated high clinical value of the radiomics nomogram.

CONCLUSION

The non-contrast CT-based radiomics nomogram of PCAT could effectively predict haemodynamically significant coronary stenosis in patients with T2DM, which might be a potential noninvasive tool for screening of high-risk patients.

The value of Coronary Artery Disease - Reporting and Data System (CAD-RADS) in Outcome Prediction of CAD Patients; a Systematic Review and Meta-analysis

Introduction

Coronary computed tomographic angiography (CCTA) reporting has traditionally been operator-dependent, and no precise classification is broadly used for reporting Coronary Artery Disease (CAD) severity. The Coronary Artery Disease Reporting and Data Systems (CAD-RADS) was introduced to address the inconsistent CCTA reports. This systematic review with meta-analysis aimed to comprehensively appraise all available studies and draw conclusions on the prognostic value of the CAD-RADS classification system in CAD patients.

Method

Online databases of PubMed, Embase, Scopus, and Web of Science were searched until September 19th, 2022, for studies on the value of CAD-RADS categorization for outcome prediction of CAD patients.

Results

16 articles were included in this systematic review, 14 of which had assessed the value of CAD-RADS in the prediction of major adverse cardiovascular events (MACE) and 3 articles investigated the outcome of all-cause mortality. Our analysis demonstrated that all original CAD-RADS categories can be a predictor of MACE [Hazard ratios (HR) ranged from 3.39 to 8.63] and all categories, except CAD-RADS 1, can be a predictor of all-cause mortality (HRs ranged from 1.50 to 3.09). Moreover, higher CAD-RADS categories were associated with an increased hazard ratio for unfavorable outcomes among CAD patients (p for MACE = 0.007 and p for all-cause mortality = 0.018).

Conclusion

The evidence demonstrated that the CAD-RADS classification system can be used to predict incidence of MACE and all-cause mortality. This indicates that the implementation of CAD-RADS into clinical practice, besides enhancing the communication between physicians and improving patient care, can also guide physicians in risk assessment of the patients and predicting their prognosis.

Exploring nitric oxide as a crucial prognostic biomarker of coronary artery disease

PURPOSE

The study aimed to examine if the polymorphism of the endothelial nitric oxide synthase (eNOS) gene variable number of tandem repeats (VNTR) and the serum NO levels are associated with CAD.

MATERIALS/METHODS

Case-control study, 70 CAD and 30 control subjects were enrolled. The eNOS gene polymorphism was measured by polymerase chain reaction-agarose gel electrophoresis and the serum NO was assessed by using an ELISA plate and reader covering 540 nm.

RESULTS

Uncovering the area under curve (AUC) for serum NO, which was (0.6821), indicating that NO seemed to be a critical prognostic biomarker of CAD; also, glucose, serum creatinine and total bilirubin proved to be significant predictors of CAD with AUC (0.6793, 0.6717 and 0.6662) respectively. Furthermore, higher serum NO levels were associated with the eNOS (ab) genotype. Revealing the intron (a) allele was protective against CAD. Moreover, diminished levels of serum NO in CAD groups compared to controls (P < 0.05). Additionally, Multiple logistic regression analysis shows a significantly high Odds ratio associated with CAD in the Duhok population.

CONCLUSIONS

The eNOS (ab) variant seems to be a protective CAD factor for patients. Low serum NO levels are another risk factor for the advancement of CAD, suggesting their involvement in atherosclerosis. The (a) allele's protective effect is mediated through changes in eNOS promoter activity and higher NO levels.

Effects of Serum LDL-C, CysC, and D-D in Patients with Coronary Atherosclerotic Heart Disease

Objective

To investigate the effects of low-density lipoprotein cholesterol (LDL-C) and serum cystatin C (CysC) combined with D-dimer (D-D) on patients with coronary atherosclerotic heart disease (CHD).

Methods

90 patients with CHD who were admitted to our hospital and diagnosed by coronary angiography (CAG) from February 2020 to June 2021 were selected as the study subjects. 90 patients were grouped according to different types and branches of coronary lesions, and 30 patients with outpatient health check-ups at the same period were selected as the control group, and the differences in serum LDL-C, CysC, and D-D levels between the groups were compared. The logistic regression model was built to explore risk factors affecting the occurrence of CHD. Also, receiver operating characteristic (ROC) curves were drawn to analyze the diagnostic value of LDL-C, CysC, and D-D in CHD.

Results

In the comparison of LDL-C, CysC, and D-D levels, CHD group > control group (P < 0.05); stable angina (SAP) group > unstable angina (UAP) group > acute myocardial infarction (AMI) group (P < 0.05); three-branch group > two-branch group > single-branch group (P < 0.05). The logistic regression model showed that high expression levels of LDL-C, CysC, and D-D, male gender, and combined hypertension were risk factors for CHD. The area under the curve (AUC) of the combination of LDL-C, CysC, and D-D was 0.868, and the sensitivity and specificity were 88.89% and 73.33%, respectively, which are higher than those in single diagnosis (P < 0.05).

Conclusions

LDL-C, CysC, and D-D are highly expressed in CHD samples, and the combination of the three is beneficial to enhance the diagnostic accuracy of clinical CHD.

Investigation of the Frequency of Coronary Artery Anomalies in MDCT Coronary Angiography and Comparison of Atherosclerotic Involvement between Anomaly Types

Coronary artery anomalies (CAAs) are rare anatomical variations characterized by abnormal origin, course, or termination of the coronary arteries. This study aims to identify incidental CAAs in patients who underwent multidetector computed tomography coronary angiography (MDCTCA) to determine their incidence and to evaluate whether there is a difference between CAA types in terms of coronary atherosclerotic involvement. For this purpose, patients who underwent MDCTCA between December 2018 and January 2022 were retrospectively assessed. Of the 5200 MDCTCAs analyzed, CAAs were detected in 136 patients (2.61%). Of these 136 patients, 37 (27.2%) patients had an origin anomaly, 97 (71.3%) had a course anomaly, and 2 (1.5%) had a termination anomaly. There was no statistically significant difference between CAA types in terms of atherosclerotic involvement (p = 0.220). However, atherosclerotic involvement was high in vessels with anomalies when normal vessels with and without anomalies were compared (p = 0.005). Accurate detection of CAAs is vital for endovascular treatment or surgical intervention. MDCTCA is helpful both in the diagnosis of CAA and in the early detection and development of prevention strategies for coronary atherosclerosis.