Coronary Artery Disease Risk Factors, Coronary Artery Calcification and Coronary Bypass Surgery

Correlation between echocardiographic calcium score and coronary artery lesion severity on invasive coronary angiography

OBJECTIVES

The direct correlation between Echocardiographic non-coronary calcium score (ECS) and lesion severity on invasive coronary angiography (ICA) is not reported. The aim of the present study was to find the correlation between ECS and Gensini score.

METHODS

One hundred seventy patients aged ≥18 years posted for clinically indicated ICA were included. All the patients underwent standard transthoracic echocardiography. ECS and Gensisni scores were calculated. The primary outcome measure was to find a correlation of ECS with Gensini score, whereas the secondary outcome measure was to correlate ECS with traditional risk factors for coronary artery disease. The Chi-square/Fisher exact test was used to compare qualitative variables. Spearman's correlation analysis was used for assessing the correlation between ECS score and the Gensini score. Receiver-operating characteristic curve analysis was performed to detect the cut-off value of the ECS score.

RESULTS

The correlation of total ECS with Gensini score was positive and statistically significant (r = 0.550, p-value < 0.0001). As ECS increased, the Gensini score increased. ECS value of >1 detected CAD with 56.5% sensitivity, 79.5% specificity. Eight-nine percent of patients who had ECS >1, had Gensini score ≥18, whereas 44.3% of patients who had ECS ≤1, had Gensini score ≥18. The patients with ECS >1 had significantly higher Gensini scores than the patients with ECS ≤1.

CONCLUSIONS

The correlation of total ECS with Gensini score was positive and statistically significant.

[Calcification and atherosclerosis of the coronary arteries]

Calcification is a very common phenomenon in the coronary arteries, which is part of the atherosclerotic process, and the degree of calcification can predict clinical outcomes in patients at high risk of coronary events. Both the degree of calcification and the patterns of its distribution are of prognostic importance, but the relationship of coronary artery calcification with atherosclerotic plaque instability is extremely complex and not fully understood. This article is devoted to the study of calcification markers and their influence on the development of atherosclerotic foci.

Relationship between Automated Coronary Calcium Volumes and a Set of Manual Coronary Lumen Volume, Vessel Volume and Atheroma Volume in Japanese Diabetic Cohort

INTRODUCTION

A high degree of correlation exists between Coronary Artery Diseases (CAD) and calcification of the vessel wall. For Percutaneous Coronary Interventional (PCI) planning, it is essential to have an exact understanding of the extent to which calcium volume is correlated to the lumen, vessel, and atheroma volume regions in the coronary artery, which is unclear in recent studies.

AIM

Four automated Coronary Calcium Volume (aCCV) measurement methods {threshold, Fuzzy c-Means (FCM), K-means, and Hidden Markov Random Field (HMRF)} and its correlation with three manual (experts) coronary parameters namely: Coronary Vessel Volume (mCVV), Coronary Lumen Volume (mCLV), and Coronary Atheroma Volume (mCAV), was determined in a Japanese diabetic cohort.

MATERIALS AND METHODS

Intravascular Ultrasound (IVUS) image dataset from 19 patients (around 40,090 frames) was collected using 40 MHz IVUS catheter (Atlantis^® SR Pro, Boston Scientific^®, pullback speed of 0.5 mm/sec). The methodology consisted of automatically computing the calcium volume in the entire IVUS coronary videos using FCM, K-means, and HMRF based pixel classification and comparing it against the previously published threshold-based method. The Coefficient of Correlation (CC) was then established between the four aCCV and three manually (experts) coronary parameters: mCVV, mCLV, and mCAV computed using iMAP software Boston Scientific^®. Statistical tests (Two-tailed paired Student t-test, Wilcoxon signed rank test, Mann-Whitney test, Chi-square test, and Kolmogorov-Smirnov KS-test) were performed to demonstrate consistency, reliability, and accuracy of the proposed work.

RESULTS

Correlation coefficient of: (a) automated threshold-based volume; (b) automated FCM based volume; (c) automated K-means based volume; and (d) automated HMRF based volume and corresponding three manually (expert's) coronary parameters (mCLV, mCVV, mCAV) were: (0.51, 0.40, 0.48), (0.52, 0.38, 0.49), (0.56, 0.45, 0.52), and (0.57, 0.42, 0.56), respectively. The CC between age and haemoglobin was 0.50.

CONCLUSION

Automated coronary volume measurement using HMRF method is more accurate compared to threshold, FCM, and K-means-based method, since it is more strongly correlated with three expert's readings.