Journal List > Korean Circ J > v.37(4) > 1016209

Choi, Youn, Jung, Choi, Lee, Park, Oh, Chung, Seung, Kim, and Choi: The Association between Coronary Artery Calcification on MDCT and Angiographic Coronary Artery Stenosis

Abstract

Background and Objectives

The assessment of CT-derived coronary artery calcification (CAC) has been used as a surrogate measurement for coronary atherosclerosis. However, the blooming artifact caused by CAC on MDCT is the potential limitation when evaluating the coronary artery stenosis. The aim of this study was to classify the morphologic characteristics of CAC on MDCT and to test whether this new classification predicts the stenotic severity on coronary angiography.

Subjects and Methods

A total of 73 CAC lesions were observed on 64 slice MDCT in the 56 enrolled patients (M:F=33:23, mean age: 66±9.3 years) who underwent coronary angiography. The morphologic types of CAC on 64-slice MDCT were classified into four groups [degree of stenosis (S), shape of the calcification (M), length of the calcification (L) and the number of calcified vessels (N)] with using a scoring system, and this morphologic classification was compared with the angiographic severity of coronary stenosis.

Result

Diffuse (L3), elongated (M2) and multi-vessel (N2) calcified lesions were significantly associated with angiographic coronary artery stenosis (p=0.03, p=0.019 and p=0.002, respectively) On the multivariate regression analysis, multi-vessel CAC was the only independent predictor for significant coronary artery stenosis [p=0.019, β=3.77, CI: 1.23-11.5 (95%)]. The type of stenosis (luminal narrowing ≥50%) accompanying CAC on MDCT was not correlated with the angiographically determined stenosis (p=0.13). A total morphologic score less than 4 had a negative predictive value of 78% for predicting significant coronary artery stenosis.

Conclusion

Our results suggest that the diffuse and multi-vessel CAC on MDCT can predict the coronary artery stenosis; however, the stenosis severity of the lesion accompanying CAC on MDCT might not coincide with the angiographic severity. Therefore, the morphologic classification with this scoring system should be considered for use when evaluating lesion with CAC on MDCT.

Figures and Tables

Fig. 1
The examples of morphologic classification of coronary artery calcification (CAC) on MDCT and comparison with the angiographic severity. A: nonobstructing (S1), elongate (M2), segmental (L2) and single vessel (N1) CAC on MDCT was not actually stenotic lesion on angiography. B: obstructing (S2), elongate (M2), diffuse (L3) and multivessel (N2) CAC was consistent with the diffuse and significant stenosis on angiography. MDCT: multi detector computed tomography.
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Fig. 2
Total score of CAC on MDCT was significantly correlated with only serum creatinine among the cardiovascular risk factors. CAC: coronary artery calcification, MDCT: multi detector computed tomography, SCr: serum creatinine.
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Fig. 3
ROC curve shows that the total score over the 6, it has the sensitivity 75%, specificity 45% and positive predictive value=75%, negative predictive value=60% for predicting the angiographic stenosis. ROC: receiver operating curve.
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Table 1
Morphologic classification of coronary artery calcification
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Table 2
Baseline characteristics of study population
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PCI: percutaneous coronary intervention, TMT: treadmill test, hs-CRP: high sensitive C-reactive protein

Table 3
Lesion characteristics of calcified coronary artery
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χ2=chi square. *: p<0.05, LAD: left anterior descending, RCA: right coronary artery, MDCT: multi detector computed tomography, LCx: left circumflex artery

Table 4
Prediction of angiographic stenosis in coronary calcified lesion on MDCT
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MDCT: multi detector computed tomography

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