Computed tomography segmental calcium score (SCS) to predict stenosis severity of calcified coronary lesions.

Abstract

To estimate the probability of ≥ 50% coronary stenoses based on computed tomography (CT) segmental calcium score (SCS) and clinical factors. The Institutional Review Board approved the study. A training sample of 201 patients underwent CT calcium scoring and conventional coronary angiography (CCA). All patients consented to undergo CT before CCA after being informed of the additional radiation dose. SCS and calcification morphology were assessed in individual coronary segments. We explored the predictive value of patient's symptoms, clinical history, SCS and calcification morphology. We developed a prediction model in the training sample based on these variables then tested it in an independent test sample. The odds ratio (OR) for ≥ 50% coronary stenosis was 1.8-fold greater (p = 0.006) in patients with typical chest pain, twofold (p = 0.014) greater in patients with acute coronary syndromes, twofold greater (p < 0.001) in patients with prior myocardial infarction. Spotty calcifications had an OR for ≥ 50% stenosis 2.3-fold (p < 0.001) greater than the absence of calcifications, wide calcifications 2.7-fold (p < 0.001) greater, diffuse calcifications 4.6-fold (p < 0.001) greater. In middle segments, each unit of SCS had an OR 1.2-fold (p < 0.001) greater than in distal segments; in proximal segments the OR was 1.1-fold greater (p = 0.021). The ROC curve area of the prediction model was 0.795 (0.95 confidence interval 0.602-0.843). Validation in a test sample of 201 independent patients showed consistent diagnostic performance. In conjunction with calcification morphology, anatomical location, patient's symptoms and clinical history, SCS can be helpful to estimate the probability of ≥ 50% coronary stenosis.

• Authors: Francesca Pugliese, M G M Hunink, Willem B Meijboom, Katarzyna Gruszczynsnka, Marco Rengo, Lu Zou, Ian Baron, Marcel L Dijkshoorn, Gabriel P Krestin, Pim J de Feyter
• Journal: The international journal of cardiovascular imaging (Int J Cardiovasc Imaging) Vol. 31 Issue 8 Pg. 1663-75 (Dec 2015) ISSN: 1875-8312 [Electronic] United States
• PMID: 26369642 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't, Validation Study)

Topics

• Adult
• Aged
• Aged, 80 and over
• Algorithms
• Area Under Curve
• Chi-Square Distribution
• Coronary Angiography (methods)
• Coronary Artery Disease (diagnostic imaging)
• Coronary Stenosis (diagnostic imaging)
• Coronary Vessels (diagnostic imaging)
• Decision Support Techniques
• Female
• Humans
• Logistic Models
• Male
• Middle Aged
• Multidetector Computed Tomography
• Multivariate Analysis
• Odds Ratio
• Predictive Value of Tests
• ROC Curve
• Reproducibility of Results
• Severity of Illness Index
• Vascular Calcification (diagnostic imaging)
• Young Adult