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Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
Published on: August 28, 2018
Non-invasive detection of coronary artery disease in patients with left bundle branch block using 64-slice computed
Saïd Ghostine1, Christophe Caussin, Béatrice Daoud
1Department of Cardiology, Marie Lannelongue Hospital, Le Plessis Robinson, France. ghostine@ccml.com
Insights
64-slice computed tomography (CT) accurately identifies coronary artery disease (CAD) in patients with left bundle branch block (LBBB). A normal CT scan can help avoid invasive procedures for these high-risk patients.
Area of Science:
- Cardiology
- Radiology
- Medical Imaging
Background:
- Left bundle branch block (LBBB) is associated with increased cardiac mortality, primarily due to underlying coronary artery disease (CAD).
- Traditional non-invasive stress tests have limited diagnostic performance in LBBB patients, often necessitating conventional coronary angiography (CCA).
Purpose of the Study:
- To evaluate the diagnostic accuracy of 64-slice computed tomography (CT) for detecting significant coronary artery disease (CAD) in patients with complete left bundle branch block (LBBB).
Main Methods:
- Sixty-six patients with complete LBBB underwent 64-slice CT prior to CCA.
- CT scan accuracy for detecting stenosis (>50% lumen narrowing) was compared against quantitative coronary angiography.
- Analysis included all coronary segments, irrespective of image quality limitations.
Main Results:
- 64-slice CT demonstrated high accuracy in identifying CAD by patient (95% overall accuracy, 97% sensitivity, 95% specificity).
- Segmental analysis showed 72% sensitivity and 99% specificity for detecting significant stenosis.
- Improved image quality was noted at lower heart rates.
Conclusions:
- 64-slice CT is a highly accurate tool for diagnosing significant CAD in patients with complete LBBB in routine clinical practice.
- A negative CT scan in this population effectively serves as a reliable filter, potentially preventing unnecessary invasive diagnostic procedures.
Objectives:
The goal of this study was to evaluate the diagnostic accuracy of 64-slice computed tomography (CT) to identify coronary artery disease (CAD) in patients with complete left bundle branch block (LBBB).
Background:
Left bundle branch block increases risk of cardiac mortality, and prognosis is primarily determined by the underlying coronary disease. Non-invasive stress tests have limited performance, and conventional coronary angiography (CCA) is usually required.
Methods:
Sixty-six consecutive patients with complete LBBB and sinus rhythm admitted for CCA were enrolled. Computed tomography was performed 3 +/- 3.9 days before CCA. The accuracy of 64-slice CT to detect significant stenosis (>50% lumen narrowing) was compared with quantitative coronary angiography. All segments were analyzed regardless of image quality from coronary calcification or motion artifacts. Results were analyzed by patient and by coronary segment (990) using the American Heart Association 15-segment model.
Results:
Lower heart rates were associated with improved image quality. Computed tomography correctly identified 35 of 37 (95%) patients without significant stenosis and 28 of 29 (97%) patients with significant stenosis on CCA. Computed tomography correctly assessed 68 of 94 (72%) significant stenosis. Overall, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 64-slice CT for identifying CAD by patient was 95%, 97%, 95%, 93%, and 97%, respectively, and by segment was 97%, 72%, 99%, 91%, and 97%, respectively.
Conclusions:
In a routine clinical practice, 64-slice CT detects with excellent accuracy a significant CAD in patients with complete LBBB. A normal CT in this clinical setting is a robust tool to act as a filter and avoid invasive diagnostic procedures.
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