In vivo detection of lipid-core plaques by coronary CT angiography: A head-to-head comparison with histologic findings

Abstract

Objective: We sought to distinguish lipid plaques using a CT quantitative pixel density histogram, based on the pathological diagnosis of lipid cores as the gold standard. Materials and Methods: Eight patients awaiting heart transplantation due to end-stage coronary heart disease underwent coronary CT angiography (CCTA) spectroscopy prior to heart transplantation; coronary artery pathological analysis was performed for all patients. Lipid-core plaques were defined pathologically as manifesting a lipid core diameter > 200 μm, a circumference > 60 degrees, and a cap thickness < 450 μm. The percentage distributions of CT pixel attenuation ≤ 20, 30, 40, and 50 HU were calculated using quantitative histogram analysis. Results: A total of 271 transverse sections were co-registered between CCTA and pathological analysis. Overall, 26 lipid cores and 16 fibrous plaques were identified by pathological analysis. There was no significant difference in median CT attenuation between the lipid and fibrous plaques (51 HU [interquartile range, 46–63] vs. 57 HU [interquartile range, 50–64], p = 0.659). The median percentage of CT pixel attenuation ≤ 30 HU accounted for 11% (5–17) of lipid-core plaques and 0% (0–2) of fibrous plaques (p < 0.001). The sensitivity and specificity of the method for diagnosing lipid plaques by the average CT pixel attenuation ≤ 30 HU were 80.8% and 87.5%, respectively. The area under the receiver operator characteristics curve was 0.898 (95% confidence interval: 0.765–0.970; 3.0% was the best cut-off value). The diagnostic performance was significantly higher than those of the average pixel CT attenuation percentages ≤ 20, 40, and 50 HU and the mean CT attenuation (p < 0.05). Conclusion: In in vivo conditions, with the pathological lipid core as the gold standard, quantification of the percentage of average CT pixel attenuation ≤ 30 HU in the histogram can be useful for accurate identification of lipid plaques.