ISSN 1004-4140
CN 11-3017/P
Volume 27 Issue 2
Apr.  2018
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HUANG Ren-jun, DAI Hui, LI Yong-gang, GUO Liang, HU Chun-hong, HE Zhi-song. Spectral Computer Tomography Combined with Serum Biomarkers in Coronary Plaque Characteristics Analysis[J]. CT Theory and Applications, 2018, 27(2): 155-163. DOI: 10.15953/j.1004-4140.2018.27.02.03
Citation: HUANG Ren-jun, DAI Hui, LI Yong-gang, GUO Liang, HU Chun-hong, HE Zhi-song. Spectral Computer Tomography Combined with Serum Biomarkers in Coronary Plaque Characteristics Analysis[J]. CT Theory and Applications, 2018, 27(2): 155-163. DOI: 10.15953/j.1004-4140.2018.27.02.03

Spectral Computer Tomography Combined with Serum Biomarkers in Coronary Plaque Characteristics Analysis

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  • Received Date: November 02, 2017
  • Available Online: November 07, 2021
  • Objective: To study the value of spectral CT in analyzing different coronary plaque components and their correlation with different serum levels of biomarker, and to provide a basis for the diagnosis value and differential diagnosis value of spectral CT. Methods: 107 consecutive patients diagnosed with coronary artery disease (CAD) or acute paroxysmal chest pain and discomfort in the anterior region of the heart (65 males and 42 females; mean age, 60 years) underwent coronary artery gemstone spectral imaging. Plaques were divided into 5 groups according to Multi-slice computed tomography (MSCT) criteria and the size of calcification in mixed plaques. Spectral attenuation curve (SAC), effective atomic number (EAN) and basic material decomposition:FAT and HAP technique were used to analyze the plaques. The vulnerability of plaques was evaluated by serum biomarkers including soluble OX40 ligand (sOX40 L), matrix metalloproteinases (MMP-9) and lipoprotein associated phospholipase A2 (Lp-PLA2). The concentrations of the serum biomarkers were detected by ELISA. Results: 159 coronary artery plaques were counted in total. 90 cases of blood samples (42 cases without coronary plaque, 48 cases with coronary plaque) were obtained. By measuring CT density, the plaques were classified as fibrosis group (group 1), soft plaque group (group 2) and pure calcification group (group 3). In addition, mixed plaques with non-spotty calcification group (group 4) and spotty calcification group (group 5) were also analyzed. There were statistically significant differences of CT density, SAC, EAN, HAP and FAT among the five groups (P<0.05), except the FAT value between group1 and group5 as well as between group 2 and group5. The concentrations of serum biomarkers were significantly higher in subjects with coronary atherosclerotic plaques than those in subjects without coronary plaques (P<0.05). There were significant differences of the MMP-9 concentrations between group 2 and group 3 as well as between group3 and group5 (P<0.05). Negative correlations were found as follow:MMP-9 concentration vs. CT density (r=-0.501, P<0.05), MMP-9 concentration vs. EAN (r=-0.372, P<0.05), MMP-9 concentration vs. SAC (r=-0.378, P<0.05) and MMP-9 concentration vs. HAP material density (r=-0.411, P<0.05). Positive correlation was found between serum MMP-9 concentration and FAT material density r=0.34, P<0.05). Receiver operating characteristic curve (ROC) showed cutoff value and area under the curve (AUC) of SAC and EAN and HAP material was 3.41 (AUC=0.633) and 8.91 AUC=0.652) and 96.07 (AUC=0.648) between group 2 and group 5. Conclusion: The results indicate that spectral CT might be promising in differentiating different kinds of atherosclerotic plaques. These four kinds of spectral CT parameters are associated with serum MMP-9 level.
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