Dual-Energy Subtraction Technique Using Dual-Source CT: Improved Assessment of Coronary Stenosis Severity and Pericoronary Adipose Tissue Measurement in the Presence of Severe Calcification
Objective: To investigate the value of dual-energy CT subtraction technique in evaluating plaque stenosis severity and pericoronary adipose tissue fat attenuation index (FAI) in patients with severe coronary artery calcification. Methods: Fifty-three patients with suspected or confirmed coronary artery disease who visited Jining No. 1 People’s Hospital from April 2022 to September 2023 were enrolled. All patients underwent dual-energy coronary computed tomography angiography (DE-CCTA) and invasive coronary angiography (CAG) within 60 days, with a calcium score > 400. According to different reconstruction methods, the patients were divided into a standard reconstruction group and a dual-energy subtraction group. Follow-up for major adverse cardiovascular events (MACE) was performed 2 years after CCTA. Results: Using CAG-diagnosed severe stenosis or occlusion as the reference, the diagnostic accuracy and specificity of the standard post-processing group were 86.9% (53/61) and 54.8% (40/73), respectively; those of the dual-energy subtraction group were 82% (50/61) and 93.2% (68/73), respectively. The dual-energy subtraction group showed good consistency and correlation with CAG for coronary artery stenosis detection. The pericoronary adipose tissue attenuation parameter measured by the dual-energy subtraction method could predict MACE events (OR = 1.110, P = 0.022; AUC = 0.670, P = 0.048), suggesting potential superiority in predicting MACE (AUC = 0.593, P = 0.277), although the overall predictive accuracy was modest. Conclusion: Dual-energy subtraction CTA technique has good clinical value for evaluating coronary stenosis severity in patients with severe calcification. Preliminary exploratory evidence also suggests that it may improve the prognostic utility of pericoronary FAI measurement for MACE, though confirmation in larger cohorts is needed.
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