Differentiation of Atherosclerotic Carotid Plaque Components with Dual-Energy Computed Tomography

Objectives: Carotid plaque vulnerability is a strong predictor of recurrent ipsilateral stroke, but differentiation of plaque components using conventional computed tomography (CT) is suboptimal. The aim of our study was to evaluate the ability of dual-energy CT (DECT) to characterize atherosclerotic carotid plaque components based on the effective atomic number and effective electron density using magnetic resonance imaging (MRI) and, where possible, histology as the reference standard. Materials and Methods: Patients with recent cerebral ischemia and a ≥2-mm carotid plaque underwent computed tomography angiography and MRI. A subgroup underwent carotid endarterectomy. Trained observers delineated plaque components on histology or MRI, independent of computed tomography angiography. DECT was coregistered with MRI and/or histology. Intraplaque hemorrhage (IPH), lipid-rich necrotic core (LRNC), fibrous tissue, and calcifications were delineated on DECT, and ρ_eff and Z_eff values were determined in the derivation cohort (n = 55). Spatial separation of these components was evaluated in a ρ_eff-Z_eff-cluster plot. Ranges that optimally differentiate plaque features were determined. For validation, plaque components were quantified in the validation cohort (n = 29) using these ρ_eff-Z_eff ranges and literature-based Hounsfield unit (HU) ranges and correlated to MRI volumes. Results: Eighty-four participants (68 ± 8 years; 55 male) were evaluated. In the derivation cohort, plaque components were well separated on the cluster plot, resulting in the following ranges: IPH:ρ_eff < 1.15, Z_eff < 7.5, LRNC:ρ_eff < 1.15, Z_eff:7.5–8.75, fibrous tissue:ρ_eff < 1.15, Z_eff > 8.75, and calcifications: ρ_eff > 1.15, Z_eff > 0. In the validation cohort, significant correlations were found between ρ_effZ_eff-based and MRI plaque volumes for fibrous tissue (r = 0.69, P < 0.001), LRNC (r = 0.94, P < 0.001), IPH (r = 0.35, P = 0.03), and calcifications (r = 0.70, P < 0.001). Lower correlations were found between HU-based and MRI plaque volumes for fibrous tissue (r = 0.40, P = 0.02), LRNC (r = 0.86, P < 0.001), and calcifications (r = 0.47, P = 0.005), with no correlation for IPH (r = 0.02, P = 0.45). Conclusions: We determined ρ_eff-Z_eff ranges for plaque assessment. ρ_eff-Z_effbased volumes showed strong-to-very strong correlations with MRI for LRNC, fibrous tissue, and calcifications and a weak correlation for IPH. ρ_eff-Z_eff-based volumes demonstrated superior agreement with MRI for all plaque components compared with HU-based volumes, highlighting the potential of DECT for the identification of patients with vulnerable plaques.