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 ρeff and Zeff values were determined in the derivation cohort (n = 55). Spatial separation of these components was evaluated in a ρeff-Zeff-cluster plot. Ranges that optimally differentiate plaque features were determined. For validation, plaque components were quantified in the validation cohort (n = 29) using these ρeff-Zeff 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:ρeff < 1.15, Zeff < 7.5, LRNC:ρeff < 1.15, Zeff:7.5-8.75, fibrous tissue:ρeff < 1.15, Zeff > 8.75, and calcifications: ρeff > 1.15, Zeff > 0. In the validation cohort, significant correlations were found between ρeff-Zeff-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 ρeff-Zeff ranges for plaque assessment. ρeff-Zeff-based volumes showed strong-to-very strong correlations with MRI for LRNC, fibrous tissue, and calcifications and a weak correlation for IPH. ρeff-Zeff-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.