Utility of Dual-Layer Spectral-Detector CTA to Characterize Carotid Atherosclerotic Plaque Components: An Imaging-Histopathology Comparison in Patients Undergoing Endarterectomy.

2021 
Background: The composition of non-calcified portions of carotid atherosclerotic plaque represents an important marker of plaque vulnerability and ischemia risk. Objective: To assess the utility of dual-layer spectral-detector CTA (DLCTA) parameters for carotid plaque component characterization, using histologic results from carotid endarterectomy (CEA) as reference. Methods: Seven patients (5 male, 2 female; 61.6±8.5 years old) with carotid plaque awaiting CEA were prospectively enrolled and underwent preoperative supra-aortic DLCTA. A neuroradiologist and pathologist performed joint slice-by-slice review of histologic slices of resected plaques and CTA images. ROIs were placed on non-calcified components [lipid-rich necrotic core (LRNC), intraplaque hemorrhage (IPH), fibrous tissue, loose matrix (LM)] on CTA images in comparison with corresponding histologic slices using anatomic landmarks. For each ROI, attenuation was recorded for polyenergetic images (CTPI) and virtual monoenergetic images with keV ranging from 40-140 (CT40-140keV); attenuation spectrum curve slope was calculated; and Z-effective value (representing effective atomic number) was recorded. DLCTA parameters were compared among plaque components. Results: Seven plaques with a total of 65 slices and 364 ROIs (159 fibrous tissue, 96 LRNC, 86 loose matrix, 23 IPH) were analyzed. All parameters (CTPI, CT40-140keV, slope from 40 to 140 keV, Z-effective value) showed significant differences between LRNC and the other components (all p<.001). For example, mean CTPI was 37.1±15.1 HU for LRNC, 58.4±21.6 HU for IPH, 69.7±20.5 HU for fibrous tissue, and 69.6±19.6 HU for loose matrix; mean CT40keV was 28.1±36.7 HU for LRNC, 87.5±48.9 HU for IPH, 106.3±47.5 HU for fibrous tissue, and 102.6±48.0 HU for loose matrix. AUC for differentiating LRNC from other components was highest (0.945) for CT40kev and decreased with higher keV; AUC for CTPI was 0.908. CT40kev also had highest accuracy (90.4%); at cutoff of 55.7 HU, CT40kev had 88.5% sensitivity and 90.9% specificity. For differentiating IPH from fibrous tissue and loose matrix, AUC was highest at 0.652 for CTPI and 0.645 for CT40kev. Conclusion: DLCTA showed strong performance in differentiating LRNC from other non-calcified plaque components; CT40kev had highest accuracy, outperforming conventional polyenergetic images. Clinical Impact: DLCTA parameters may help characterize carotid plaque composition as a marker of vulnerable plaque and ischemia risk.
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