To determine the optimal spatial coverage for CT-imaging of carotid atherosclerosis, allowing the most accurate prediction of the associated risk of ischemic stroke.
In a cross-sectional study, we retrospectively identified 136 consecutive patients admitted to our emergency department with suspected stroke who underwent a CT-angiogram (CTA) of the cervical and intracranial carotid arteries. CTA studies of the carotid arteries were processed using a custom, CT-based automated computer classifier algorithm that quantitatively assesses a battery of carotid CT features. We used this algorithm to individually analyze different lengths of the common and internal carotid arteries for carotid wall features previously shown to be significantly associated with the risk of stroke. Acute stroke patients were categorized into “acute carotid stroke patients” and “non-acute carotid stroke patients” independently of carotid wall CT features. Univariate and multivariate analyses were used to compare the different spatial coverages in terms of their ability to distinguish between the carotid stroke patients and the noncarotid stroke patients using a receiver-operating characteristic curve (ROC) approach.
The carotid wall volume was excellent at distinguishing between carotid stroke patients and noncarotid stroke patients, especially for coverages 20mm or less. The number and location of lipid clusters had a good discrimination power, mainly for coverages 15mm or greater. Measurement of minimal fibrous cap thickness was most associated with carotid stroke when assessed using intermediate coverages. Typically, a 20mm coverage on each side of the carotid bifurcation offered the optimal compromise between the individual carotid features.
We recommend assessment of 20mm of each side of the carotid bifurcation to best characterize carotid atherosclerotic disease and the associated risk of ischemic stroke.El texto completo de este artículo está disponible en PDF.
Keywords : Carotid arteries, Atherosclerosis, Ischemic stroke, Computed tomography