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Carotid plaque characteristics by computed Tomography: A diagnostic accuracy systematic review

. 2025 Jun ; 58 () : 101656. [epub] 20250321

Status PubMed-not-MEDLINE Language English Country Ireland Media electronic-ecollection

Document type Journal Article, Review

Links

PubMed 40213415
PubMed Central PMC11982955
DOI 10.1016/j.ijcha.2025.101656
PII: S2352-9067(25)00059-4
Knihovny.cz E-resources

Beyond the stenosis degree, the carotid plaque morphology assessed by computed tomography may improve the stroke risk stratification and is recommended to be considered before interventional treatment according to current guidelines. This study aimed to systematically review the accuracy of computed tomography (CT) to detect carotid plaque characteristics compared to histology in patients with symptomatic and asymptomatic carotid plaques. We registered the protocol in PROSPERO and searched Medline Ovid, Embase.com, Cochrane Library, and Web of Science for diagnostic accuracy of CT in specific carotid plaque characteristic imaging compared to histology, without any search limitation up to May 27, 2022. Out of 8,168 studies, 20 studies that evaluated seven specific plaque characteristics were included in our systematic review. The best diagnostic performance was found for the detection of ulceration (sensitivity range 39.4-100% [mean 79.6%], specificity range 74-100% [mean 93.6%]), followed by calcification (72.7-100% [88.1%], 35.7-100% [80.1%]), lipid-rich necrotic core (63.2-95.6% [81.1%], 60-100% [80.1%]), and intraplaque hemorrhage (61.5-100% [86%], 20-99.5% [67.8%]). Only a few studies evaluated specifically vulnerable, mixed, and fibrous plaque. Diagnostic studies with larger sample sizes are needed, using novel available CT techniques that enable increasing diagnostic performance and decreasing radiation and amount of contrast agent. CT allows for highly accurate detection of carotid plaque features, particularly ulceration and calcification. These results underline the role of routine CT examinations to assess not only stenosis degree but also plaque morphology and individual patient stroke risk to better guide management. Registration: PROSPERO ID CRD42022329690 (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=329690).

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