A novel imaging biomarker for prediction of cerebrovascular ischemic events: Pericarotid fat density

Background: To investigate the relationship between pericarotid fat density measured in carotid CTA and vulnerable carotid plaque. Methods: This retrospective study included 374 participants who underwent carotid CTA between June 1, 2021, and December 1, 2021 (234 males, median age 68 years [interquartile range: 61-75]). Two groups, symptomatic and asymptomatic, were defined based on either diffusion-weighted MRI or a clinical history of acute ischemia or TIA within 6 months before or after CTA. The relationship between pericarotid fat density and cerebrovascular ischemic events was assessed using receiver operating characteristic analysis and binary logistic regression analysis. Results: In the symptomatic group (n = 135), mean pericarotid fat density (-63.3 f 21.7 vs.-81.7 f 16.9 HU, respectively; p <0.001) and median maximum plaque thickness (4 [interquartile range: 3-6] vs. 3.7 [inter- quartile range: 2.6-4.7] mm, respectively; p = 0.002) were higher, while plaque density (42.1 f 19.6 vs. 50.6 f 20.4 HU, respectively; p = 0.001) was lower compared to the asymptomatic group. Pericarotid fat density (OR: 1.038,95% CI: 1.023-1.053, p <0.001) was identified as an independent predictor for symptomatic patients. The optimal cut-off value for pericarotid fat density predicting symptomatic patients was estimated as -74 HU (area under the curve: 0.753, 95% CI:0.699-0.808, p < 0.001). Inter-reader agreement for pericarotid fat density was found to be almost perfect (intraclass correlation coefficient: 0.818,95% CI: 0.770-0.856, p < 0.001). Conclusion: Pericarotid fat density may serve as an imaging biomarker in predicting acute cerebrovascular ischemic events. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.