Carotid perivascular fat attenuation on CT angiography as an imaging biomarker for inflammation in carotid atherosclerosis: a systematic review and meta-analysis

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Abstract

Aims

Carotid atherosclerosis is a leading cause of ischemic stroke, driven by plaque inflammation. While current carotid imaging focuses on luminal stenosis, quantitative perivascular adipose tissue attenuation (PVAT) on computed tomography angiography has emerged as a potential non-invasive biomarker for arterial inflammation and plaque instability in coronary arteries. This systematic review and meta-analysis consider the utility of PVAT for imaging and risk-stratifying inflamed and vulnerable carotid atherosclerotic plaques.

Methods and Results

Following PRISMA guidelines, a systematic literature search identified 11 studies suitable for meta-analysis, incorporating 2316 patients. We compared continuous PVAT measures between symptomatic and asymptomatic carotid arteries using mean differences and 95% confidence intervals, employing a random-effects meta-analysis due to substantial heterogeneity (I² = 92%). The pooled mean difference (MD) was 12.63 HU (95% CI: 8.39-16.88), indicating significantly higher PVAT in symptomatic arteries. While funnel plot asymmetry was visually observed, Egger’s test (intercept = 7.29, p = 0.044) confirmed statistically significant publication bias, highlighting the need to apply caution when interpreting the results given the high heterogeneity. Notably, the leave-one-out sensitivity analysis showed no significant change in the overall p-value or substantial shifts in statistical heterogeneity.

Conclusion

This meta-analysis supports PVAT as a promising non-invasive imaging marker for inflammation and vulnerable plaques in symptomatic carotid atherosclerosis. The findings, while subject to heterogeneity and requiring further validation against conflicting individual study results, suggest a possible role of carotid PVAT for risk stratification. Future directions may PVAT use for monitoring treatment response in clinical trials.

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