Echogenicity of carotid plaques as a predictor of regression following lipid-lowering therapy

颈动脉斑块回声强度可预测降脂治疗后斑块消退情况

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Abstract

OBJECTIVE: Atherosclerotic plaque regression under lipid-lowering therapy shows considerable individual variation, and the factors influencing this variability remain incompletely understood. This study aimed to investigate the relationship between carotid plaque echogenicity and plaque regression in patients receiving lipid-lowering therapy, and to identify ultrasound characteristics that might predict plaque regression. METHODS: A total of 838 patients with carotid plaques receiving lipid-lowering therapy were enrolled between July 2020 and May 2024 and followed up for 12 months. Carotid ultrasound was performed at baseline and follow-up to evaluate plaque characteristics. Plaque regression was defined as meeting any of the following criteria: (1) reduction in plaque area ≥ 5%, (2) decrease in plaque thickness ≥ 0.4 mm, or (3) reduction in plaque number, as assessed by vascular ultrasound imaging. Plaque echogenicity was classified into three types: hypoechoic, hyperechoic, and mixed echogenicity. Cox proportional hazards regression analysis was performed to assess the association between plaque echogenicity and plaque regression, adjusting for potential confounding factors. RESULTS: Hypoechoic plaques showed higher rates of regression (72.8%) compared to hyperechoic (37.7%) and mixed echogenicity plaques (50.0%) (p < 0.001). After adjusting for confounding variables, hypoechoic plaques exhibited greater odds of regression compared to hyperechoic plaques (adjusted HR = 4.52, 95% CI: 3.18-6.43, p < 0.001). Additionally, the median percentage reduction in plaque size was more pronounced in hypoechoic plaques, (15.2%, IQR: 7.7-22.3%) compared with other echogenicities (p < 0.001). CONCLUSION: Carotid plaque echogenicity is strongly associated with the likelihood plaque regression, with hypoechoic plaques exhibiting higher regression rates and greater reductions in plaque size. These findings may help guide personalized treatment strategies and improve risk assessment.

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