颈动脉超声在心血管疾病中的研究进展:从传统影像到人工智能

Research progress of carotid ultrasound in cardiovascular diseases:from traditional imaging to artificial intelligence

摘要:

我国心血管疾病的发病率与死亡率持续上升,严重威胁国民生命健康。已有大量研究证实,颈动脉超声在心血管疾病的风险预测与诊断中具有重要价值。近年来,人工智能在超声影像领域发展迅速,在颈动脉斑块智能识别、易损特征提取及风险评估中展现出良好应用前景。该文通过系统回顾相关文献,梳理了颈动脉超声从传统影像评价到与人工智能技术融合的研究进展,围绕颈动脉内膜中膜厚度、斑块负荷与易损特征、血流动力学参数等核心指标,探讨其与心血管疾病的关联,同时对人工智能在此领域的应用进展与转化挑战进行了全面梳理与展望,以期为心血管疾病的早期诊断和干预提供理论依据与前沿支持。

Abstract:

The incidence and mortality of cardiovascular diseases (CVD) in China have been continuously rising, posing a serious threat to public health. Extensive studies have demonstrated the important value of carotid ultrasound in the prediction and diagnosis of cardiovascular risks. In recent years, artificial intelligence (AI) has rapidly advanced in the field of ultrasonic imaging, showing great promise in the intelligent identification of carotid plaques, extraction of vulnerable features and assessment of cardiovascular risk. This article systematically reviews the relevant literature to summarize the research progress of carotid ultrasound metrics from traditional imaging to the integration of AI technologies. Focusing on core metrics such as carotid intima-media thickness, plaque burden, vulnerability features, and hemodynamic parameters, it explores the correlation between these indicators and CVD. Furthermore, the review provides a comprehensive outlook on the advances and translational challenges of AI in this field, aiming to provide a theoretical basis and cutting-edge support for the early diagnosis and intervention of CVD.