CT血管成像（Computed Tomography Angiography，CTA）在临床上被广泛应用于血管病变的诊断，然而，CTA存在X线辐射损伤、对比剂外渗和对比剂肾病的3大风险。本文综述了国内外最新文献研究结果，首先介绍“三低”剂量（低辐射剂量、低对比剂流速和总量）下行CTA扫描的理论基础与实现方式|其次介绍不同等级与强度的迭代重建算法在改善低剂量图像质量的能力|最后介绍基于人工智能的深度学习算法在改善低剂量图像质量的能力，以及相较于迭代重建技术的优势。因此，本文不仅可以指导放射技师正确使用“三低”剂量与图像重建算法行CTA扫描，而且结合最新的图像重建算法（基于人工智能深度学习算法）在低剂量CTA中的研究进展进行综述，为后续研究提供参考。

CT angiography (CTA) is widely used clinically in the diagnosis of vascular disease. However, CTA has three major risks of X-ray radiation damage, contrast extravasation and contrast nephropathy. This article summarized the latest literature research results at home and abroad. Firstly, it introduced the theoretical basis and implementation of CTA scanning in the “three low” doses (low radiation dose, low contrast agent ?ow rate and total amount). Secondly, it introduced the ability of iterative reconstruction algorithms with different levels and intensities to improve the image quality of low-dose. Finally, the ability of deep learning algorithms based on arti?cial intelligence to improve the image quality of low-dose was introduced, as well as their advantages over iterative reconstruction algorithms. Therefore,this paper can not only guide the radiographers to correctly use the “three low” dose and image reconstruction algorithm for CTA scanning, but also provide reference for the follow-up research combined with the latest image reconstruction algorithm (based on arti?cial intelligence deep learning algorithm) in low-dose CTA.