Zhang Yunmeng, Liu Shenglin, Zhang Qiang, Feng Qingmin
Institute of Biomedical Engineering, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Comput Assist Surg (Abingdon). 2025 Dec;30(1):2535967. doi: 10.1080/24699322.2025.2535967. Epub 2025 Jul 28.
Percutaneous femoral arterial access is a fundamental procedure in minimally invasive vascular interventions. However, inadequate visualization of the femoral artery may lead to inaccurate puncture and complications, with reported incidence rates of 3 to 18%. This study proposes a three-dimensional (3D) image-guided navigation system designed to enhance real-time visualization of the target vessel and puncture site during femoral artery access. This system employed an Iterative Closest Point (ICP)-based point cloud algorithm to achieve spatial registration between image space and patient space. An improved ICP method is implemented to optimize surface point cloud alignment, providing higher efficiency and accuracy compared to conventional approaches. Validation experiments were conducted using a standard model and a human phantom. Registration and navigation accuracy were quantified using fiducial registration error (FRE) for spatial alignment, target registration error (TRE) for navigation accuracy, and distance error for puncture precision. The system achieved a FRE of 0.944 mm. On the standard model, the average distance error was 0.885 mm, and the TRE was 0.915 mm. On the human phantom, the average distance error is 0.967 mm, and the average TRE is 0.981 mm. These results confirm the feasibility and effectiveness of the proposed 3D navigation system in guiding femoral artery puncture. All error metrics were within clinically acceptable thresholds, suggesting potential for improved procedural safety and precision in percutaneous vascular interventions.
经皮股动脉穿刺是微创血管介入治疗中的一项基本操作。然而，股动脉可视化不足可能导致穿刺不准确及并发症，据报道其发生率为3%至18%。本研究提出一种三维（3D）图像引导导航系统，旨在增强股动脉穿刺过程中目标血管和穿刺部位的实时可视化。该系统采用基于迭代最近点（ICP）的点云算法来实现图像空间与患者空间之间的空间配准。实施了一种改进的ICP方法以优化表面点云对齐，与传统方法相比，具有更高的效率和准确性。使用标准模型和人体模型进行了验证实验。使用基准配准误差（FRE）进行空间对齐、使用目标配准误差（TRE）进行导航准确性以及使用距离误差进行穿刺精度来量化配准和导航准确性。该系统的FRE为0.944毫米。在标准模型上，平均距离误差为0.885毫米，TRE为0.915毫米。在人体模型上，平均距离误差为0.967毫米，平均TRE为0.981毫米。这些结果证实了所提出的3D导航系统在引导股动脉穿刺方面的可行性和有效性。所有误差指标均在临床可接受阈值范围内，表明在经皮血管介入治疗中提高手术安全性和精度具有潜力。
