Three-dimensional image-guided navigation technique for femoral artery puncture

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.