Augmented reality navigation with ultrasound-assisted point cloud registration for percutaneous ablation of liver tumors

Purpose We present a novel augmented reality (AR) surgical navigation method with ultrasound-assisted point cloud registration for percutaneous ablation of liver tumors. A preliminary study is carried out to verify its feasibility. Methods Two three-dimensional (3D) point clouds of the liver surface are derived from the preoperative images and intraoperative tracked US images, respectively. To compensate for the soft tissue deformation, the point cloud registration between the preoperative images and the liver is performed using the non-rigid iterative closest point (ICP) algorithm. A 3D AR device based on integral videography technology is designed to accurately display naked-eye 3D images for surgical navigation. Based on the above registration, naked-eye 3D images of the liver surface, planning path, entry points, and tumor can be overlaid in situ through our 3D AR device. Finally, the AR-guided targeting accuracy is evaluated through entry point positioning. Results Experiments on both the liver phantom and in vitro pork liver were conducted. Several entry points on the liver surface were used to evaluate the targeting accuracy. The preliminary validation on the liver phantom showed average entry-point errors (EPEs) of 2.34 ± 0.45 mm, 2.25 ± 0.72 mm, 2.71 ± 0.82 mm, and 2.50 ± 1.11 mm at distinct US point cloud coverage rates of 100%, 75%, 50%, and 25%, respectively. The average EPEs of the deformed pork liver were 4.49 ± 1.88 mm and 5.02 ± 2.03 mm at the coverage rates of 100% and 75%, and the average covered-entry-point errors (CEPEs) were 4.96 ± 2.05 mm and 2.97 ± 1.37 mm at 50% and 25%, respectively. Conclusion Experimental outcomes demonstrate that the proposed AR navigation method based on US-assisted point cloud registration has achieved an acceptable targeting accuracy on the liver surface even in the case of liver deformation.