Exact biopsy planning and careful execution of needle injection is crucial to ensure successful procedure completion as initially intended while minimizing the risk of complications. This study introduces a solution aimed at helping the operator navigate to precisely position the needle in a previously planned trajectory utilizing a mixed reality headset. A markerless needle tracking method was developed by integrating deep learning and deterministic computer vision techniques. The system is based on superimposing imaging data onto the patient’s body in order to directly perceive the anatomy and determine a path from the selected injection site to the target location. Four types of tests were conducted to assess the system’s performance: measuring the accuracy of needle pose estimation, determining the distance between injection sites and designated targets, evaluating the efficiency of material collection, and comparing procedure time and number of punctures required with and without the system. These tests, involving both phantoms and physician participation in the latter two, demonstrated the accuracy and usability of the proposed solution. The results showcased a significant improvement, with a reduction in number of punctures needed to reach the target location. The test was successfully completed on the first attempt in 70% of cases, as opposed to only 20% without the system. Additionally, there was a 53% reduction in procedure time, validating the effectiveness of the system.
精确的活检规划与细致的针头穿刺操作对确保手术按预定方案顺利完成并最大限度降低并发症风险至关重要。本研究提出一种基于混合现实头戴设备的解决方案，旨在辅助操作者沿预设轨迹精准定位穿刺针。通过融合深度学习与确定性计算机视觉技术，开发了无标记点穿刺针追踪方法。该系统通过将影像数据叠加投射至患者体表，使术者能直观感知解剖结构并规划从穿刺点到靶目标的最优路径。研究通过四类实验评估系统性能：穿刺针姿态估计精度测量、穿刺点与靶目标间距测定、取材效率评估，以及对比使用系统前后的手术时间与穿刺次数。其中后两项实验采用体模并邀请医师参与操作，验证了该方案的准确性与实用性。结果显示系统显著提升了操作效能：靶目标命中所需穿刺次数明显减少，70%的案例首次穿刺即成功命中目标（未使用系统时仅为20%），同时手术时间缩短53%，充分验证了该系统的临床应用价值。
肿瘤(癌症)患者之家