Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States of America.
Phys Med Biol. 2023 May 15;68(10). doi: 10.1088/1361-6560/accefa.
Clinical outcomes of transperineal prostate interventions, such as biopsy, thermal ablations, and brachytherapy, depend on accurate needle placement for effectiveness. However, the accurate placement of a long needle, typically 150-200 mm in length, is challenging due to needle deviation induced by needle-tissue interaction. While several approaches for needle trajectory correction have been studied, many of them do not translate well to practical applications due to the use of specialized needles not yet approved for clinical use, or to relying on needle-tissue models that need to be tailored to individual patients.In this paper, we present a robot-assisted collaborative needle insertion method that only requires an actuated passive needle guide and a conventional needle. The method is designed to assist a physician inserting a needle manually through a needle guide. If the needle is deviated from the intended path, actuators shifts the needle radially in order to steer the needle trajectory and compensate for needle deviation adaptively. The needle guide is controlled by a new data-driven algorithm which does not requireinformation about needle or tissue properties. The method was evaluated in experiments with bothandphantoms.The experiments intissue reported a mean final placement error of 0.36 mm with a reduction of 96.25% of placement error when compared to insertions without the use of assistive correction.Presented results show that the proposed closed-loop formulation can be successfully used to correct needle deflection during collaborative manual insertion with potential to be easily translated into clinical application.
经会阴前列腺介入（如活检、热消融和近距离放射治疗）的临床结果取决于为实现有效性而进行的准确置针。然而，由于针-组织相互作用引起的针偏差，长针（通常长 150-200 毫米）的准确放置具有挑战性。尽管已经研究了几种用于校正针轨迹的方法，但由于使用的特殊针尚未获得临床批准，或者由于依赖需要针对个体患者进行调整的针-组织模型，其中许多方法无法很好地转化为实际应用。在本文中，我们提出了一种机器人辅助协作式针插入方法，该方法仅需要一个带驱动器的被动针引导器和一个常规针。该方法旨在辅助医生手动通过针引导器插入针。如果针偏离了预定路径，驱动器会径向移动针，以自适应地改变针轨迹并补偿针偏差。针引导器由一种新的数据驱动算法控制，该算法不需要有关针或组织特性的信息。该方法在人体组织和模型中的实验中得到了验证。在人体组织的实验中，最终的放置误差的平均值为 0.36 毫米，与没有辅助校正的插入相比，放置误差减少了 96.25%。结果表明，所提出的闭环公式可成功用于在协作式手动插入过程中校正针的偏差，并且有可能很容易地转化为临床应用。
