The diagnostic value of biopsies is highly dependent on the placement of needles. Robotic trajectory guidance has been shown to improve needle positioning, but feedback for real-time navigation is limited. Haptic display of needle tip forces can provide rich feedback for needle navigation by enabling localization of tissue structures along the insertion path. We present a collaborative robotic biopsy system that combines trajectory guidance with kinesthetic feedback to assist the physician in needle placement. The robot aligns the needle while the insertion is performed in collaboration with a medical expert who controls the needle position on site. We present a needle design that senses forces at the needle tip based on optical coherence tomography and machine learning for real-time data processing. Our robotic setup allows operators to sense deep tissue interfaces independent of frictional forces to improve needle placement relative to a desired target structure. We first evaluate needle tip force sensing in ex-vivo tissue in a phantom study. We characterize the tip forces during insertions with constant velocity and demonstrate the ability to detect tissue interfaces in a collaborative user study. Participants are able to detect 91% of ex-vivo tissue interfaces based on needle tip force feedback alone. Finally, we demonstrate that even smaller, deep target structures can be accurately sampled by performing post-mortem in situ biopsies of the pancreas.

翻译：活检的诊断价值高度依赖于针头定位的准确性。机器人轨迹引导已被证明可改善针头定位，但实时导航的反馈方式仍有限。针尖力的触觉显示可通过沿插入路径定位组织结构来提供丰富的针头导航反馈。我们提出了一种协作式机器人活检系统，该系统将轨迹引导与动觉反馈相结合，以辅助医生进行针头定位。机器人调整针头方向，同时由现场控制针头位置的医学专家协作完成插入操作。我们提出了一种基于光学相干断层扫描和机器学习进行实时数据处理的针头设计，用于感测针尖力。我们的机器人装置使操作者能够感应深部组织界面，且不受摩擦力的干扰，从而改善相对于目标结构的针头定位。我们首先在离体组织体模研究中评估了针尖力传感性能，表征了恒定速度插入过程中的针尖力，并通过协作用户研究验证了检测组织界面的能力。参与者仅凭针尖力反馈即可检测出91%的离体组织界面。最后，我们通过对胰腺进行尸检原位活检，证明了即使是更小的深层目标结构也能实现精准取样。