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.

通过机器人生物组织活检系统，配合视觉辅助，运用光学相干断层扫描技术进行针尖力传感，收集来自医学专家对深层组织的意见，以提高针对性和准确性。