Vessel Pose Estimation for Obstacle Avoidance in Needle Steering Surgery Using Multiple Forward Looking Sensors

During percutaneous interventions in the brain, puncturing a vessel can cause life threatening complications. To avoid such a risk, current research has been directed towards the development of steerable needles. However, there is a risk that vessels of a size which is close to or smaller than the resolution of commonly used preoperative imaging modalities (0.59 × 0.59 × 1 mm) would not be detected during procedure planning, with a consequent increase in risk to the patient. In this work, we present a novel ensemble of forward looking sensors based on laser Doppler flowmetry, which are embedded within a biologically inspired steerable needle to enable vessel detection during the insertion process. Four Doppler signals are used to classify the pose of a vessel in front of the advancing needle with a high degree of accuracy (2° and 0.1 mm RMS errors), where relative measurements between sensors are used to correct for ambiguity. By using a robotic assisted needle insertion process, and thus a precisely controlled insertion speed, we also demonstrate how the setup can be used to discriminate between tissue bulk motion and vessel motion. In doing so, we describe a sensing apparatus applicable to a variety of needle steering systems, with the potential to eliminate the risk of hemorrhage during percutaneous procedures.