Developing a method to plan robotic straight needle insertion using a probability-based assessment of puncture occurrence

Needle-based treatments for cancer require accurate placement of the needle tip into the target tissue. However, it is often difficult to insert a needle accurately because of the cancer displacement caused by organ deformation. Therefore, developing a planning method based on a numerical simulation that analyzes organ deformation is important for accurate needle insertion. However, predicting the puncture conditions, including the force applied to the needle is not trivial owing to marked variations in the experimental data. The purpose of this research is to develop a novel method for predicting a robust path for straight needle insertion with various puncture points. The method is based on the probabilities of the various puncture conditions and evaluates the expected accuracy of needle placement. First, a probability-based puncture condition was established and the expected accuracy of needle placement was defined. We also performed in vitro needle insertion experiments using a porcine liver. Significant variations in puncture force were observed. Accordingly, we established a probability distribution for the tissue stress caused by the puncture. An in vitro experiment was performed to measure needle placement accuracy using the optimized path. Experimental results show that the proposed method achieves a mean accuracy of 1.5 mm.