Session: 06-05-01: Biomedical Devices

Paper Number: 111812

111812 - A Model to Predict Deflection of an Active Tendon-Driven Notched Needle Inside Soft Tissue 

The last decade has witnessed major progress in the field of minimally invasive and robotic-assisted surgeries. Needle insertion, a minimally invasive technique, has proven its efficacy in procedures such as brachytherapy, ablation, drug delivery, and biopsy. Manual needle steering inside tissue remains a challenging task due to complex needle-tissue interactions, needle and tissue movement, lack of actuation and control, as well as poor sensing and visualization. Recently, active tendon-driven notched needles and robotic manipulation systems have been proposed to assist surgeons to guide the needles in desired trajectories towards target positions.

This work introduces, for the first time, a new mechanics-based model according to Euler-Bernoulli beam theory to predict deflection of the active tendon-driven notched needle inside soft tissue for intention to use in model-based robotic control.

The overall potential energy of the system, consisting of the energy stored in the needle and the tissue and the external work applied to the needle during a needle insertion task, was used to model the needle deflection. The total stored energy in the system was represented by the energy stored in the system due to the needle displacement and the work applied to the system. The energy terms include the strain energy due to the needle bending, the energy stored in the system due to displaced tissue, the work applied at the tip due to the needle-tissue interactions, and the work applied by the internal tendons of the needle. The model was developed to predict needle deflection in single-layer and multi-layer tissues.

To validate the proposed deflection model, three sets of active needle insertion experiments with bevel-tip and conical-tip active needle into single-layer and two-layer phantom tissues were performed.

The active tendon-driven notched needle was made of superelastic nitinol tube (Johnson Matthey, London, UK) with an inner and outer diameter of 2.00 and 1.47mm, respectively. Notches were carved on the tube with an average width of 0.39mm and depth of 1.68mm, producing a flexible section. An internal tendon (0.10mm diameter SMA wire) was attached near the distal end of the flexible section for actuation and consequent bending of the needle.

A robotic needle insertion system was used to insert and actuate the active tendon-driven notched needle inside a phantom tissue. The robotic system consists of (i) a needle manipulation system, which comprises of a Maxon motor that is programmed to pull the tendon and actuate (bend) the active needle, (ii) an ultrasound machine (Chison, ECO 5) and an Arducam USB camera to track the needle tip in real time, and (iii) a linear motorized stage (Velmex, Inc., Bloom- field, NY) and a guide template for axial movement (insertion) of the active needle inside the tissue.

Additionally, a real-time robot-assisted ultrasound tracking (R-AUST) method, developed in our previous work, was used in this work to track the needle tip in real time during needle insertion. Real-time tracking of the needle tip was challenging especially in needle insertions in two-layer tissue. The R-AUST, with some improvement, was successful in real-time tracking of the needle tip where tracking complications have been observed. The improved tracking was achieved by integrating the R-AUST method with needle shape prediction.  It was shown that the improved tracking method resulted in improved model validation in needle insertions in two-layer tissue.

Overall, the needle insertion experiments showed that the model predicts the needle deflection with an average error of 0.61±0.18mm and 0.48±0.16mm for the bevel-tip and conical-tip active needle insertion in single-layer phantom tissue, respectively, and an average error of 0.81±0.17mm for the conical-tip active needle insertion in two-layer phantom tissue. This work concludes that the model is able to predict active tendon-driven needle deflection inside tissue with reasonable accuracy appropriate for model-based control systems.

Presenting Author: Bardia Konh University of Hawaii at Manoa, Mech Eng Dept

Presenting Author Biography: Bardia Konh received his B.Sc. from K. N. Toosi University of Technology in 2007, and his M.S. from Free University of Science and Research in 2011 both in Mechanical Engineering in Tehran, Iran. He received his Ph.D. in Mechanical Engineering from Temple University, Philadelphia in 2016.
He is currently an Associate Professor at the Department of Mechanical Engineering at the University of Hawaii at Manoa. He is the founder and director of the Advanced Materials and Medical Instruments (AMMI) Laboratory, which brings together physicians and engineers to solve challenging clinical problems.
Bardia's research interests include surgical robotics, medical device design, image-guided surgery, and continuum robotics. Bardia is a recipient of National Institute of Health (NIH) Mentored Quantitative Career Development Award (K25). His research is also funded by various sources such as National Science Foundation (NSF), Hawaii Community Foundation (HCF), and University of Hawaii Cancer Center (UHCC).

Authors:

Blayton Padasdao University of Hawaii at Manoa
Bardia Konh University of Hawaii at Manoa, Mech Eng Dept