|Ph.D Student||Glozman Daniel|
|Subject||Flexible Needle Steering and Control|
for Percutaneous Therapies
|Department||Department of Mechanical Engineering||Supervisor||Professor Emeritus Moshe Shoham|
|Full Thesis text|
The trend of contemporary medicine is towards less invasive and more localized therapy. Many routine treatments employed in modern clinical practice involve percutaneous insertion of needles and catheters for biopsy and drug delivery. The aim of a needle insertion procedure is to place the tip of an appropriate needle safely and accurately in a lesion, organ or vessel. Examples of treatments requiring needle insertions include vaccinations, blood/fluid sampling, regional anesthesia, tissue biopsy, cryogenic ablation, brachytherapy, neurosurgery, deep brain stimulation and various minimally invasive surgeries.
Most of the current needle insertion procedures are done blindly by the surgeon relying on their feeling on the tip of the fingers which leads to inaccurate procedures, excessive pain and post-puncture syndromes. The needles used for current procedures are thick and stiff, which drag the tissues during manipulation. There is a clear need for an automatic system that can steer a needle inside a flexible tissue ensuring precise targeting.
In this study we present a robotic system for steering under real-time fluoroscopic guidance a flexible needle in soft-tissue. Given a target and possible obstacle locations, the computer calculates the flexible needle tip trajectory that avoids the obstacle and hits the target. Using an inverse kinematics algorithm the needle base maneuvers required for a tip to follow this trajectory are calculated, enabling a robot to perform controlled needle insertion. Flexible needle insertion into a deformable tissue is modeled as a linear beam supported by virtual springs, where the stiffness coefficients of the springs can vary along the needle. Using this simplified model, the forward and inverse kinematics of the needle are solved analytically, enabling both path planning and path correction in real-time. The needle shape is detected in real-time from fluoroscopic images and the controller commands the needle base motion that minimizes the needle tip error.
This approach was verified experimentally using a robot to maneuver the base of a flexible needle inserted into a muscle and liver tissue. Along the 40mm trajectory that avoids the obstacle and hits the target the error stayed below the 0.5mm level. This study demonstrates the ability to perform close-loop control and steering of a flexible needle by maneuvering the needle base so that its tip achieves a planned trajectory.