Remotely Actuated Needle Driving Device for MRI-Guided Percutaneous Interventions: Force and Accuracy Evaluation

Non-Metallic MR-Guided Concentric Tube Robot for Intracerebral Hemorrhage Evacuation

OBJECTIVE

We aim to develop and evaluate an MR-conditional concentric tube robot for intracerebral hemorrhage (ICH) evacuation.

METHODS

We fabricated the concentric tube robot hardware with plastic tubes and customized pneumatic motors. The robot kinematic model was developed using a discretized piece-wise constant curvature (D-PCC) approach to account for variable curvature along the tube shape, and tube mechanics model was used to compensate torsional deflection of the inner tube. The MR-safe pneumatic motors were controlled using a variable gain PID algorithm. The robot hardware was validated in a series of bench-top and MRI experiments, and the robot's evacuation efficacy was tested in MR-guided phantom trials.

RESULTS

The pneumatic motor was able to achieve a rotational accuracy of 0.32°±0.30° with the proposed variable gain PID control algorithm. The kinematic model provided a positional accuracy of the tube tip of 1.39 ± 0.54 mm. The robot was able to evacuate an initial 38.36 mL clot, leaving a residual hematoma of 8.14 mL after 5 minutes, well below the 15 mL guideline suggesting good post-ICH evacuation clinical outcomes.

CONCLUSION

This robotic platform provides an effective method for MR-guided ICH evacuation.

SIGNIFICANCE

ICH evacuation is feasible under MRI guidance using a plastic concentric tube, indicating potential feasibility in future live animal studies.

Toward Robust Partial-Image Based Template Matching Techniques for MRI-Guided Interventions

We have developed an MRI-safe needle guidance toolkit for MRI-guided interventions intended to enable accurate positioning for needle-based procedures. The toolkit allows intuitive and accurate needle angulation and entry point positioning according to an MRI-based plan, using a flexible, patterned silicone 2D grid. The toolkit automatically matches the grid on MRI planning images with a physical silicon grid placed conformally on the patient's skin and provides the Interventional Radiologist an easy-to-use guide showing the needle entry point on the silicon grid as well as needle angle information. The radiologist can use this guide along with a 2-degree-of-freedom (rotation and angulation relative to the entry point) hand-held needle guide to place the needle into the anatomy of interest. The initial application that we are considering for this toolkit is arthrography, a diagnostic procedure to evaluate the joint space condition. However, this toolkit could be used for any needle-based and percutaneous procedures such as MRI-guided biopsy and facet joint injection. For matching the images, we adopt a transformation parameter estimation technique using the phase-only correlation method in the frequency domain. We investigated the robustness of this method against rotation, displacement, and Rician noise. The algorithm was able to successfully match all the dataset images. We also investigated the accuracy of identifying the entry point from registered template images as a prerequisite for a future targeting study. Application of the template matching algorithm to locate the needle entry points within the MRI dataset resulted in an average entry point location estimation accuracy of 0.12 ±0.2 mm. This promising result motivates a more detailed assessment of this algorithm in the future including a targeting study on a silicon phantom with embedded plastic targets to investigate the end-to-end accuracy of this automatic template matching algorithm in the interventional MRI room.

An MR-Conditional Needle Driver for Robot-Assisted Spinal Injections: Design Modifications and Evaluations

This paper introduces design modifications to our MR-Conditional, 2-degree-of-freedom (DOF), remotely-actuated needle driver for MRI-guided spinal injections. The new needle driver should better meet cleaning and sterilization guidelines needed for regulatory approval, preserve the sterile field during intraoperative needle attachment, and offer better ergonomics and intuitiveness when handling the device. Dy-namic and static force and torque required to properly install the needle driver onto our 4-DOF robot base are analyzed, which provide insight into the risks of intraoperative tool attachment in the setting of robot-assisted spinal injections under MRI guidance.

MRI-guided lumbar spinal injections with body-mounted robotic system: cadaver studies

INTRODUCTION

This paper reports the system integration and cadaveric assessment of a body-mounted robotic system for MRI-guided lumbar spine injections. The system is developed to enable MR-guided interventions in closed bore magnet and avoid problems due to patient movement during cannula guidance.

MATERIAL AND METHODS

The robot is comprised by a lightweight and compact structure so that it can be mounted directly onto the lower back of a patient using straps. Therefore, it can minimize the influence of patient movement by moving with the patient. The MR-Conditional robot is integrated with an image-guided surgical planning workstation. A dedicated clinical workflow is created for the robot-assisted procedure to improve the conventional freehand MRI-guided procedure.

RESULTS

Cadaver studies were performed with both freehand and robot-assisted approaches to validate the feasibility of the clinical workflow and to assess the positioning accuracy of the robotic system. The experiment results demonstrate that the root mean square (RMS) error of the target position to be 2.57 ± 1.09 mm and of the insertion angle to be 2.17 ± 0.89°.

CONCLUSION

The robot-assisted approach is able to provide more accurate and reproducible cannula placements than the freehand procedure, as well as to reduce the number of insertion attempts.

Towards Safe In Situ Needle Manipulation for Robot Assisted Lumbar Injection in Interventional MRI

Lumbar injection is an image-guided procedure performed manually for diagnosis and treatment of lower back pain and leg pain. Previously, we have developed and verified an MR-Conditional robotic solution to assisting the needle insertion process. Drawing on our clinical experiences, a virtual remote center of motion (RCM) constraint is implemented to enable our robot to mimic a clinician's hand motion to adjust the needle tip position in situ. Force and image data are collected to study the needle behavior in gel phantoms during this motion, and a mechanics-based needle-tissue interaction model is proposed and evaluated to further examine the underlying physics. This work extends the commonly-adopted notion of an RCM for flexible needles, and introduces new motion parameters to describe the needle behavior. The model parameters can be tuned to match the experimental result to sub-millimeter accuracy, and this proposed needle manipulation method presents a safer alternative to laterally translating the needle during in situ needle adjustments.

MR-Conditional Actuations: A Review

Magnetic resonance imaging (MRI) is one of the most prevailing technologies to enable noninvasive and radiation-free soft tissue imaging. Operating a robotic device under MRI guidance is an active research area that has the potential to provide efficient and precise surgical therapies. MR-conditional actuators that can safely drive these robotic devices without causing safety hazards or adversely affecting the image quality are crucial for the development of MR-guided robotic devices. This paper aims to summarize recent advances in actuation methods for MR-guided robots and each MR-conditional actuator was reviewed based on its working principles, construction materials, the noteworthy features, and corresponding robotic application systems, if any. Primary characteristics, such as torque, force, accuracy, and signal-to-noise ratio (SNR) variation due to the variance of the actuator, are also covered. This paper concludes with a perspective on the current development and future of MR-conditional actuators.

A Fully Actuated Body-Mounted Robotic Assistant for MRI-Guided Low Back Pain Injection

This paper reports the development of a fully actuated body-mounted robotic assistant for MRI-guided low back pain injection. The robot is designed with a 4-DOF needle alignment module and a 2-DOF remotely actuated needle driver module. The 6-DOF fully actuated robot can operate inside the scanner bore during imaging; hence, minimizing the need of moving the patient in or out of the scanner during the procedure, and thus potentially reducing the procedure time and streamlining the workflow. The robot is built with a lightweight and compact structure that can be attached directly to the patient's lower back using straps; therefore, attenuating the effect of patient motion by moving with the patient. The novel remote actuation design of the needle driver module with beaded chain transmission can reduce the weight and profile on the patient, as well as minimize the imaging degradation caused by the actuation electronics. The free space positioning accuracy of the system was evaluated with an optical tracking system, demonstrating the mean absolute errors (MAE) of the tip position to be 0.99±0.46 mm and orientation to be 0.99±0.65°. Qualitative imaging quality evaluation was performed on a human volunteer, revealing minimal visible image degradation that should not affect the procedure. The mounting stability of the system was assessed on a human volunteer, indicating the 3D position variation of target movement with respect to the robot frame to be less than 0.7 mm.