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

IRE made easy: introducing the robotic grid system for multiple parallel needle insertion in irreversible electroporation treatment

PURPOSE

Accurate needle placement is crucial for successful tumor treatment using the irreversible electroporation (IRE) method. Multiple needles are inserted around the tumor, ideally in parallel, to achieve uniform electric field distribution. This paper presents a robot utilizing a grid system to enable multiple needles insertion while maintaining parallelism between them.

METHODS

The robotic system has two degrees of freedom, which allow for the adjustment of the grid system to accommodate targeting lesions in various positions. The robot's performance was evaluated by testing its accuracy across various configurations and target depth locations, as well as its ability to maintain the needle parallelism.

RESULTS

The robot has dimensions of ϕ 134 mm and a height of 46 mm, with a total weight of 295 g. The system accuracy test showed that the robot can precisely target points across different target depths and needle orientations, with an average error of 2.71 ± 0.68 mm. Moreover, multiple insertions at different grid locations reveal needle orientation deviations typically below 1 ∘ .

CONCLUSION

This study presented the design and validation of a robotic grid system. The robot is capable of maintaining insertion accuracy and needle parallelism during multiple needle insertions at various robot configurations. The robot showed promising results with limited needle deviation, making it suitable for IRE procedures.

Modeling and Control of an MR-Safe Pneumatic Radial Inflow Motor and Encoder (PRIME)

Magnetic resonance (MR) conditional actuators and encoders are the key components for MR-guided robotic systems. In this article, we present the modeling and control of our MR-safe pneumatic radial inflow motor and encoder. A comprehensive model is developed that considers the primary dynamic elements of the system, including: 1) motor dynamics, 2) pneumatic transmission line dynamics, and 3) valve dynamics. After model validation, we present a simplified third order model that facilitates design of a first order sliding mode controller (TO-SMC). Finally, the motor hardware is tested in a 7T MRI. No image distortion or artifacts were observed. We posit the MR-safe motor and dynamic model will lower the entry barriers for researchers interested in MR-guided robots and promote wider adoption of MR-guided robotic systems.

A magnetic resonance conditional robot for lumbar spinal injection: Development and preliminary validation

PURPOSE

This work presents the design and preliminary validation of a Magnetic Resonance (MR) conditional robot for lumbar injection for the treatment of lower back pain.

METHODS

This is a 4-degree-of-freedom (DOF) robot that is 200 × 230 × 130 mm3 in volume and has a mass of 0.8 kg. Its lightweight and compact features allow it to be directly affixed to patient's back, establishing a rigid connection, thus reducing positional errors caused by patient movements during treatment.

RESULTS

To validate the positioning accuracy of the needle by the robot, an electromagnetic (EM) tracking system and a needle with an EM sensor embedded in the tip were used for the free space evaluation with position accuracy of 0.88 ± 0.46 mm and phantom mock insertions using the Loop-X CBCT scanner with target position accuracy of 3.62 ± 0.92 mm.

CONCLUSION

Preliminary experiments demonstrated that the proposed robot showed improvements and benefits in its rotation range, flexible needle adjustment, and sensor protection compared with previous and existing systems, offering broader clinical applications.

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.

Flexible Needle Bending Model for Spinal Injection Procedures

An in situ needle manipulation technique used by physicians when performing spinal injections is modeled to study its effect on needle shape and needle tip position. A mechanics-based model is proposed and solved using finite element method. A test setup is presented to mimic the needle manipulation motion. Tissue phantoms made from plastisol as well as porcine skeletal muscle samples are used to evaluate the model accuracy against medical images. The effect of different compression models as well as model parameters on model accuracy is studied, and the effect of needle-tissue interaction on the needle remote center of motion is examined. With the correct combination of compression model and model parameters, the model simulation is able to predict needle tip position within submillimeter accuracy.

Fluoroscopy-Guided Robotic System for Transforaminal Lumbar Epidural Injections

We present an autonomous robotic spine needle injection system using fluoroscopic image-based navigation. Our system includes patient-specific planning, intra-operative image-based 2D/3D registration and navigation, and automatic robot-guided needle injection. We performed intensive simulation studies to validate the registration accuracy. We achieved a mean spine vertebrae registration error of 0.8 ± 0.3 mm, 0.9 ± 0.7 degrees, mean injection device registration error of 0.2 ± 0.6 mm, 1.2 ± 1.3 degrees, in translation and rotation, respectively. We then conducted cadaveric studies comparing our system to an experienced clinician's free-hand injections. We achieved a mean needle tip translational error of 5.1 ± 2.4 mm and needle orientation error of 3.6 ± 1.9 degrees for robotic injections, compared to 7.6 ± 2.8 mm and 9.9 ± 4.7 degrees for clinician's free-hand injections, respectively. During injections, all needle tips were placed within the defined safety zones for this application. The results suggest the feasibility of using our image-guided robotic injection system for spinal orthopedic applications.

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.

State of the Art and Future Opportunities in MRI-Guided Robot-Assisted Surgery and Interventions

Magnetic resonance imaging (MRI) can provide high-quality 3-D visualization of target anatomy, surrounding tissue, and instrumentation, but there are significant challenges in harnessing it for effectively guiding interventional procedures. Challenges include the strong static magnetic field, rapidly switching magnetic field gradients, high-power radio frequency pulses, sensitivity to electrical noise, and constrained space to operate within the bore of the scanner. MRI has a number of advantages over other medical imaging modalities, including no ionizing radiation, excellent soft-tissue contrast that allows for visualization of tumors and other features that are not readily visible by other modalities, true 3-D imaging capabilities, including the ability to image arbitrary scan plane geometry or perform volumetric imaging, and capability for multimodality sensing, including diffusion, dynamic contrast, blood flow, blood oxygenation, temperature, and tracking of biomarkers. The use of robotic assistants within the MRI bore, alongside the patient during imaging, enables intraoperative MR imaging (iMRI) to guide a surgical intervention in a closed-loop fashion that can include tracking of tissue deformation and target motion, localization of instrumentation, and monitoring of therapy delivery. With the ever-expanding clinical use of MRI, MRI-compatible robotic systems have been heralded as a new approach to assist interventional procedures to allow physicians to treat patients more accurately and effectively. Deploying robotic systems inside the bore synergizes the visual capability of MRI and the manipulation capability of robotic assistance, resulting in a closed-loop surgery architecture. This article details the challenges and history of robotic systems intended to operate in an MRI environment and outlines promising clinical applications and associated state-of-the-art MRI-compatible robotic systems and technology for making this possible.

Design of a 6-DoF Parallel Robotic Platform for MRI Applications

In this work, the design, analysis, and characterization of a parallel robotic motion generation platform with 6-degrees of freedom (DoF) for magnetic resonance imaging (MRI) applications are presented. The motivation for the development of this robot is the need for a robotic platform able to produce accurate 6-DoF motion inside the MRI bore to serve as the ground truth for motion modeling; other applications include manipulation of interventional tools such as biopsy and ablation needles and ultrasound probes for therapy and neuromodulation under MRI guidance. The robot is comprised of six pneumatic cylinder actuators controlled via a robust sliding mode controller. Tracking experiments of the pneumatic actuator indicates that the system is able to achieve an average error of 0.69 ± 0.14 mm and 0.67 ± 0.40 mm for step signal tracking and sinusoidal signal tracking, respectively. To demonstrate the feasibility and potential of using the proposed robot for minimally invasive procedures, a phantom experiment was performed in the benchtop environment, which showed a mean positional error of 1.20 ± 0.43 mm and a mean orientational error of 1.09 ± 0.57°, respectively. Experiments conducted in a 3T whole body human MRI scanner indicate that the robot is MRI compatible and capable of achieving positional error of 1.68 ± 0.31 mm and orientational error of 1.51 ± 0.32° inside the scanner, respectively. This study demonstrates the potential of this device to enable accurate 6-DoF motions in the MRI environment.

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.