Remotely Actuated Needle Driving Device for MRI-Guided Percutaneous Interventions

Deep learning-based automatic pipeline for 3D needle localization on intra-procedural 3D MRI

PURPOSE

Accurate and rapid needle localization on 3D magnetic resonance imaging (MRI) is critical for MRI-guided percutaneous interventions. The current workflow requires manual needle localization on 3D MRI, which is time-consuming and cumbersome. Automatic methods using 2D deep learning networks for needle segmentation require manual image plane localization, while 3D networks are challenged by the need for sufficient training datasets. This work aimed to develop an automatic deep learning-based pipeline for accurate and rapid 3D needle localization on in vivo intra-procedural 3D MRI using a limited training dataset.

METHODS

The proposed automatic pipeline adopted Shifted Window (Swin) Transformers and employed a coarse-to-fine segmentation strategy: (1) initial 3D needle feature segmentation with 3D Swin UNEt TRansfomer (UNETR); (2) generation of a 2D reformatted image containing the needle feature; (3) fine 2D needle feature segmentation with 2D Swin Transformer and calculation of 3D needle tip position and axis orientation. Pre-training and data augmentation were performed to improve network training. The pipeline was evaluated via cross-validation with 49 in vivo intra-procedural 3D MR images from preclinical pig experiments. The needle tip and axis localization errors were compared with human intra-reader variation using the Wilcoxon signed rank test, with p < 0.05 considered significant.

RESULTS

The average end-to-end computational time for the pipeline was 6 s per 3D volume. The median Dice scores of the 3D Swin UNETR and 2D Swin Transformer in the pipeline were 0.80 and 0.93, respectively. The median 3D needle tip and axis localization errors were 1.48 mm (1.09 pixels) and 0.98°, respectively. Needle tip localization errors were significantly smaller than human intra-reader variation (median 1.70 mm; p < 0.01).

CONCLUSION

The proposed automatic pipeline achieved rapid pixel-level 3D needle localization on intra-procedural 3D MRI without requiring a large 3D training dataset and has the potential to assist MRI-guided percutaneous interventions.

Design of a Patient-Specific Respiratory-Motion-Simulating Platform for In Vitro 4D Flow MRI

Four-dimensional (4D) flow magnetic resonance imaging (MRI) is a leading-edge imaging technique and has numerous medicinal applications. In vitro 4D flow MRI can offer some advantages over in vivo ones, especially in accurately controlling flow rate (gold standard), removing patient and user-specific variations, and minimizing animal testing. Here, a complete testing method and a respiratory-motion-simulating platform are proposed for in vitro validation of 4D flow MRI. A silicon phantom based on the hepatic arteries of a living pig is made. Under the free-breathing, a human volunteer's liver motion (inferior-superior direction) is tracked using a pencil-beam MRI navigator and is extracted and converted into velocity-distance pairs to program the respiratory-motion-simulating platform. With the magnitude displacement of about 1.3 cm, the difference between the motions obtained from the volunteer and our platform is ≤ 1 mm which is within the positioning error of the MRI navigator. The influence of the platform on the MRI signal-to-noise ratio can be eliminated even if the actuator is placed in the MRI room. The 4D flow measurement errors are respectively 0.4% (stationary phantom), 9.4% (gating window = 3 mm), 27.3% (gating window = 4 mm) and 33.1% (gating window = 7 mm). The vessel resolutions decreased with the increase of the gating window. The low-cost simulation system, assembled from commercially available components, is easy to be duplicated.

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.

Fully Actuated Body-Mounted Robotic System for MRI-Guided Lower Back Pain Injections: Initial Phantom and Cadaver Studies

This paper reports the improved design, system integration, and initial experimental evaluation of a fully actuated body-mounted robotic system for real-time MRI-guided lower back pain injections. The 6-DOF robot is composed of a 4-DOF needle alignment module and a 2-DOF remotely actuated needle driver module, which together provide a fully actuated manipulator that can operate inside the scanner bore during imaging. The system minimizes the need to move the patient in and out of the scanner during a procedure, and thus may shorten the procedure time and streamline the clinical workflow. The robot is devised with a compact and lightweight structure that can be attached directly to the patient's lower back via straps. This approach minimizes the effect of patient motion by allowing the robot to move with the patient. The robot is integrated with an image-based surgical planning module. A dedicated clinical workflow is proposed for robot-assisted lower back pain injections under real-time MRI guidance. Targeting accuracy of the system was evaluated with a real-time MRI-guided phantom study, demonstrating the mean absolute errors (MAE) of the tip position to be 1.50±0.68mm and of the needle angle to be 1.56±0.93°. An initial cadaver study was performed to validate the feasibility of the clinical workflow, indicating the maximum error of the position to be less than 1.90mm and of the angle to be less than 3.14°.

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.

Body-mounted robotic assistant for MRI-guided low back pain injection

PURPOSE

This paper presents the development of a body-mounted robotic assistant for magnetic resonance imaging (MRI)-guided low back pain injection. Our goal was to eliminate the radiation exposure of traditional X-ray guided procedures while enabling the exquisite image quality available under MRI. The robot is designed with a compact and lightweight profile that can be mounted directly on the patient's lower back via straps, thus minimizing the effect of patient motion by moving along with the patient. The robot was built with MR-conditional materials and actuated with piezoelectric motors so it can operate inside the MRI scanner bore during imaging and therefore streamline the clinical workflow by utilizing intraoperative MR images.

METHODS

The robot is designed with a four degrees of freedom parallel mechanism, stacking two identical Cartesian stages, to align the needle under intraoperative MRI-guidance. The system targeting accuracy was first evaluated in free space with an optical tracking system, and further assessed with a phantom study under live MRI-guidance. Qualitative imaging quality evaluation was performed on a human volunteer to assess the image quality degradation caused by the robotic assistant.

RESULTS

Free space positioning accuracy study demonstrated that the mean error of the tip position to be [Formula: see text] mm and needle angle to be [Formula: see text]. MRI-guided phantom study indicated the mean errors of the target to be [Formula: see text] mm, entry point to be [Formula: see text] mm, and needle angle to be [Formula: see text]. Qualitative imaging quality evaluation validated that the image degradation caused by the robotic assistant in the lumbar spine anatomy is negligible.

CONCLUSIONS

The study demonstrates that the proposed body-mounted robotic system is able to perform MRI-guided low back injection in a phantom study with sufficient accuracy and with minimal visible image degradation that should not affect the procedure.

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

This paper presents a 2 degrees-of-freedom (DOF) remotely actuated needle driving device for Magnetic Resonance Imaging (MRI) guided pain injections. The device is evaluated in phantom studies under real-time MRI guidance. The force and torque asserted by the device on the 4-DOF base robot are measured. The needle driving device consists of a needle driver, a 1.2-meter long beaded chain transmission, an actuation box, a robot controller and a Graphical User Interface (GUI). The needle driver can fit within a typical MRI scanner bore and is remotely actuated at the end of the MRI table through a novel beaded chain transmission. The remote actuation mechanism significantly reduces the weight and size of the needle driver at the patient end as well as the artifacts introduced by the motors. The clinician can manually steer the needle by rotating the knobs on the actuation box or remotely through a software interface in the MRI console room. The force and torque resulting from the needle driver in various configurations both in static and dynamic status were measured and reported. An accuracy experiment in the MRI environment under real-time image feedback demonstrates a small mean targeting error (<; 1.5 mm) in a phantom study.