Development of a Low-Profile, Piezoelectric Robot for MR-Guided Abdominal Needle Interventions

Samuel Wilcox, Saikat Sengupta, Chuan Huang, Junichi Tokuda, Aiming Lu, David Woodrum, Yue Chen

Abstract:

Purpose
Minimally invasive needle-based interventions are commonly used in cancer diagnosis and treatment, including procedures, such as biopsy, brachytherapy, and microwave ablation. Although MR-guided needle placement offers several distinct advantages, such as high-resolution target visualization and accurate device tracking, one of the primary limitations that affect its widespread adoption is the ergonomic constraints of the closed-bore MRI environment, requiring the patients to be frequently moved in and out to perform the needle-based procedures. This paper introduces a low-profile, body-mounted, MR-guided robot designed to address this limitation by streamlining the operation workflow and enabling accurate needle placement within the MRI scanner.

Methods
The robot employs piezoelectric linear actuators and stacked Cartesian XY stages to precisely control the position and orientation of a needle guide. A kinematic model and control framework was developed to facilitate accurate targeting. Additionally, clinical workflow for the liver interventions was developed to demonstrate the robot’s capability to replicate existing procedures. The proposed system was validated in benchtop environment and 3T MRI scanner to quantify the system performance.

Results
Experimental validations conducted in free space demonstrated a position accuracy of 2.38 ± 0.94 mm and orientation error of 1.40 ± 2.89°. Additional tests to confirm MR-conditionality and MR-guided phantom placements were carried out to assess the system’s performance and safety in MRI suite, yielding a position error of 2.01 ± 0.77 mm and an orientation error of 1.57 ± 1.31°.

Conclusion
The presented robot shows exceptional compatibility with a wide range of patients and bore sizes while maintaining clinically significant accuracy. Future work will focus on the validations in dynamic liver environments.