A Preliminary Add-on Differential Drive System for MRI-Compatible Prostate Robotic System
<|reference_start|>A Preliminary Add-on Differential Drive System for MRI-Compatible Prostate Robotic System: MRI-targeted biopsy has shown significant advantages over conventional random sextant biopsy, detecting more clinically significant cancers and improving risk stratification. However, needle targeting accuracy, especially in transperineal MRI-guided biopsies, presents a challenge due to needle deflection. This can negatively impact patient outcomes, leading to repeated sampling and inaccurate diagnoses if cancerous tissue isn't properly collected. To address this, we developed a novel differential drive prototype designed to improve needle control and targeting precision. This system, featuring a 2-degree-of-freedom (2-DOF) MRI-compatible cooperative needle driver, distances the robot from the MRI imaging area, minimizing image artifacts and distortions. By using two motors for simultaneous needle insertion and rotation without relative movement, the design reduces MRI interference. In this work, we introduced two mechanical differential drive designs: the ball screw/spline and lead screw/bushing types, and explored both hollow-type and side-pulley differentials. Validation through low-resolution rapid-prototyping demonstrated the feasibility of differential drives in prostate biopsies, with the custom hollow-type hybrid ultrasonic motor (USM) achieving a rotary speed of 75 rpm. The side-pulley differential further increased the speed to 168 rpm, ideal for needle rotation applications. Accuracy assessments showed minimal errors in both insertion and rotation motions, indicating that this proof-of-concept design holds great promise for further development. Ultimately, the differential drive offers a promising solution to the critical issue of needle targeting accuracy in MRI-guided prostate biopsies.<|reference_end|>
@article{zhao2024a,
    title={A Preliminary Add-on Differential Drive System for MRI-Compatible
  Prostate Robotic System},
    author={Zhanyue Zhao, Yiwei Jiang, Charles Bales, Yang Wang, and Gregory
  Fischer},
    journal={arXiv preprint arXiv:2409.09971},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.09971},
    primaryClass={cs.RO}
}