Body-Mounted Robotic System for MRI-Guided Shoulder Arthrography: Cadaver and Clinical Workflow Studies - Patel, Niravkumar; Yan, Jiawen; Li, Gang; Monfaredi, Reza; Priba, Lukasz; Donald-Simpson, Helen; Joy, Joyce; Dennison, Andrew; Melzer, Andreas; Sharma, Karun; Iordachita, Iulian; Cleary, Kevin (Frontiers in Robotics and AI, 2021)
This paper presents an intraoperative MRI-guided, patient-mounted robotic system for shoulder arthrography procedures in pediatric patients. The robot is designed to be compact and lightweight and is constructed with nonmagnetic materials for MRI safety. Our goal is to transform the current two-step arthrography procedure( CT/x-ray-guided needle insertion followed by diagnostic MRI) into a streamlined single-step ionising radiation-free procedure under MRI guidance. The MR-conditional robot was evaluated in a Thiel embalmed cadaver study and healthy volunteer studies. The robot was attached to the shoulder using straps and ten locations in the shoulder joint space were selected as targets. For the first target, contrast agent (saline) was injected to complete the clinical workflow. After each targeting attempt, a confirmation scan was acquired to analyse the needle placement accuracy. During the volunteer studies, a more comfortable and ergonomic shoulder brace was used, and the complete clinical workflow was followed to measure the total procedure time. In the cadaver study, the needle was successfully placed in the shoulder joint space in all the targeting attempts with translational and rotational accuracy of 2.07$±$1.22 $mm$ and 1.46$±$1.06 degrees, respectively. The total time for the entire procedure was 94 minutes and the average time for each targeting attempt was 20 minutes in the cadaver study, while the average time for the entire workflow for the volunteer studies was 36 minutes. No image quality degradation due to the presence of the robot was detected. This Thiel-embalmed cadaver study along with the clinical workflow studies on human volunteers demonstrated the feasibility of using an MR-conditional, patient-mounted robotic system for MRI-guided shoulder arthrography procedure. Future work will be focused on moving the technology to clinical practice.