###Intraoperative Magnetic Resonance Imaging-guided Robotic System for Stereotactic Surgery
Project ID: 2228bd1054 (You will need this ID for your application)
Research Theme: Artificial Intelligence and Robotics
UCL Lead department: Medical Physics and Biomedical Engineering
Lead Supervisor: Ziyan Guo
Project Summary:
Stereotaxy is a minimally invasive approach to precisely apply dedicated instrumentation to the target areas. It is one of the treatments for a variety of movement disorders, e.g. Parkinson’s Disease and dystonia. Parkinson’s disease alone will affect over 8.7 million people worldwide by 2030. Since the population is increasingly ageing, the prevalence and incidence numbers are expected to further grow.
Magnetic Resonance Imaging (MRI) is a versatile imaging modality that can provide high-contrast images of soft tissue, e.g. the brain. Despite the many benefits of using MRI in stereotaxy, such as enhancing accuracy and efficiency by compensating for brain shift, the wide use of MRI as intraoperative guidance remains to be seen. This is due to the strong magnetic field and the confined space of the MRI scanner which makes manual operation very difficult. These challenges have directed increasing attention to the development of intraoperative MRI-guided robotic teleoperation systems.
This project is to develop and validate an MRI-compatible robotic system that can precisely navigate stereotactic tools towards the surgical targets under real-time intraoperative MRI guidance. The system will integrate high-performance actuators, dexterous manipulators, MR-based trackers and intraoperative navigation for stereotactic surgery. This multidisciplinary study involves collaboration with clinicians and scientists with a breadth of expertise in stereotactic procedures, healthcare sensors, and medical robotics.
The project involves the development and experimental validation of mechanical and electronic systems for robot-assisted stereotaxy. The robot control of surgical instruments will be validated on the phantom models in lab. MRI-based experiments will be performed to evaluate system’s imaging compatibility and intraoperative navigation.
Candidates with backgrounds in Mechanical Engineering, Electrical and Electronic Engineering, Biomedical Engineering, or relevant experience in mechatronics, medical instrumentation and image navigation are welcome to apply. Hands-on experience in engineering designs, 3D printing, rapid prototyping, system control and integration will be a plus.