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Author Spotlight: Advancing Human Brain Modulation – Optimized Protocols for Transcranial Ultrasound Stimulation Experiments
Published on: June 28, 2024
Design and validation of an MR-conditional robot for transcranial focused ultrasound surgery in infants
Karl D Price1, Vivian W Sin2, Charles Mougenot3
1Centre for Image Guided Innovation and Therapeutic Intervention, The Hospital for Sick Children, Toronto, Ontario M5G 1X8, Canada and The Department of Mechanical Engineering, The University of Toronto, Toronto, Ontario M5S 3G8, Canada.
Purpose:
Current treatment of intraventricular hemorrhage (IVH) involves cerebral shunt placement or an invasive brain surgery. Magnetic resonance-guided focused ultrasound (MRgFUS) applied to the brains of pediatric patients presents an opportunity to treat IVH in a noninvasive manner, termed "incision-less surgery." Current clinical and research focused ultrasound systems lack the capability to perform neonatal transcranial surgeries due to either range of motion or dexterity requirements. A novel robotic system is proposed to position a focused ultrasound transducer accurately above the head of a neonatal patient inside an MRI machine to deliver the therapy.
Methods:
A clinical Philips Sonalleve MRgFUS system was expanded to perform transcranial treatment. A five degree-of-freedom MR-conditional robot was designed and manufactured using MR compatible materials. The robot electronics and control were integrated into existing Philips electronics and software interfaces. The user commands the position of the robot with a graphical user interface, and is presented with real-time MR imaging of the patient throughout the surgery. The robot is validated through a series of experiments that characterize accuracy, signal-to-noise ratio degeneration of an MR image as a result of the robot, MR imaging artifacts generated by the robot, and the robot's ability to operate in a representative surgical environment inside an MR machine.
Results:
Experimental results show the robot responds reliably within an MR environment, has achieved 0.59 ± 0.25 mm accuracy, does not produce severe MR-imaging artifacts, has a workspace providing sufficient coverage of a neonatal brain, and can manipulate a 5 kg payload. A full system demonstration shows these characteristics apply in an application environment.
Conclusions:
This paper presents a comprehensive look at the process of designing and validating a new robot from concept to implementation for use in an MR environment. An MR conditional robot has been designed and manufactured to design specifications. The system has demonstrated its feasibility as a platform for MRgFUS interventions for neonatal patients. The success of the system in experimental trials suggests that it is ready to be used for validation of the transcranial intervention in animal studies.
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