Motion-Robust Pulse Design for Parallel Transmission Excitation at Ultra-High Field MRI

Patient-motion tolerant functional Magnetic Resonance Imaging at the Ultra-high Field
Background
Functional magnetic resonance imaging (fMRI), the most commonly used technique to map neuronal activity, makes it possible to evaluate how healthy versus diseased/injured brains function and determine which regions of the brain handle tasks like moving or speaking. Because fMRI acquisitions consist of repetitive scanning of the same volume to conduct statistical analysis on the temporal variation of the signal in every part of the brain, patient motion makes data inconsistent over time and deteriorates the analysis. Motion is specifically problematic with uncooperative patients such as patients with Parkinson's or dementia.
The state-of-the-art ultra-high field (UHF) scanners provide a unique opportunity to study neuronal activity with increased accuracy of the functional mapping signals for fMRI. Unfortunately, correcting the artificial contrast variations intrinsic to UHF MRI require specifically designed imaging protocols (parallel-transmit RF pulses). With current techniques, these pulses are designed for a stationary patient, leading to inconsistent data when the patient moves
Project aims and methods
In this study, you will develop techniques to design pulses that will 'freeze' motion; ie, acquire consistent data while the patient can freely move during a functional MRI scan. These motion-tolerant parallel-transmit pulses will be designed only once before a scan to accommodate a user-specified range of 'expected' or 'maximum' patient motion, and will require only simple adjustments rather than a computationally expensive redesign during the scan.
The effect of motion on fMRI analysis will be documented, and the performance of these pulses will be evaluated via in-vivo experiments. The outcomes will guide the development of novel fMRI imaging protocols and make it more feasible to conduct UHF functional MRI on patients with dementia and Parkinson's.
This interdisciplinary project lies at the boundary of engineering, physics and psychology, and you will benefit from working with faculty members from the schools of Physics and Psychology.
Research training
The project lies at the interface of multiple disciplines and benefits from a team of supervisors from Physics and Psychology. You will develop specific and transferrable skills across multi-disciplinary domains, including:
robust knowledge on MRI and fMRI physics
signal processing
conducting research with patients
fMRI data acquisition and analysis
MRI scanner (7T), parallel-transmit and motion tracking hardware
computational modelling and electromagnetic simulations (Sim4Life)
programming fluency (e.g. Matlab, C++, Python)
experiment design (PsychoPy)
MRI sequence development (Siemens IDEA).
You will also be supported to attend from over 350 workshops offered through the Doctoral Academy to further develop research and professional skills, and the schools of Psychology and Physics have active portfolios of training for PhD students that include teaching opportunities, seminars and networking events. The multi-disciplinary nature of the project and acquired skills will launch the student on a successful research career.
CUBRIC has strong collaborative ties with Siemens Healthcare and benefits from the full-time presence of an on-site Siemens engineer, which will expose the student to academia-industry collaborations.