Diffusion MRI as a new biomarker in Duchenne Muscular Dystrophy

Background:
Diffusion MRI (1) is an imaging modality that is sensitive to the bulk motion of water in biological tissue during the acquisition of the MRI pulse sequence. As water molecules diffuse, they interact with their environment. Biological structures affect their motion, and hence the measured signal decay curve. The typical duration of an MRI pulse sequence is on the order of milliseconds, the typical distance diffused by water molecules in vivo is on the order of microns. This is similar to the size of living cells, and orders of magnitude smaller than the highest accessible spatial resolution of typical MRI scans, which has led to considerable interest in the application of these methods in biomedical applications.  Outside the brain, however, application of diffusion MRI has been less extensive.

However, recent advances in clinical scanner hardware, such as high- and ultra-high field, improvements in RF coil technology, and more powerful gradients with higher slew-rates have made advanced diffusion imaging outside the brain more feasible. New environments, however, bring new challenges. Muscle fibres, for example, range in size from tens to hundreds of microns necessitating much longer diffusion times to probe them, accessible mainly via STEAM sequences. Muscle structure also presents a challenge in analysis: it has a hierarchical structure which is not compatible with explicit geometric modelling.

Duchenne Muscular Dystrophy (DMD) is a genetic muscle-wasting disease affecting approximately 1 in 3600 boys in the UK. The pathology is known to change tissue microstructure and leads eventually to the fibrous tissue being lost and replaced by fat. By providing sensitivity to the microstructural environment, diffusion MRI is uniquely placed to deliver novel, non-invasive information on disease progression.

Aims/Objectives:
This project will explore the use of cutting-edge diffusion MRI-based imaging for assessment of DMD patients including image acquisition, post-processing, and image analysis. 

The project aims to use novel contrast metrics from advanced diffusion MRI to provide new vectors of clinical information on DMD patients, and explore the combination of MRI data with other non-invasive disease assessments such as clinical testing, histological data and gait analysis.

Methods:
Advanced diffusion MRI sequences. Sequences will be optimised using phantoms simulating muscle tissue. In addition the student will have the opportunity to build on modelling work using Monte-Carlo simulations and finite element analyses to investigate different biophysical patterns of muscle tissue degeneration as occurs in DMD (2). Reproducibility of optimised sequences will assessed in healthy volunteers (3) and then the finalised sequences will be deployed in a patient study in which diffusion MRI data will be collected alongside conventional T2-weighted and Dixon water fat fraction imaging. Careful comparison between these modalities will be undertaken.

Timeline:
Year 1: Testing of candidate diffusion MRI sequences using muscle simulating phantoms. Examination of different diffusion model fitting routines. Modelling of diffusion in muscle tissue by simulation. Examine various muscle degeneration scenarios.
Year 2: Collection of data in healthy volunteers. Assessment of reproducibility. Start of data collection in DMD patients. Begin careful comparison of diffusion MRI with existing MRI techniques and where available gait analysis and histology.
Year 3: Completion of patient study and completion of data analyses. Writing up of thesis.

References:
1.            Le Bihan, D., Mangin, J.F., Poupon, C., Clark, C.A., Pappata, S., Molko, N., Chabriat, H. (2001). Diffusion tensor imaging: concepts and applications. Journal of Magnetic Resonance Imaging 13, 534-546.
2.            Hall, M.G., Clark, C.A. (2017). Diffusion in hierarchical systems: a simulation study in models of healthy and diseased muscle tissue. Magnetic Resonance in Medicine 78(3):1187-1198.
3.            Grech-Sollars, M., Hales, P.W., Miyazaki, K., Raschke, F., Rodriguez, D., Wilson, M., Gill, S.K., Banks, T., Saunders, D.E., Clayden, J.D., Gwilliam, M.N., Barrick, T.R., Morgan, P.S., Davies, N.P., Rossiter, J., Auer, D.P., Grundy, R., Leach, M.O., Howe, F.A., Peet, A.C.*, Clark, C.A.* (2015). Multi centre reproducibility of diffusion MRI parameters for clinical sequences in the brain. NMR in Biomedicine 28(4): 468-85.