Advanced MRI-based characterisation of multiple sclerosis
Multiple sclerosis (MS) is an autoimmune disease that affects the central nervous system of millions of individuals worldwide, causing motor, sensory, cognitive and emotional deficits. In MS, the immune system attacks myelin, the sheath that insulates the neurons and ensures signal transmission. Diagnosis involves the use of a range of magnetic resonance imaging methods which show different hallmarks of the disease, such as plaques in white matter. Researchers are also turning to functional magnetic resonance imaging (fMRI) to assess changes in brain function in MS and quantitative susceptibility mapping (QSM) to evaluate the iron distribution within white matter lesions as an indication of active disease.
New MRI methods
Identification of plaques and lesions alongside evaluation of clinical symptoms are the two parameters used to categorise patients into the different disease phenotypes(opens in new window): clinically isolated syndrome (CIS), relapsing-remitting MS (RRMS), primary-progressive MS (PPMS) and secondary progressive MS (SPMS). The key objective of the MS-fMRI-QSM project was to develop a method which provides simultaneous information about functional and structural changes in MS which occur at an early stage, bringing with it the prospect of being able to identify which patients are transitioning from a relapsing-remitting to a progressive stage. The research was undertaken with the support of the Marie Skłodowska-Curie Actions(opens in new window) (MSCA) programme and involved the development of an MRI method which allows both functional and structural data to be acquired in a single measurement. “In MS research, QSM and fMRI scans are acquired separately, but this is either not always feasible or either one might be corrupted by motion,” explains the MSCA research fellow Simon Robinson. Researchers came up with a new method where they could extract high resolution QSM data from fMRI scans, but although the combination of QSM and fMRI proved quicker, it was prone to technical artefacts caused by imaging distortion. The MS-fMRI-QSM approach(opens in new window) allowed the correction of distortions in functional imaging and the disruptive effects caused by respiratory and cardiac action.
Insight into disease mechanisms
The next steps for the scientific team are to assess the quality of the QSMs generated using this method and link changes in iron distribution and function with clinical symptoms. Integrating iron accumulation data with demyelination and disruption of functional networks in the different disease phenotypes will help identify characteristic hallmarks. Moreover, it will lay the groundwork for understanding the mechanisms underlying disease progression from RRMS without disability to RRMS with disability. “By speeding up the data acquisition and generating co-localised measures of changes in structure and function, we hope to identify MS imaging biomarkers,” emphasises Robinson.
Advantages and clinical prospects
One of the key advantages of the MS-fMRI-QSM method is the unprecedented resolution it offers compared to prior fMRI studies of MS. In addition, repeat scans provide an improved understanding of treatment response, so clinicians can monitor disease progression and change medication, if necessary. The ultimate goal is to allow MS to be diagnosed at an earlier stage, so that patients can begin treatment before damage accumulates. The hope is that fMRI-QSM imaging will contribute to improving the health and life expectancy of patients and reducing the burden on carers and healthcare services. Furthermore, it can be extended to the acquisition of QSM data in a range of other pathologies.
