Using structural and functional MRI as a neuroimaging technique to investigate chronic fatigue syndrome/myalgic...

This systematic review aims to synthesise and evaluate structural MRI (sMRI) and functional MRI (fMRI) studies in chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME).

We systematically searched Medline and Ovid and included articles from 1991 (date of Oxford diagnostic criteria for CFS/ME) to first April 2019. Studies were selected by predefined inclusion and exclusion criteria. Two reviewers independently reviewed the titles and abstracts to determine articles for inclusion, full text and quality assessment for risk of bias.

sMRI studies report differences in CFS/ME brain anatomy in grey and white matter volume, ventricular enlargement and hyperintensities. Three studies report no neuroanatomical differences between CFS/ME and healthy controls. Task-based fMRI investigated working memory, attention, reward and motivation, sensory information processing and emotional conflict. The most consistent finding was CFS/ME exhibited increased activations and recruited additional brain regions. Tasks with increasing load or complexity produced decreased activation in task-specific brain regions.

There were insufficient data to define a unique neural profile or biomarker of CFS/ME. This may be due to inconsistencies in finding neuroanatomical differences in CFS/ME and the variety of different tasks employed by fMRI studies. But there are also limitations with neuroimaging. All brain region specific volumetric differences in CFS/ME were derived from voxel-based statistics that are biased towards group differences that are highly localised in space. fMRI studies demonstrated both increases and decreases in activation patterns in CFS/ME, this may be related to task demand. However, fMRI signal cannot differentiate between neural excitation and inhibition or function-specific neural processing. Many studies have small sample sizes and did not control for the heterogeneity of this clinical population. We suggest that with robust study design, subgrouping and larger sample sizes, future neuroimaging studies could potentially lead to a breakthrough in our understanding of the disease.