Brain abnormalities in myalgic encephalomyelitis/chronic fatigue syndrome: Evaluation by diffusional kurtosis imaging and neurite orientation dispersion and density imaging

Background

Diffusional kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) metrics provide more specific information regarding pathological changes than diffusion tensor imaging (DTI).

Purpose

To detect microstructural abnormalities in myalgic encephalomyelitis (ME) / chronic fatigue syndrome (CFS) patients by using DKI and NODDI metrics.

Study Type

Prospective.

Population

Twenty ME/CFS patients and 23 healthy controls were recruited.

Field Strength/Sequence

Three‐b value DWI (b‐values = 0, 1000, and 2000 sec/mm²) and 3D T₁‐weighted images were at 3.0T.

Assessment

Mean kurtosis (MK), neurite density index (NDI), orientation dispersion index (ODI), fractional anisotropy (FA), and mean diffusivity (MD) were calculated.

Statistical Testing

The two‐sample t‐test analysis in SPM12 software was used to compare the differences between ME/CFS and control groups.

Results

In the ME/CFS patients, we observed significant FA decreases in the genu of the corpus callosum and the anterior limb of the right internal capsule (P < 0.05), but no significant difference in MD (P = 0.164); there were also significant MK decreases in the right frontal area, anterior cingulate gyrus, superior longitudinal fasciculus (SLF), and left parietal area (P < 0.05). Significant NDI decreases were observed in the right posterior cingulate gyrus, SLF, and left frontal area of the ME/CFS patients (P < 0.05). Significant ODI decreases were seen in the bilateral occipital areas, right superior temporal gyrus, the anterior limb of internal capsule, and the posterior cingulate gyrus (P < 0.05), and significant ODI increases were revealed in the bilateral occipital and right temporal areas (P < 0.05).

Data Conclusion

Right SLF abnormalities may be a diagnostic marker for ME/CFS.

Level of Evidence: 1

Technical Efficacy: Stage 2

J. Magn. Reson. Imaging 2018.

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