Morphometric and microstructural gray matter alterations identified by diffusion magnetic resonance imaging (dMRI) may help discriminate between relapsing remitting multiple sclerosis (RRMS) and primary progressive multiple sclerosis (PPMS), according to study results published in the Journal of Magnetic Resonance Imaging.

Multiple sclerosis is a chronic inflammatory-demyelinating disease of the central nervous system, which mainly affect the white matter. However, imaging studies have suggested that gray matter may also be involved in both RRMS and PPMS, the most common forms of multiple sclerosis. 

The objective of the current study was to determine the morphometric and microstructural gray matter differences between patients with RRMS and those with PPMS. Study researchers used 3-dimensional simple harmonic oscillator-based reconstruction, estimation microstructural indices, diffusion tensor imaging, and conventional brain morphometry. 


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The study included 45 patients (women, 26; mean age, 47.4 years) with PPMS and 45 patients (women, 32 women; mean age, 42.8 years) with RRMS with an available standard anatomical 3T MRI scan acquired near the most recent neurological examination. 

Study researchers utilized three dimensional fast field echo T1-weighted MRI data to provide information about morphometric features. For dMRI data, they used diffusion tensor imaging and 3D simple harmonic oscillator based reconstruction and estimation models. Additional analysis relied on a linear support vector machine classifier in an attempt to identify the features that best discriminate between RRMS and PPMS. 

Compared to patients with RRMS, patients with PPMS were significantly older, had longer disease duration, and worse physical disability status. 

The data suggested that all the dMRI-derived indices showed significant microstructural alterations between patients with PPMS and RRMS, especially for the restriction indices (return to the axis probability, return to the origin probability, and return to the plane probability) which reported significantly different mode and median values. The hippocampus was a key region showing group microstructure variations in both median and mode.

Thalamic volume was the only morphometric feature significantly different between the groups, as patients with PPMS had significantly lower volume values than patients with RRMS.

Support vector machine analysis identified 12 features that discriminated between RRMS and PPMS. The analysis provided additional evidence of the importance of the hippocampus region, as 10 of the features corresponded to this region, while 2 were related to the thalamus. The accuracy of the support vector machine analysis in classifying RRMS and PPMS was 68.3%.

The study had several limitations, including the small sample size, lack of a healthy control group, cross-sectional design, and the inclusion of only 2 analytical models to assess gray matter damage

“Our study provides evidence for the higher sensitivity of dMRI in differentiating PPMS from RRMS based on regional GM [gray matter] microstructure properties compared to morphometry measures. Noteworthy, the GM region most sensitive to group differences was the hippocampus, suggesting a central role of this region in disease progression and calling for further investigation,” concluded the study researchers. 

Reference

Boscolo IG, Brusini L, Akinci M, et al. Unraveling the MRI-based microstructural signatures behind primary progressive and relapsing-remitting multiple sclerosis phenotypes. J Magn Reson Imaging. Published online June 30, 2021. doi:10.1002/jmri.27806