Diffusion MRI can primarily differentiate progressive from relapsing-remitting MS

Gray matter morphometric and microstructural changes identified by diffusion magnetic resonance imaging (dMRI) may help differentiate 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 that primarily affects the white matter. However, imaging studies have shown that gray matter can also be implicated in RRMS and PPMS, the most common forms of multiple sclerosis.

The aim of the current study was to determine the morphometric and microstructural differences in gray matter between patients with RRMS and patients with PPMS. The study researchers used a three-dimensional simple reconstruction based on a harmonic oscillator, estimation of 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 3T MRI anatomical scan that was close to the last neurological examination was recorded.

The study researchers used 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 reconstruction and estimation models based on a simple harmonic oscillator. Additional analysis relied on a linear support vector machine classifier to identify the features that best differentiate between RRMS and PPMS.

Compared to patients with RRMS, patients with PPMS were significantly older, had a longer duration of illness and a poorer physical disability status.

The data suggested that all dMRI-derived indices showed significant microstructural changes between patients with PPMS and RRMS, particularly in the restriction indices (return to axis likelihood, return to origin likelihood, and return to level likelihood), which were significantly different reported mode and median values. The hippocampus was a key region that exhibited group microstructure variations in both median and mode.

The thalamic volume was the only morphometric feature that differed significantly between the groups, as patients with PPMS had significantly lower volume values ​​than patients with RRMS.

The support vector machine analysis identified 12 features that differentiated between RRMS and PPMS. The analysis provided additional evidence of the importance of the hippocampal region, as 10 of the features corresponded to that 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, the lack of a healthy control group, the cross-sectional design, and the inclusion of only 2 analytical models to assess gray matter damage.

“Our study provides evidence of the higher sensitivity of dMRI in differentiating PPMS from RRMS based on regional GM [gray matter] Microstructural properties compared to morphometric measurements. Notably, the hippocampus was the most sensitive GV region to group differences, suggesting a central role this region plays in disease progression and warrants further investigation, ”the study researchers concluded.


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

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