Tract-wise microstructural analysis informs on current and future disability in early multiple sclerosis

Abstract

Objectives: Microstructural characterization of patients with multiple sclerosis (MS) has been shown to correlate better with disability compared to conventional radiological biomarkers. Quantitative MRI provides effective means to characterize microstructural brain tissue changes both in lesions and normal-appearing brain tissue. However, the impact of the location of microstructural alterations in terms of neuronal pathways has not been thoroughly explored so far. Here, we study the extent and the location of tissue changes probed using quantitative MRI along white matter (WM) tracts extracted from a connectivity atlas.

Methods: We quantified voxel-wise T1 tissue alterations compared to normative values in a cohort of 99 MS patients. For each WM tract, we extracted metrics reflecting tissue alterations both in lesions and normal-appearing WM and correlated these with cross-sectional disability and disability evolution after 2 years.

Results: In early MS patients, T1 alterations in normal-appearing WM correlated better with disability evolution compared to cross-sectional disability. Further, the presence of lesions in supratentorial tracts was more strongly associated with cross-sectional disability, while microstructural alterations in infratentorial pathways yielded higher correlations with disability evolution. In progressive patients, all major WM pathways contributed similarly to explaining disability, and correlations with disability evolution were generally poor.

Conclusions: We showed that microstructural changes evaluated in specific WM pathways contribute to explaining future disability in early MS, hence highlighting the potential of tract-wise analyses in monitoring disease progression. Further, the proposed technique allows to estimate WM tract-specific microstructural characteristics in clinically compatible acquisition times, without the need for advanced diffusion imaging.

Keywords: Demyelinating diseases; Magnetic resonance imaging; Multiple sclerosis; Relaxometry; White matter.

Fig. 1

Pipeline used to extract white matter, tract-specific T1 abnormalities shown here for six example white matter tracts. A White matter tract streamlines from a connectivity atlas [31]. B Normalized tract density images representing the percentage of streamlines passing through each voxel for each individual white matter tract, registered to SST space. C T1 normative voxel-wise atlas estimated from the healthy cohort and using sex and age as covariates. D Estimation of T1 deviations from the normative atlas in terms of z-scores for individual patients. E Estimation of tract-specific T1 z-scores in each patient. CST cortico-spinal tract; CT corticostriatal pathway; ML medial lemniscus; CC corpus callosum; ILF inferior longitudinal fasciculus; ICP inferior cerebellar peduncle; SST spinothalamic tract; RMSE root mean squared error; UNI uniform MP2RAGE image

Fig. 2

White matter tract-specific T1 z-scores shown in two example early MS patients. Despite similar total lesion load, the patient on the left, whose EDSS increased over 2 years, presented more severe alterations of the NAWM compared the patient on the right, who was clinically stable. CST cortico-spinal tract; CT corticostriatal pathway; ML medial lemniscus; CC corpus callosum; ILF inferior longitudinal fasciculus; ICP inferior cerebellar peduncle; SST spinothalamic tract; TLC total lesion count; TLV total lesion volume; EDSS expanded disability status scale

Fig. 3

Spearman correlations between white matter tract-specific metrics and EDSS in early (left half) and progressive MS (right half) cohorts. We estimated correlation of tract-specific lesion volume (LV, gray, first column) and T1 abnormalities in the NAWM (second column). We computed the average absolute z-score value in each tract (${\mu }_{|z|}$, teal). Correlations to EDSS₀ are shown in top rows and ΔEDSS in bottom rows. The inner circles represent the correlation of TLC (red) and TLV (gold). Red (/yellow) stars highlight tracts that yield to significantly higher (/lower) correlations to ΔEDSS compared to cross-sectional EDSS. Tract abbreviations are provided in the table. NAWM normal-appearing white matter; EDSS₀ expanded disability status scale, ΔEDSS change in EDSS after 2 years; TLC total lesion count; TLV total lesion volume; LV tract-specific lesion volume