Enlarged perivascular spaces are associated with brain microangiopathy and aging in multiple sclerosis.

BACKGROUND: Growing evidence links brain-MRI enlarged perivascular spaces (EPVS) and multiple sclerosis (MS), but their role remains unclear. OBJECTIVE: This study aimed to investigate the cross-sectional associations of EPVS with several neuroinflammatory and neurodegenerative features in a large multicentric-MS cohort. METHODS: In total, 207 patients underwent 3T axial-T2-weighted brain-MRI for EPVS assessment (EPVS dichotomized into high/low according to ⩾ 2/< 2 rating categories). MRI biomarkers included brain-predicted age and brain-predicted age difference (brain-PAD), central vein sign (CVS)-positive lesion percentage (CVS%), paramagnetic rim and cortical lesions, T2-lesion load, and brain volumetry. The variable relative importance for EPVS-category prediction was explored using a classification random forest approach. RESULTS: High EPVS patients were older (49 vs 44 years, p = 0.003), had ⩾ 1 vascular risk factors (VRFs; p = 0.005), lower CVS% (67% vs 78%, p < 0.001), reduced brain volumes (whole brain: 0.63 vs 0.73, p = 0.01; gray matter: 0.36 vs 0.40; p = 0.002), and older brain-predicted age (58 vs 50 years, p < 0.001). No differences were found for neuroinflammatory markers. After adjusting for age and VFRs (multivariate analyses), the high EPVS category correlated with lower CVS% (odds ratio (OR) = 0.98, 95% confidence interval (CI) = 0.96-0.99; p = 0.02), lower whole brain (OR = 0.01, 95% CI = 0.0003-0.5; p = 0.02), gray matter (OR = 0.0004, 95% CI = 0.0000004-0.4; p = 0.03) volumes, and higher brain-PAD (OR = 1.05, 95% CI = 1.01-1.09; p = 0.02). Random forest identified brain-PAD as the most important predictor of high EPVS. CONCLUSION: EPVS in MS likely reflect microangiopathic disease rather than neuroinflammation, potentially contributing to accelerated neurodegeneration.

Comparative overview of multi-shell diffusion MRI models to characterize the microstructure of multiple sclerosis lesions and periplaques.

In multiple sclerosis (MS), accurate in vivo characterization of the heterogeneous lesional and extra-lesional tissue pathology remains challenging. Marshalling several advanced imaging techniques - quantitative relaxation time (T1) mapping, a model-free average diffusion signal approach and four multi-shell diffusion models - this study investigates the performance of multi-shell diffusion models and characterizes the microstructural damage within (i) different MS lesion types - active, chronic active, and chronic inactive - (ii) their respective periplaque white matter (WM), and (iii) the surrounding normal-appearing white matter (NAWM). In 83 MS participants (56 relapsing-remitting, 27 progressive) and 23 age and sex-matched healthy controls (HC), we analysed a total of 317 paramagnetic rim lesions (PRL+), 232 non-paramagnetic rim lesions (PRL-), 38 contrast-enhancing lesions (CEL). Consistent with previous findings and histology, our analysis revealed the ability of advanced multi-shell diffusion models to characterize the unique microstructural patterns of CEL, and to elucidate their possible evolution into a resolving (chronic inactive) vs smoldering (chronic active) inflammatory stage. In addition, we showed that the microstructural damage extends well beyond the MRI-visible lesion edge, gradually fading out while moving outward from the lesion edge into the immediate WM periplaque and the NAWM, the latter still characterized by diffuse microstructural damage in MS vs HC. This study also emphasizes the critical role of selecting appropriate diffusion models to elucidate the complex pathological architecture of MS lesions and their periplaque. More specifically, multi-compartment diffusion models based on biophysically interpretable metrics such as neurite orientation dispersion and density (NODDI; mean auc=0.8002) emerge as the preferred choice for MS applications, while simpler models based on a representation of the diffusion signal, like diffusion tensor imaging (DTI; mean auc=0.6942), consistently underperformed, also when compared to T1 mapping (mean auc=0.73375).

Central Vein Sign, Cortical Lesions, and Paramagnetic Rim Lesions for the Diagnostic and Prognostic Workup of Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: The diagnosis of multiple sclerosis (MS) can be challenging in clinical practice because MS presentation can be atypical and mimicked by other diseases. We evaluated the diagnostic performance, alone or in combination, of the central vein sign (CVS), paramagnetic rim lesion (PRL), and cortical lesion (CL), as well as their association with clinical outcomes. METHODS: In this multicenter observational study, we first conducted a cross-sectional analysis of the CVS (proportion of CVS-positive lesions or simplified determination of CVS in 3/6 lesions-Select3*/Select6*), PRL, and CL in MS and non-MS cases on 3T-MRI brain images, including 3D T2-FLAIR, T2*-echo-planar imaging magnitude and phase, double inversion recovery, and magnetization prepared rapid gradient echo image sequences. Then, we longitudinally analyzed the progression independent of relapse and MRI activity (PIRA) in MS cases over the 2 years after study entry. Receiver operating characteristic curves were used to test diagnostic performance and regression models to predict diagnosis and clinical outcomes. RESULTS: The presence of ≥41% CVS-positive lesions/≥1 CL/≥1 PRL (optimal cutoffs) had 96%/90%/93% specificity, 97%/84%/60% sensitivity, and 0.99/0.90/0.77 area under the curve (AUC), respectively, to distinguish MS (n = 185) from non-MS (n = 100) cases. The Select3*/Select6* algorithms showed 93%/95% specificity, 97%/89% sensitivity, and 0.95/0.92 AUC. The combination of CVS, CL, and PRL improved the diagnostic performance, especially when Select3*/Select6* were used (93%/94% specificity, 98%/96% sensitivity, 0.99/0.98 AUC; p = 0.002/p < 0.001). In MS cases (n = 185), both CL and PRL were associated with higher MS disability and severity. Longitudinal analysis (n = 61) showed that MS cases with >4 PRL at baseline were more likely to experience PIRA at 2-year follow-up (odds ratio 17.0, 95% confidence interval: 2.1-138.5; p = 0.008), whereas no association was observed between other baseline MRI measures and PIRA, including the number of CL. DISCUSSION: The combination of CVS, CL, and PRL can improve MS differential diagnosis. CL and PRL also correlated with clinical measures of poor prognosis, with PRL being a predictor of disability accrual independent of clinical/MRI activity.

BMAT: An open-source BIDS managing and analysis tool.

Magnetic Resonance Imaging (MRI) is an established technique to study in vivo neurological disorders such as Multiple Sclerosis (MS). To avoid errors on MRI data organization and automated processing, a standard called Brain Imaging Data Structure (BIDS) has been recently proposed. The BIDS standard eases data sharing and processing within or between centers by providing guidelines for their description and organization. However, the transformation from the complex unstructured non-open file data formats coming directly from the MRI scanner to a correct BIDS structure can be cumbersome and time consuming. This hinders a wider adoption of the BIDS format across different study centers. To solve this problem and ease the day-to-day use of BIDS for the neuroimaging scientific community, we present the BIDS Managing and Analysis Tool (BMAT). The BMAT software is a complete and easy-to-use local open-source neuroimaging analysis tool with a graphical user interface (GUI) that uses the BIDS format to organize and process brain MRI data for MS imaging research studies. BMAT provides the possibility to translate data from MRI scanners to the BIDS structure, create and manage BIDS datasets as well as develop and run automated processing pipelines, and is faster than its competitor. BMAT software propose the possibility to download useful analysis apps, especially applied to MS research with lesion segmentation and processing of imaging contrasts for novel disease biomarkers such as the central vein sign and the paramagnetic rim lesions.