Structural MRI can robustly assess brain tissue alterations related to neurological diseases and ageing. Traditional morphological MRI metrics, such as cortical volume and thickness, only partially relate to functional impairment and disease trajectories at the individual level. Emerging research has increasingly focused on reconstructing interregional meso- and macro-structural relationships in the brain by analysing covarying morphometric patterns. These patterns suggest that structural variations in specific brain regions tend to covary with deviations in other regions across individuals, a phenomenon termed structural covariance. This concept reflects the idea that physiological and pathological processes follow an anatomically defined spreading pattern. Advanced computational strategies, particularly those within the graph-theoretical framework, yield quantifiable properties at both the whole-brain and regional levels, which correlate more closely with the clinical state or cognitive performance than classical atrophy patterns. This review highlights cutting-edge methods for evaluating morphometric covariance networks on an individual basis, with a focus on their utility in characterizing ageing, central nervous system inflammation and neurodegeneration. Specifically, these methods hold significant potential for quantifying structural alterations in patients with Alzheimer’s disease, Parkinson’s disease, frontotemporal dementia and multiple sclerosis. By capturing the distinctive morphometric organization of each individual’s brain, structural covariance network analyses allow the tracking and prediction of pathology progression and clinical outcomes, information that can be integrated into clinical decision-making and used as variables in clinical trials. Furthermore, by investigating distinct and cross-diagnostic patterns of structural covariance, these approaches offer insights into shared mechanistic processes critical to understanding severe neurological disorders and their therapeutic implications. Such advancements pave the way for more precise diagnostic tools and targeted therapeutic strategies.

Invasive procedures may delay the diagnostic process in multiple sclerosis (MS). We investigated the added value of serum neurofilament light chain (sNfL), glial fibrillary acidic protein (sGFAP), chitinase-3-like 1 (sCHI3L1), and the immune responses to the Epstein-Barr virus-encoded nuclear antigen 1 to current MS diagnostic criteria. In this multicentric study, we selected patients from 2 prospective cohorts presenting a clinically isolated syndrome (CIS). Patients were classified as (1) not presenting dissemination in space (DIS) nor dissemination in time (DIT) (noDIS and noDIT); (2) presenting DIS without DIT (DIS and noDIT); and (3) presenting both (DIS and DIT), which were used as a reference. sNfL, sGFAP, and sCHI3L1 levels were measured with single-molecule array immunoassays and EBNA1-specific IgG levels with ELISA. Biomarker levels were compared between groups using linear regression models. Receiver operating characteristic curve analyses and Youden Index were used to determine cutoff values associated with MS diagnosis during follow-up. We included 181 patients (66.3% females, mean [SD] age of 35.0 [9.7] years). At baseline, 25 (13.8%) were classified as noDIS and noDIT, 62 (34.3%) as DIS and noDIT, and 94 (51.9%) as DIS and DIT. Only sNfL Z-scores discriminated between groups (DIS and DIT vs DIS and noDIT [p = 0.002], DIS and DIT vs noDIS and noDIT [p < 0.001], and DIS and noDIT vs noDIS and noDIT [p = 0.026]). In noDIS and noDIT patients (median interquartile range [IQR] follow-up of 8.1 [5.0-11.7] years), high sNfL Z-scores best predicted MS diagnosis (specificity [SP] and 95% CI of 93.3% [68.1-99.8] and positive predictive value [PPV] of 87.5% [47.3-99.7]). Among DIS and noDIT patients (median [IQR] follow-up of 6.8 [4.0-9.1] years), high sNfL Z-scores best predicted MS diagnosis (SP of 80% [28.4-99.5] and PPV of 97.3% [85.8-99.9]) without considering oligoclonal band (OB) status. In the subset of patients of this group with negative OBs, a combination of high sNfL Z-scores and sGFAP levels predicted MS diagnosis (SP of 100% [39.8-100] and PPV of 100% [54.1-100]). These results suggest that sNfL and sGFAP may be incorporated in particular scenarios to diagnose MS in patients with CIS not fulfilling current diagnostic criteria.

Emerging concepts in the early detection of multiple sclerosis (MS) progression reveal that disability accumulation can start early in the disease course. Aging in MS is increasingly recognized as a key factor for disease progression and disability accrual. We evaluate the prognostic impact of age in a cohort of patients experiencing a first demyelinating event (FDE), using a variety of disability outcomes, including some not previously assessed in age-specific studies. Patients aged 18-50 years, assessed within 3 months from the FDE, were prospectively included since 1994 and categorized into 3 age groups: 18-29, 30-39, and 40-50 years. Relapse-associated worsening (RAW) at FDE, annualized relapse rate, and EDSS trajectories during follow-up were compared across age groups. Cox regression analyses adjusted for sex, comorbidities, and time exposed to very high-efficacy drugs were performed to assess the risk of achieving the following outcomes: time to reach McDonald 2017 criteria, first relapse, recurrent RAW, >2 new T2 brain lesions/year, first progression independent of relapse activity (PIRA), confirmed disability accumulation (CDA), and confirmed EDSS score 3.0. Patient-reported outcome measures were also analyzed. A total of 1,170 patients were included (median age 32 years; 69% female). The 40-50 group had a higher proportion of RAW at FDE (34% vs 25% and 29%; p = 0.031) and less time exposed to very high-efficacy treatments (p < 0.001) than the 30-39 and 18-29 groups, respectively. EDSS trajectories in the 40-50 group displayed a greater annual increase in the EDSS score compared with the 18-29 group (β 0.019 [95% CI 0.0001; 0.0387]). Cox analyses (HR; 95% CI) showed that the 40-50 group was at lower risk to reach McDonald 2017 criteria (0.80; 0.67-0.96), first relapse (0.59; 0.47-0.74), recurrent RAW (0.51; 0.31-0.86), or >2 new T2 brain lesions/year (0.39; 0.30-0.52), but at a higher risk of CDA (1.49; 1.16-1.97), PIRA (2.48; 1.88-3.27), and EDSS score 3.0 (1.50; 1.05-2.12), than the 18-29 group. Different functional and well-being variables were more affected in the 40-50 group, compared with 30-39 and 18-29 groups (p values< 0.05). Patients with a FDE at 40-50 years exhibit less inflammatory outcomes compared with younger patients and reach outcomes more closely related to neurodegeneration despite the lower disease activity.

In multiple sclerosis (MS), brain reserve serves as a protective factor against cognitive impairment. Previous research has suggested a structural counterpart in the spine-spinal cord reserve-seemed to be associated with physical disability. This study aimed to investigate the potential of the cervical canal area (CCaA) as a proxy for spinal cord reserve in a multicentric cohort of people with MS (PwMS). This retrospective, multicentric, longitudinal study included PwMS and healthy controls (HCs) from 9 European MAGNIMS sites. Baseline cervical 3D T1-weighted images were acquired, excluding poor-quality images. CCaA was estimated independently at the C2/C3 and C3/C4 levels. The Expanded Disability Status Scale (EDSS) score was assessed at baseline and 5-year follow-up. We analyzed mean CCaA differences between groups and the association of CCaA with baseline EDSS scores and disability progression using multivariable regression models adjusted for age, sex, spinal cord parenchymal fraction, and cervical cord lesions. After quality check, the cohort included 177 HCs (mean age 39.8 years, 57.6% women) and 428 PwMS (mean age 46.5 years, 60.8% women), comprising 289 people with relapsing MS (PwRMS) and 139 people with progressive MS (PwPMS). No significant differences in CCaA were found between HCs and PwRMS at C2/C3 or C3/C4 levels. Conversely, PwPMS showed a smaller CCaA at the C2/C3 level (210.51 mm²) than HCs (214.62 mm², estimated mean difference [EMD] -4.11, 95% CI -6.28 to -1.00, p = 0.007) and PwRMS (213.68 mm², EMD -3.17, 95% CI -5.22 to -0.34, p = 0.026). PwPMS also had a smaller CCaA at C3/C4 (165.16 mm²) than HCs (169.67 mm², EMD -4.51, 95% CI -5.50 to -1.60, p < 0.001) and PwRMS (169.44 mm², EMD -3.81, 95% CI -5.22 to -0.34, p < 0.001). At the C3/C4 level, CCaA and baseline EDSS scores were significantly associated (β = -0.13, p < 0.001); in addition, PwMS with clinical worsening at 5-year follow-up displayed a smaller baseline CCaA (worsened vs stable: 167.03 mm² vs 169.13 mm², EMD -2.10, 95% CI -3.98 to -023, p = 0.028). CCaA was associated with baseline EDSS scores and clinical worsening in a multicentric MS cohort, suggesting the existence of spinal cord reserve. PwPMS had a smaller CCaA, indicating that reduced spinal cord reserve might be characteristic of progressive MS. Therefore, spinal cord reserve may represent a novel radiologic marker for better understanding physical disability in MS.

BACKGROUND AND PURPOSE: As in the brain reserve concept, a larger cervical canal area may also protect against disability. In this context, a semiautomated pipeline has been developed to obtain quantitative estimations of the cervical canal area. The aim of the study was to validate the pipeline, to evaluate the consistency of the cervical canal area measurements during a 1-year period, and to compare cervical canal area estimations obtained from brain and cervical MRI acquisitions. MATERIALS AND METHODS: Eight healthy controls and 18 patients with MS underwent baseline and follow-up 3T brain and cervical spine sagittal 3D MPRAGE. The cervical canal area was measured in all acquisitions, and estimations obtained with the proposed pipeline were compared with manual segmentations performed by 1 evaluator using the Dice similarity coefficient. The cervical canal area estimations obtained on baseline and follow-up T1WI were compared; brain and cervical cord acquisitions were also compared using the individual and average intraclass correlation coefficients. RESULTS: The agreement between the manual cervical canal area masks and the masks provided by the proposed pipeline was excellent, with a mean Dice similarity coefficient mean of 0.90 (range, 0.73–0.97). The cervical canal area estimations obtained from baseline and follow-up scans showed a good level of concordance (intraclass correlation coefficient = 0.76; 95% CI, 0.44–0.88); estimations obtained from brain and cervical MRIs also had good agreement (intraclass correlation coefficient = 0.77; 95% CI, 0.45–0.90). CONCLUSIONS: The proposed pipeline is a reliable tool to estimate the cervical canal area. The cervical canal area is a stable measure across time; moreover, when cervical sequences are not available, the cervical canal area could be estimated using brain T1WI.