Impact of 3 Tesla MRI on interobserver agreement in clinically isolated syndrome: A MAGNIMS multicentre study

Compared to 1.5 T, 3 T magnetic resonance imaging (MRI) increases signal-to-noise ratio leading to improved image quality. However, its clinical relevance in clinically isolated syndrome suggestive of multiple sclerosis remains uncertain

Opportunities for Understanding MS Mechanisms and Progression With MRI Using Large-Scale Data Sharing and Artificial Intelligence

Multiple sclerosis (MS) patients have heterogeneous clinical presentations, symptoms and progression over time, making MS difficult to assess and comprehend in vivo. The combination of large-scale data-sharing and artificial intelligence creates new opportunities for monitoring and understanding MS using magnetic resonance imaging (MRI).First, development of validated MS-specific image analysis methods can be boosted by verified reference, test and benchmark imaging data. Using detailed expert annotations, artificial intelligence algorithms can be trained on such MS-specific data. Second, understanding disease processes could be greatly advanced through shared data of large MS cohorts with clinical, demographic and treatment information. Relevant patterns in such data that may be imperceptible to a human observer could be detected through artificial intelligence techniques. This applies from image analysis (lesions, atrophy or functional network changes) to large multi-domain datasets (imaging, cognition, clinical disability, genetics, etc.).After reviewing data-sharing and artificial intelligence, this paper highlights three areas that offer strong opportunities for making advances in the next few years: crowdsourcing, personal data protection, and organized analysis challenges. Difficulties as well as specific recommendations to overcome them are discussed, in order to best leverage data sharing and artificial intelligence to improve image analysis, imaging and the understanding of MS

The ageing central nervous system in multiple sclerosis: the imaging perspective

The interaction between ageing and multiple sclerosis is complex and carries significant implications for patient care. Managing multiple sclerosis effectively requires an understanding of how ageing and multiple sclerosis impact brain structure and function. Ageing inherently induces brain changes, including reduced plasticity, diminished grey matter volume, and ischaemic lesion accumulation. When combined with multiple sclerosis pathology, these age-related alterations may worsen clinical disability. Ageing may also influence the response of multiple sclerosis patients to therapies and/or their side-effects, highlighting the importance of adjusted treatment considerations. Magnetic resonance MRI is highly sensitive to age- and multiple sclerosis-related processes. Accordingly, MRI can provide insights into the relationship between ageing and multiple sclerosis, enabling a better understanding of their pathophysiological interplay and informing treatment selection. This review summarizes current knowledge on the immuno-pathological and MRI aspects of ageing in the central nervous system in the context of multiple sclerosis. Starting from immunosenescence, ageing-related pathological mechanisms, and specific features like enlarged Virchow-Robin spaces, this review then explores clinical aspects, including late-onset multiple sclerosis, the influence of age on diagnostic criteria, and comorbidity effects on imaging features. The role of MRI in understanding neurodegeneration, iron dynamics, and myelin changes influenced by ageing and how MRI can contribute to defining treatment effects in ageing multiple sclerosis patients, are also discussed

Association of Gray Matter Atrophy Patterns with Clinical Phenotype and Progression in Multiple Sclerosis

OBJECTIVES: Grey matter (GM) involvement is clinically relevant in multiple sclerosis (MS). Using source-based morphometry (SBM), we characterized GM atrophy and its 1-year evolution across different MS phenotypes. METHODS: Clinical and MRI data were obtained at 8 European sites from 170 healthy controls (HCs) and 398 MS patients (34 clinically isolated syndromes [CIS], 226 relapsing-remitting [RR], 95 secondary progressive [SP] and 43 primary progressive [PP] MS). Fifty-seven HC and 144 MS underwent 1-year follow-up. Baseline GM loss, atrophy progression and correlations with disability and 1-year clinical worsening were assessed. RESULTS: SBM identified 26 cerebellar, subcortical, sensory, motor and cognitive GM components. GM atrophy was found in MS vs HC in almost all components (p=range<0.001-0.04). Compared to HCs, CIS patients showed circumscribed subcortical, cerebellar, temporal and salience GM atrophy, while RRMS patients exhibited widespread GM atrophy. Cerebellar, subcortical, sensorimotor, salience and fronto-parietal GM atrophy was found in PPMS patients vs HCs, and SPMS vs RRMS. At 1-year, 21 (15%) patients had clinically worsened. GM atrophy progressed in MS in subcortical, cerebellar, sensorimotor, and fronto-temporo-parietal components. Baseline higher disability was associated (R2=0.65) with baseline lower normalized brain volume (beta=-0.13, p=0.001), greater sensorimotor GM atrophy (beta=-0.12, p=0.002) and longer disease duration (beta=0.09, p=0.04). Baseline normalized GM volume (odds ratio=0.98, p=0.008) and cerebellar GM atrophy (odds ratio=0.40, p=0.01) independently predicted clinical worsening (area-under-the-curve=0.83). CONCLUSION: GM atrophy differed across disease phenotypes and progressed at 1-year in MS. In addition to global atrophy measures, sensorimotor and cerebellar GM atrophy explained baseline disability and clinical worsening

Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis

Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response

Longitudinal assessment of multiple sclerosis with the brain-age paradigm

OBJECTIVE: During the natural course of MS, the brain is exposed to ageing as well as disease effects. Brain ageing can be modelled statistically; the so-called 'brain-age' paradigm. Here, we evaluated whether brain-predicted age difference (brain-PAD) was sensitive to the presence of MS, clinical progression and future outcomes. METHODS: In a longitudinal, multi-centre sample of 3,565 MRI scans, in 1,204 MS and clinically-isolated syndrome (CIS) patients and 150 healthy controls (mean follow-up time: patients 3.41 years, healthy controls 1.97 years), we measured 'brain-predicted age' using T1-weighted MRI. We compared brain-PAD between MS and CIS patients and healthy controls, and between disease subtypes. Relationships between brain-PAD and Expanded Disability Status Scale (EDSS) were explored. RESULTS: MS patients had markedly higher brain-PAD than healthy controls (mean brain-PAD +10.3 years [95% CI 8.5, 12.1] versus 4.3 years [-2.1, 6.4], p < 0.001). The highest brain-PADs were in secondary-progressive MS (+19.4 years [17.1, 21.9]). Brain-PAD at study entry predicted time-to-disability progression (hazard ratio 1.02 [1.01, 1.03], p < 0.001); though normalised brain volume was a stronger predictor. Greater annualised brain-PAD increases were associated with greater annualised EDSS score (r = 0.26, p < 0.001). INTERPRETATION: The brain-age paradigm is sensitive to MS-related atrophy and clinical progression. A higher brain-PAD at baseline was associated with more rapid disability progression and the rate of change in brain-PAD related to worsening disability. Potentially, 'brain-age' could be used as a prognostic biomarker in early-stage MS, to track disease progression or stratify patients for clinical trial enrolment. This article is protected by copyright. All rights reserved

Association of Gray Matter Atrophy Patterns With Clinical Phenotype and Progression in Multiple Sclerosis

ObjectivesGay matter (GM) involvement is clinically relevant in multiple sclerosis (MS). Using source-based morphometry (SBM), we characterized GM atrophy and its 1-year evolution across different MS phenotypes.MethodsClinical and MRI data were obtained at 8 European sites from 170 healthy controls (HCs) and 398 patients with MS (34 with clinically isolated syndrome [CIS], 226 with relapsing-remitting MS [RRMS], 95 with secondary progressive MS [SPMS], and 43 with primary progressive MS [PPMS]). Fifty-seven HCs and 144 with MS underwent 1-year follow-up. Baseline GM loss, atrophy progression, and correlations with disability and 1-year clinical worsening were assessed.ResultsSBM identified 26 cerebellar, subcortical, sensory, motor, and cognitive GM components. GM atrophy was found in patients with MS vs HCs in almost all components (p range &lt;0.001-0.04). Compared toHCs, patients withCIS showed circumscribed subcortical, cerebellar, temporal, and salience GM atrophy, while patients with RRMS exhibited widespread GM atrophy. Cerebellar, subcortical, sensorimotor, salience, and frontoparietal GM atrophy was found in patients with PPMS vs HCs and in patients with SPMS vs those with RRMS. At 1 year, 21 (15%) patients had clinically worsened. GM atrophy progressed in MS in subcortical, cerebellar, sensorimotor, and fronto-temporo-parietal components. Baseline higher disability was associated (R-2 = 0.65) with baseline lower normalized brain volume (beta = -0.13, p = 0.001), greater sensorimotor GM atrophy (beta = -0.12, p = 0.002), and longer disease duration (beta = 0.09, p = 0.04). Baseline normalized GM volume (odds ratio 0.98, p = 0.008) and cerebellar GM atrophy (odds ratio 0.40, p = 0.01) independently predicted clinical worsening (area under the curve 0.83).ConclusionGM atrophy differed across disease phenotypes and progressed at 1 year in MS. In addition to global atrophy measures, sensorimotor and cerebellar GM atrophy explained baseline disability and clinical worsening

Towards a Unified Set of Diagnostic Criteria for Multiple Sclerosis

Objective: The 2017 McDonald criteria continued the separation of diagnostic criteria for relapsing–remitting multiple sclerosis (RRMS) and primary progressive MS (PPMS) for historical, rather than biological, reasons. We aimed to explore the feasibility of a single, unified set of diagnostic criteria when applied to patients with suspected PPMS. // Methods: We retrospectively identified patients evaluated for suspected PPMS at 5 European centers. The 2017 McDonald PPMS criteria was the gold standard against which the 2017 McDonald RRMS dissemination in space (DIS) and dissemination in time criteria were evaluated. We also investigated modified RRMS DIS criteria, including: (i) optic nerve lesions; (ii) ≥2 spinal cord lesions; and (iii) higher fulfilment of DIS criteria alone (lesions in ≥3 regions) without dissemination in time/positive cerebrospinal fluid, for a diagnosis of PPMS. // Results: A total of 282 patients were diagnosed with PPMS using the 2017 McDonald criteria, and 40 with alternate disorders. The 2017 McDonald RRMS DIS criteria and the modified DIS criteria including the optic nerve or ≥2 spinal cord lesions performed well in PPMS diagnosis when combined with dissemination in time/positive cerebrospinal fluid (sensitivity 92.9–95.4%, specificity 95%, accuracy 93.2–95.3%). A diagnosis of PPMS based on high fulfillment of modified RRMS DIS criteria had high specificity, but low sensitivity. A diagnostic algorithm applicable to patients evaluated for suspected MS is proposed. // Interpretation: The 2017 McDonald RRMS criteria and modifications to DIS criteria, currently under consideration, performed well in PPMS diagnosis. Forthcoming revisions to the McDonald criteria should consider a single, unified set of diagnostic criteria for MS

Performance of the 2017 and 2010 Revised McDonald Criteria in Predicting MS Diagnosis After a Clinically Isolated Syndrome: A MAGNIMS Study

BACKGROUND AND OBJECTIVES: To compare the performance of the 2017 revisions to the McDonald criteria with the 2010 McDonald criteria in establishing MS diagnosis and predicting prognosis in patients with clinically isolated syndrome (CIS) suggestive of multiple sclerosis (MS). METHODS: CSF examination, brain and spinal cord MRI obtained ≤5 months from CIS onset, and a follow-up brain MRI acquired within 15 months from CIS onset were evaluated in 785 CIS patients from 9 European centers. Date of second clinical attack and of reaching Expanded Disability Status Score (EDSS) ≥ 3.0, if they occurred, were also collected. Performance of the 2017 and 2010 McDonald criteria for dissemination in space (DIS), time (DIT) (including oligoclonal bands assessment) and DIS + DIT for predicting a second clinical attack (clinically definite [CD] MS) and EDSS ≥ 3.0 at follow-up was evaluated. Time to MS diagnosis for the different criteria was also estimated. RESULTS: At follow-up (median = 69.1 months), 406/785 CIS patients developed CDMS. At 36 months, the 2017 DIS + DIT criteria had higher sensitivity (0.83 vs 0.66), lower specificity (0.39 vs 0.60) and similar area under the curve values (0.61 vs 0.63). Median time to MS diagnosis was shorter with the 2017 vs the 2010 or CDMS criteria (2017 revision = 3.2; 2010 revision = 13.0; CDMS = 58.5 months). The 2 sets of criteria similarly predicted EDSS ≥ 3.0 milestone. Three periventricular lesions improved specificity in patients ≥45 years. DISCUSSION: The 2017 McDonald criteria showed higher sensitivity, lower specificity and similar accuracy in predicting CDMS compared to 2010 McDonald criteria, while shortening time to diagnosis of MS. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that the 2017 McDonald Criteria more accurately distinguish CDMS in patients early after a CIS when compared to the 2010 McDonald criteria

Single-subject structural cortical networks in clinically isolated syndrome

BACKGROUND: Structural cortical networks (SCNs) represent patterns of coordinated morphological modifications in cortical areas, and they present the advantage of being extracted from previously acquired clinical magnetic resonance imaging (MRI) scans. SCNs have shown pathophysiological changes in many brain disorders, including multiple sclerosis. OBJECTIVE: To investigate alterations of SCNs at the individual level in patients with clinically isolated syndrome (CIS), thereby assessing their clinical relevance. METHODS: We analyzed baseline data collected in a prospective multicenter (MAGNIMS) study. CIS patients (n = 60) and healthy controls (n = 38) underwent high-resolution 3T MRI. Measures of disability and cognitive processing were obtained for patients. Single-subject SCNs were extracted from brain 3D-T1 weighted sequences; global and local network parameters were computed. RESULTS: Compared to healthy controls, CIS patients showed altered small-world topology, an efficient network organization combining dense local clustering with relatively few long-distance connections. These disruptions were worse for patients with higher lesion load and worse cognitive processing speed. Alterations of centrality measures and clustering of connections were observed in specific cortical areas in CIS patients when compared with healthy controls. CONCLUSION: Our study indicates that SCNs can be used to demonstrate clinically relevant alterations of connectivity in CIS