[Optical coherence tomography angiography in the diagnosis of multiple sclerosis]. / Opticheskaya kogerentnaya tomografiya-angiografiya v diagnostike rasseyannogo skleroza.

PURPOSE: This study analyzes the main changes in retinal microcirculation in patients with multiple sclerosis (MS) and their relationship with the type of disease course. MATERIAL AND METHODS: 159 patients (318 eyes) were examined. The groups were formed according to the type of course and duration of MS: group 1 - 37 patients (74 eyes; 23.27%) with relapsing-remitting MS (RRMS) less than 1 year; group 2 - 47 patients (94 eyes; 29.56%) with RRMS from 1 year to 10 years; group 3 - 44 patients (86 eyes; 27.05%) with RRMS >10 years; group 4 - 32 patients (64 eyes; 20.12%) with secondary progressive MS (SPMS). Subgroups A and B were allocated within each group depending on the absence or presence of optic neuritis (ON). Patients underwent standard ophthalmological examination, including optical coherence tomography angiography (OCTA). RESULTS: A decrease in the vessel density (wiVD) and perfusion density (wiPD) in the macular and peripapillary regions was revealed, progressing with the duration of the disease and with its transition to the progressive type. The minimum values were observed in patients with SPMS (group 4), with the most pronounced in the subgroup with ON (wiVD = 16.06±3.65 mm/mm2, wiPD = 39.38±9.46%, ppwiPD = 44.06±3.09%, ppwiF = 0.41±0.05). CONCLUSION: OCTA provides the ability to detect subclinical vascular changes and can be considered a comprehensive, reliable method for early diagnosis and monitoring of MS progression.

Radiologic Lag and Brain MRI Lesion Dynamics During Attacks in MOG Antibody-Associated Disease.

BACKGROUND AND OBJECTIVES: Knowledge of the evolution of CNS demyelinating lesions within attacks could assist diagnosis. We evaluated intra-attack lesion dynamics in patients with myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) vs multiple sclerosis (MS) and aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorder (AQP4+NMOSD). METHODS: This retrospective observational multicenter study included consecutive patients from Mayo Clinic (USA) and Great Ormond Street Hospital for Children (UK). Inclusion criteria were as follows: (1) MOGAD, MS, or AQP4+NMOSD diagnosis; (2) availability of ≥2 brain MRIs (within 30 days of attack onset); and (3) brain involvement (i.e., ≥1 T2 lesion) on ≥1 brain MRI. The initial and subsequent brain MRIs within a single attack were evaluated for the following: new T2 lesions(s); resolved T2 lesion(s); both; or no change. This was compared between MOGAD, MS, and AQP4+NMOSD attacks. We used the Mann-Whitney U test and χ2/Fisher exact test for statistical analysis. RESULTS: Our cohort included 55 patients with MOGAD (median age, 14 years; interquartile range [IQR] 5-34; female sex, 29 [53%]) for a total of 58 attacks. The comparison groups included 38 patients with MS, and 19 with AQP4+NMOSD. In MOGAD, the initial brain MRI (median of 5 days from onset [IQR 3-9]) was normal in 6/58 (10%) attacks despite cerebral symptoms (i.e., radiologic lag). The commonest reason for repeat MRI was clinical worsening or no improvement (33/56 [59%] attacks with details available). When compared with the first MRI, the second intra-attack MRI (median of 8 days from initial scan [IQR 5-13]) showed the following: new T2 lesion(s) 27/58 (47%); stability 24/58 (41%); resolution of T2 lesion(s) 4/58 (7%); or both new and resolved T2 lesions 3/58 (5%). Findings were similar between children and adults. Steroid treatment was associated with resolution of ≥1 T2 lesion (6/28 [21%] vs 1/30 [3%], p = 0.048) and reduced the likelihood of new T2 lesions (9/28 vs 18/30, p = 0.03). Intra-attack MRI changes favored MOGAD (34/58 [59%]) over MS (10/38 [26%], p = 0.002) and AQP4+NMOSD (4/19 [21%], p = 0.007). Resolution of ≥1 T2 lesions was exclusive to MOGAD (7/58 [12%]). DISCUSSION: Radiologic lag is common within MOGAD attacks. Dynamic imaging with frequent appearance and occasional disappearance of lesions within a single attack suggest MOGAD diagnosis over MS and AQP4+NMOSD. These findings have implications for clinical practice, clinical trial attack adjudication, and understanding of MOGAD pathogenesis.

Diagnostic effectiveness of deep learning-based MRI in predicting multiple sclerosis: A meta-analysis.

OBJECTIVES: The brain and spinal cord, constituting the central nervous system (CNS), could be impacted by an inflammatory disease known as multiple sclerosis (MS). The convolutional neural networks (CNN), a machine learning method, can detect lesions early by learning patterns on brain magnetic resonance image (MRI). We performed this study to investigate the diagnostic performance of CNN based MRI in the identification, classification, and segmentation of MS lesions. METHODS: PubMed, Web of Science, Embase, the Cochrane Library, CINAHL, and Google Scholar were used to retrieve papers reporting the use of CNN based MRI in MS diagnosis. The accuracy, the specificity, the sensitivity, and the Dice Similarity Coefficient (DSC) were evaluated in this study. RESULTS: In total, 2174 studies were identified and only 15 articles met the inclusion criteria. The 2D-3D CNN presented a high accuracy (98.81, 95% CI: 98.50-99.13), sensitivity (98.76, 95% CI: 98.42-99.10), and specificity (98.67, 95% CI: 98.22-99.12) in the identification of MS lesions. Regarding classification, the overall accuracy rate was significantly high (91.38, 95% CI: 83.23-99.54). A DSC rate of 63.78 (95% CI: 58.29-69.27) showed that 2D-3D CNN-based MRI performed highly in the segmentation of MS lesions. Sensitivity analysis showed that the results are consistent, indicating that this study is robust. CONCLUSION: This metanalysis revealed that 2D-3D CNN based MRI is an automated system that has high diagnostic performance and can promptly and effectively predict the disease.

Improving multiple sclerosis lesion segmentation across clinical sites: A federated learning approach with noise-resilient training.

Accurately measuring the evolution of Multiple Sclerosis (MS) with magnetic resonance imaging (MRI) critically informs understanding of disease progression and helps to direct therapeutic strategy. Deep learning models have shown promise for automatically segmenting MS lesions, but the scarcity of accurately annotated data hinders progress in this area. Obtaining sufficient data from a single clinical site is challenging and does not address the heterogeneous need for model robustness. Conversely, the collection of data from multiple sites introduces data privacy concerns and potential label noise due to varying annotation standards. To address this dilemma, we explore the use of the federated learning framework while considering label noise. Our approach enables collaboration among multiple clinical sites without compromising data privacy under a federated learning paradigm that incorporates a noise-robust training strategy based on label correction. Specifically, we introduce a Decoupled Hard Label Correction (DHLC) strategy that considers the imbalanced distribution and fuzzy boundaries of MS lesions, enabling the correction of false annotations based on prediction confidence. We also introduce a Centrally Enhanced Label Correction (CELC) strategy, which leverages the aggregated central model as a correction teacher for all sites, enhancing the reliability of the correction process. Extensive experiments conducted on two multi-site datasets demonstrate the effectiveness and robustness of our proposed methods, indicating their potential for clinical applications in multi-site collaborations to train better deep learning models with lower cost in data collection and annotation.

Hippocampal subfields and thalamic nuclei associations with clinical outcomes in multiple sclerosis: An ultrahigh field MRI study.

BACKGROUND: Previous studies have shown that thalamic and hippocampal neurodegeneration is associated with clinical decline in Multiple Sclerosis (MS). However, contributions of the specific thalamic nuclei and hippocampal subfields require further examination. OBJECTIVE: Using 7 Tesla (7T) magnetic resonance imaging (MRI), we investigated the cross-sectional associations between functionally grouped thalamic nuclei and hippocampal subfields volumes and T1 relaxation times (T1-RT) and subsequent clinical outcomes in MS. METHODS: High-resolution T1-weighted and T2-weighted images were acquired at 7T (n=31), preprocessed, and segmented using the Thalamus Optimized Multi Atlas Segmentation (THOMAS, for thalamic nuclei) and the Automatic Segmentation of Hippocampal Subfields (ASHS, for hippocampal subfields) packages. We calculated Pearson correlations between hippocampal subfields and thalamic nuclei volumes and T1-RT and subsequent multi-modal rater-determined and patient-reported clinical outcomes (∼2.5 years after imaging acquisition), correcting for confounders and multiple tests. RESULTS: Smaller volume bilaterally in the anterior thalamus region correlated with worse performance in gait function, as measured by the Patient Determined Disease Steps (PDDS). Additionally, larger volume in most functional groups of thalamic nuclei correlated with better visual information processing and cognitive function, as measured by the Symbol Digit Modalities Test (SDMT). In bilateral medial and left posterior thalamic regions, there was an inverse association between volumes and T1-RT, potentially indicating higher tissue degeneration in these regions. We also observed marginal associations between the right hippocampal subfields (both volumes and T1-RT) and subsequent clinical outcomes, though they did not survive correction for multiple testing. CONCLUSION: Ultrahigh field MRI identified markers of structural damage in the thalamic nuclei associated with subsequently worse clinical outcomes in individuals with MS. Longitudinal studies will enable better understanding of the role of microstructural integrity in these brain regions in influencing MS outcomes.

Radiologically isolated syndrome in the spectrum of multiple sclerosis.

The radiologically isolated syndrome (RIS) currently represents the earliest detectable preclinical phase of multiple sclerosis (MS). Remarkable advancements have been recently made, including the identification of risk factors for disease evolution, revisions to the existing 2009 RIS criteria, and our understanding of the impact of early disease-modifying therapy use in the prevention/delay of symptomatic MS from two randomized clinical trials. Here, we discuss RIS in the context of the spectrum of MS, implications in the clinical management of individuals, and provide insights into future opportunities and challenges given the anticipated inclusion of asymptomatic MS in the formal definition of MS.

Temporal Relationship Between Serum Neurofilament Light Chain and Radiologic Disease Activity in Patients With Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: Serum neurofilament light chain (sNfL) levels correlate with multiple sclerosis (MS) disease activity, but the dynamics of this correlation are unknown. We evaluated the relationship between sNfL levels and radiologic MS disease activity through monthly assessments during the 24-week natalizumab treatment interruption period in RESTORE (NCT01071083). METHODS: In the RESTORE trial, participants with relapsing forms of MS who had received natalizumab for ≥12 months were randomized to either continue or stop natalizumab and followed with MRI and blood draws every 4 weeks to week 28 and again at week 52 The sNfL was measured, and its dynamics were correlated with the development of gadolinium-enhancing (Gd+) lesions. Log-linear trend in sNfL levels were modeled longitudinally using generalized estimating equations with robust variance estimator from baseline to week 28. RESULTS: Of 175 patients enrolled in RESTORE, 166 had serum samples for analysis. Participants with Gd+ lesions were younger (37.7 vs 43.1, p = 0.001) and had lower Expanded Disability Status Scale scores at baseline (2.7 vs 3.4, p = 0.017) than participants without Gd+ lesions. sNfL levels increased in participants with Gd+ lesions (n = 65) compared with those without (n = 101, mean change from baseline to maximum sNfL value, 12.1 vs 3.2 pg/mL, respectively; p = 0.003). As the number of Gd+ lesions increased, peak median sNfL change also increased by 1.4, 3.0, 4.3, and 19.6 pg/mL in the Gd+ lesion groups of 1 (n = 12), 2-3 (n = 18), 4-9 (n = 21), and ≥10 (n = 14) lesions, respectively. However, 46 of 65 (71%) participants with Gd+ lesions did not increase above the 95th percentile threshold of the group without Gd+ lesions. The initial increase of sNfL typically trailed the first observation of Gd+ lesions, and the peak increase in sNfL was a median [interquartile range] of 8 [0, 12] weeks after the first appearance of the Gd+ lesion. DISCUSSION: Although sNfL correlated with the presence of Gd+ lesions, most participants with Gd+ lesions did not have elevations in sNfL levels. These observations have implications for the use and interpretation of sNfL as a biomarker for monitoring MS disease activity in controlled trials and clinical practice.

Predictors of multiple sclerosis progression: A systematic review of conventional magnetic resonance imaging studies.

INTRODUCTION: Multiple Sclerosis (MS) is a chronic neurodegenerative disorder that affects the central nervous system (CNS) and results in progressive clinical disability and cognitive decline. Currently, there are no specific imaging parameters available for the prediction of longitudinal disability in MS patients. Magnetic resonance imaging (MRI) has linked imaging anomalies to clinical and cognitive deficits in MS. In this study, we aimed to evaluate the effectiveness of MRI in predicting disability, clinical progression, and cognitive decline in MS. METHODS: In this study, according to PRISMA guidelines, we comprehensively searched the Web of Science, PubMed, and Embase databases to identify pertinent articles that employed conventional MRI in the context of Relapsing-Remitting and progressive forms of MS. Following a rigorous screening process, studies that met the predefined inclusion criteria were selected for data extraction and evaluated for potential sources of bias. RESULTS: A total of 3028 records were retrieved from database searching. After a rigorous screening, 53 records met the criteria and were included in this study. Lesions and alterations in CNS structures like white matter, gray matter, corpus callosum, thalamus, and spinal cord, may be used to anticipate disability progression. Several prognostic factors associated with the progression of MS, including presence of cortical lesions, changes in gray matter volume, whole brain atrophy, the corpus callosum index, alterations in thalamic volume, and lesions or alterations in cross-sectional area of the spinal cord. For cognitive impairment in MS patients, reliable predictors include cortical gray matter volume, brain atrophy, lesion characteristics (T2-lesion load, temporal, frontal, and cerebellar lesions), white matter lesion volume, thalamic volume, and corpus callosum density. CONCLUSION: This study indicates that MRI can be used to predict the cognitive decline, disability progression, and disease progression in MS patients over time.

Functional gradients reveal cortical hierarchy changes in multiple sclerosis.

Functional gradient (FG) analysis represents an increasingly popular methodological perspective for investigating brain hierarchical organization but whether and how network hierarchy changes concomitant with functional connectivity alterations in multiple sclerosis (MS) has remained elusive. Here, we analyzed FG components to uncover possible alterations in cortical hierarchy using resting-state functional MRI (rs-fMRI) data acquired in 122 MS patients and 97 healthy control (HC) subjects. Cortical hierarchy was assessed by deriving regional FG scores from rs-fMRI connectivity matrices using a functional parcellation of the cerebral cortex. The FG analysis identified a primary (visual-to-sensorimotor) and a secondary (sensory-to-transmodal) component. Results showed a significant alteration in cortical hierarchy as indexed by regional changes in FG scores in MS patients within the sensorimotor network and a compression (i.e., a reduced standard deviation across all cortical parcels) of the sensory-transmodal gradient axis, suggesting disrupted segregation between sensory and cognitive processing. Moreover, FG scores within limbic and default mode networks were significantly correlated ( ρ = 0.30 $$ \rho =0.30 $$ , p < .005 after Bonferroni correction for both) with the symbol digit modality test (SDMT) score, a measure of information processing speed commonly used in MS neuropsychological assessments. Finally, leveraging supervised machine learning, we tested the predictive value of network-level FG features, highlighting the prominent role of the FG scores within the default mode network in the accurate prediction of SDMT scores in MS patients (average mean absolute error of 1.22 ± 0.07 points on a hold-out set of 24 patients). Our work provides a comprehensive evaluation of FG alterations in MS, shedding light on the hierarchical organization of the MS brain and suggesting that FG connectivity analysis can be regarded as a valuable approach in rs-fMRI studies across different MS populations.

Comparative analysis of glymphatic system alterations in multiple sclerosis and neuromyelitis optica spectrum disorder using MRI indices from diffusion tensor imaging.

OBJECTIVE: The glymphatic system is a glial-based perivascular network that promotes brain metabolic waste clearance. Glymphatic system dysfunction has been observed in both multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD), indicating the role of neuroinflammation in the glymphatic system. However, little is known about how the two diseases differently affect the human glymphatic system. The present study aims to evaluate the diffusion MRI-based measures of the glymphatic system by contrasting MS and NMOSD. METHODS: This prospective study included 63 patients with NMOSD (n = 21) and MS (n = 42) who underwent DTI. The fractional volume of extracellular-free water (FW) and an index of diffusion tensor imaging (DTI) along the perivascular space (DTI-ALPS) were used as indirect indicators of water diffusivity in the interstitial extracellular and perivenous spaces of white matter, respectively. Age and EDSS scores were adjusted. RESULTS: Using Bayesian hypothesis testing, we show that the present data substantially favor the null model of no differences between MS and NMOSD for the diffusion MRI-based measures of the glymphatic system. The inclusion Bayes factor (BF10) of model-averaged probabilities of the group (MS, NMOSD) was 0.280 for FW and 0.236 for the ALPS index. CONCLUSION: Together, these findings suggest that glymphatic alteration associated with MS and NMOSD might be similar and common as an eventual result, albeit the disease etiologies differ. PRACTITIONER POINTS: Previous literature indicates important glymphatic system alteration in MS and NMOSD. We explore the difference between MS and NMOSD using diffusion MRI-based measures of the glymphatic system. We show support for the null hypothesis of no difference between MS and NMOSD. This suggests that glymphatic alteration associated with MS and NMOSD might be similar and common etiology.

Glial Activity Load on PET Reveals Persistent "Smoldering" Inflammation in MS Despite Disease-Modifying Treatment: 18 F-PBR06 Study.

PURPOSE OF THE REPORT: 18 F-PBR06-PET targeting 18-kDa translocator protein can detect abnormal microglial activation (MA) in multiple sclerosis (MS). The objectives of this study are to develop individualized mapping of MA using 18 F-PBR06, to determine the effect of disease-modifying treatment (DMT) efficacy on reducing MA, and to determine its clinical, radiological, and serological correlates in MS patients. PATIENTS AND METHODS: Thirty 18 F-PBR06-PET scans were performed in 22 MS patients (mean age, 46 ± 13 years; 16 females) and 8 healthy controls (HCs). Logarithmically transformed "glial activity load on PET" scores (calculated as the sum of voxel-by-voxel z -scores ≥4), "lnGALP," were compared between MS and HC and between MS subjects on high-efficacy DMTs (H-DMT, n = 13) and those on no or lower-efficacy treatment, and correlated with clinical measures, serum biomarkers, and cortical thickness. RESULTS: Cortical gray matter (CoGM) and white matter (WM) lnGALP scores were higher in MS versus HC (+33% and +48%, P < 0.001). In H-DMT group, CoGM and WM lnGALP scores were significantly lower than lower-efficacy treatment ( P < 0.01) but remained abnormally higher than in HC group ( P = 0.006). Within H-DMT patients, CoGM lnGALP scores correlated positively with physical disability, fatigue and serum glial fibrillary acid protein levels ( r = 0.65-0.79, all P 's < 0.05), and inversely with cortical thickness ( r = -0.66, P < 0.05). CONCLUSIONS: High-efficacy DMTs decrease, but do not normalize, CoGM and WM MA in MS patients. Such "residual" MA in CoGM is associated with clinical disability, serum biomarkers, and cortical degeneration. Individualized mapping of translocator protein PET using 18 F-PBR06 is clinically feasible and can potentially serve as an imaging biomarker for evaluating "smoldering" inflammation in MS patients.

Structural and functional correlates of disability, motor and cognitive performances in multiple sclerosis: Focus on the globus pallidus.

OBJECTIVES: To explore structural and functional alterations of external (GPe) and internal (GPi) globus pallidus in people with multiple sclerosis (pwMS) compared to healthy controls (HC) and analyze their relationship with measures of clinical disability, motor and cognitive impairment. METHODS: Sixty pwMS and 30 HC comparable for age and sex underwent 3.0T MRI, including conventional, diffusion tensor MRI and resting state (RS) functional MRI. Expanded Disability Status Scale (EDSS) scores were rated and timed 25-foot walk (T25FW) test, nine-hole peg test (9HPT), and paced auditory serial addition test (PASAT) were administered. Two operators segmented the GP into GPe and GPi. Volumes, T1/T2 ratio, diffusivity indices and seed-based RS functional connectivity (FC) of the GP and its components were assessed. RESULTS: PwMS had no atrophy or altered diffusivity measures of the GP. Compared to HC, pwMS had higher T1/T2 ratio in both GP regions, which correlated with EDSS score (r = 0.26-0.39, p = 0.01-0.05). RS FC analysis highlighted component-specific functional alterations in pwMS: the GPe had decreased RS FC with fronto-parietal cortices, whereas the GPi had decreased intra-GP RS FC and increased RS FC with the thalamus. Worse EDSS, 9HPT, T25FW and PASAT scores were associated with GP RS FC modifications (r=-0.51‒0.51, p < 0.001). CONCLUSIONS: Structural GP involvement in MS was homogeneous across its portions. Increased T1/T2 ratio values, possibly representing iron accumulation, were related to more severe disability. RS FC alterations of the GPe and GPi were consistent with their roles within the basal ganglia network and correlated with worse functional status, suggesting less efficient communication between structures.

Artificial intelligence in multiple sclerosis management: Challenges in a new era.

Multiple sclerosis poses diagnostic and therapeutic challenges for healthcare professionals, with a high risk of misdiagnosis and difficulties in assessing therapeutic effectiveness. Artificial intelligence, particularly machine learning and deep neural networks, emerges as a promising tool to address these challenges. These technologies have the capability to analyze a wide range of data, from magnetic resonance imaging to genetic information, to provide more accurate diagnoses, classify multiple sclerosis subtypes, and predict disease progression and treatment response with extraordinary precision. However, their implementation raises ethical dilemmas, such as accountability in case of errors and the risk of excessive reliance on healthcare personnel. That said, this manuscript aims to urge healthcare professionals dedicated to the care and research of multiple sclerosis patients to recognize artificial intelligence as a valuable and complementary resource in their clinical practice. It also seeks to emphasize the importance of integrating this type of technology safely and responsibly, thereby ensuring the ethics and welfare of patients.

Event-related desynchronization and synchronization in multiple sclerosis.

BACKGROUND: Motor preparation and execution can be impaired in patients with multiple sclerosis (pwMS). These neural processes can be assessed using electroencephalography (EEG). During a self-paced movement, EEG signal amplitude decreases before movement (event-related desynchronization, ERD) and increases after movement (event-related synchronization, ERS). OBJECTIVE: To reappraise ERD/ERS changes in pwMS compared to healthy controls (HC). METHODS: This single-center study included 13 pwMS and 10 sex/age-matched HC. 60-channel EEG was recorded during two self-paced movements of the right hand: a simple index finger extension task and a more complex finger tapping task. Clinical variables included MS type, sex, age, disease duration, disability, grip strength, fatigue and attentional performance. EEG variables included ERD and ERS onset latency, duration, and amplitude determined using two methods of signal analyses (based on visual or automated determination) in the alpha and beta frequency bands in five cortical regions: right and left frontocentral and centroparietal regions and a midline region. Neuroimaging variables included the volumes of four deep brain structures (thalamus, putamen, pallidum and caudate nucleus) and the relative lesion load. RESULTS: ERD/ERS changes in pwMS compared to HC were observed only in the beta band. In pwMS, beta-ERD had a delayed onset in the midline and right parietocentral regions and a shortened duration or increased amplitude in the parietocentral region; beta-ERS had a shorter duration, delayed onset, or reduced amplitude in the left parieto/frontocentral region. In addition, pwMS with a more delayed beta-ERD in the midline region had less impaired executive functions but increased caudate nuclei volume, while pwMS with a more delayed beta-ERS in the parietocentral region contralateral to the movement had less fatigue but increased thalami volume. CONCLUSION: This study confirms an alteration of movement preparation and execution in pwMS, mainly characterized by a delayed cortical activation (ERD) and a delayed and reduced post-movement inhibition (ERS) in the beta band. Compensatory mechanisms could be involved in these changes, associating more preserved clinical performance and overactivation of deep brain structures.

A novel imaging marker of cortical "cellularity" in multiple sclerosis patients.

Pathological data showed focal inflammation and regions of diffuse neuronal loss in the cortex of people with multiple sclerosis (MS). In this work, we applied a novel model ("soma and neurite density imaging (SANDI)") to multishell diffusion-weighted MRI data acquired in healthy subjects and people with multiple sclerosis (pwMS), in order to investigate inflammation and degeneration-related changes in the cortical tissue of pwMS. We aimed to (i) establish whether SANDI is applicable in vivo clinical data; (ii) investigate inflammatory and degenerative changes using SANDI soma fraction (fsoma)-a marker of cellularity-in both cortical lesions and in the normal-appearing-cortex and (iii) correlate SANDI fsoma with clinical and biological measures in pwMS. We applied a simplified version of SANDI to a clinical scanners. We then provided evidence that pwMS exhibited an overall decrease in cortical SANDI fsoma compared to healthy subjects, suggesting global degenerative processes compatible with neuronal loss. On the other hand, we have found that progressive pwMS showed a higher SANDI fsoma in the outer part of the cortex compared to relapsing-remitting pwMS, possibly supporting current pathological knowledge of increased innate inflammatory cells in these regions. A similar finding was obtained in subpial lesions in relapsing-remitting patients, reflecting existing pathological data in these lesion types. A significant correlation was found between SANDI fsoma and serum neurofilament light chain-a biomarker of inflammatory axonal damage-suggesting a relationship between SANDI soma fraction and inflammatory processes in pwMS again. Overall, our data show that SANDI fsoma is a promising biomarker to monitor changes in cellularity compatible with neurodegeneration and neuroinflammation in the cortex of MS patients.

Modeling and simulation for prediction of multiple sclerosis progression.

In light of extensive work that has created a wide range of techniques for predicting the course of multiple sclerosis (MS) disease, this paper attempts to provide an overview of these approaches and put forth an alternative way to predict the disease progression. For this purpose, the existing methods for estimating and predicting the course of the disease have been categorized into clinical, radiological, biological, and computational or artificial intelligence-based markers. Weighing the weaknesses and strengths of these prognostic groups is a profound method that is yet in need and works directly at the level of diseased connectivity. Therefore, we propose using the computational models in combination with established connectomes as a predictive tool for MS disease trajectories. The fundamental conduction-based Hodgkin-Huxley model emerged as promising from examining these studies. The advantage of the Hodgkin-Huxley model is that certain properties of connectomes, such as neuronal connection weights, spatial distances, and adjustments of signal transmission rates, can be taken into account. It is precisely these properties that are particularly altered in MS and that have strong implications for processing, transmission, and interactions of neuronal signaling patterns. The Hodgkin-Huxley (HH) equations as a point-neuron model are used for signal propagation inside a small network. The objective is to change the conduction parameter of the neuron model, replicate the changes in myelin properties in MS and observe the dynamics of the signal propagation across the network. The model is initially validated for different lengths, conduction values, and connection weights through three nodal connections. Later, these individual factors are incorporated into a small network and simulated to mimic the condition of MS. The signal propagation pattern is observed after inducing changes in conduction parameters at certain nodes in the network and compared against a control model pattern obtained before the changes are applied to the network. The signal propagation pattern varies as expected by adapting to the input conditions. Similarly, when the model is applied to a connectome, the pattern changes could give an insight into disease progression. This approach has opened up a new path to explore the progression of the disease in MS. The work is in its preliminary state, but with a future vision to apply this method in a connectome, providing a better clinical tool.

Feasibility and tolerability of portable, low-field brain MRI for patients with multiple sclerosis.

Low-field, portable MRI (LF-MRI) promises to expand neuroimaging access for patients with multiple sclerosis (MS). We aimed to measure the feasibility and tolerability of LF-MRI for clinical use in 50 people with MS (mean age 46.5 ± 15.3 years; 72 % female; median disease duration 5.9 years), 38 % of whom reported barriers to undergoing MRI, and 34 % of whom were low-income or unemployed. Experience ratings of LF-MRI were strongly positive (mean rating of 9.2 on a ten-point scale). Seventy percent of participants were willing to receive future LF-MRI scans, and 46 % preferred LF-MRI to standard MRI (35 % undecided). The overall feasibility and tolerability of LF-MRI support its integration into a one-stop, patient-centered model of outpatient MS care.

Intrathecal B cell activation and memory impairment in multiple sclerosis.

BACKGROUND: Cognitive impairment (CI) is a common and disabling feature of people with multiple sclerosis (pwMS), but its underlying mechanisms are heterogenous and not fully understood. A role of infiltrating immune cells in the meninges and brain parenchyma has been hypothesized. This study aimed to explore the hypothesis that intrathecal B cells might influence cognitive performance in pwMS. METHODS: A retrospective study was performed on 39 newly diagnosed pwMS who underwent cerebrospinal fluid (CSF) analysis. Kappa (κ)-index was measured as a biomarker of intrathecal B cell activation. Cognitive performance was assessed using the Brief Repeatable Battery of Neuropsychological Tests (BRBN). Brain T2 lesions number (T2LN) and volume (T2LV) together with brain, cortical grey matter, thalamic and hippocampal volumes were calculated to account for MRI-visible damage. RESULTS: κ-index was higher in pwMS with verbal memory impairment (median 99.6, range 58.5-195.2 vs. median 37.2, range 2.3-396.9, p < 0.001), and it was negatively associated with BRBN tests exploring verbal memory and information processing speed. In multivariate models, higher κ-index was confirmed to be independently associated with worse scores of BRBN tests exploring verbal memory and with a higher probability of verbal memory impairment. CONCLUSION: Intrathecal B cells might drive memory impairment in pwMS independently of brain damage visible on MRI scans.

Evaluation of IVIM in the Spinal Cord of Multiple Sclerosis Patients.

PURPOSE: To evaluate the ability of intravoxel incoherent motion (IVIM), a perfusion-weighted imaging technique, to differentiate microcirculation changes in the spinal cord of patients with multiple sclerosis (MS) compared with healthy individuals. METHODS: Fifteen healthy individuals and 15 individuals with MS underwent IVIM magnetic resonance (MR) imaging using a 3 T scanner with 2-D axial gradient recalled echo and 2-D axial diffusion-weighted imaging (DWI) sequences. The MR images underwent segmentation to produce white matter and gray matter regions of interest. IVIM metrics for perfusion fraction, pseudo-diffusion coefficients, water-diffusion coefficients, and signal without diffusion encoding were calculated using DWI data. An unpaired t test was performed on these IVIM metrics to compare imaging of healthy individuals with imaging of individuals with MS. RESULTS: No significant differences between images from healthy individuals and individuals with MS were found for any IVIM metric. The lowest P values calculated (.082 and .055) were in the white matter region of interest perfusion fraction and pseudo-diffusion measurements. The gray matter region of interest had the highest P value. DISCUSSION: The findings in this study are consistent with current perfusion-weighted imaging literature focused on MS in the brain. The gray matter in MS patients in this study showed reduced perfusion compared with healthy individuals. CONCLUSION: IVIM is a promising imaging technique for the evaluation of the spinal cord in MS patients. It has the potential to provide valuable information on microvascular perfusion and diffusion in the spinal cord, which might be related to disease progression and response to treatment.

Radiologically isolated syndromes: to treat or not to treat?

The widespread use of magnetic resonance imaging (MRI) has led to increased detection of individuals exhibiting asymptomatic brain and spinal cord lesions suggestive of multiple sclerosis (MS), defined as "radiologically isolated syndrome" (RIS). Specific criteria have been proposed and updated over time to identify individuals with RIS. Moreover, a younger age, the presence of infratentorial, spinal cord or gadolinium-enhancing lesions, as well as of cerebrospinal fluid-specific oligoclonal bands have been recognized as relevant risk factors for the occurrence of a first clinical event. Recent randomized controlled trials conducted in individuals with RIS have shown that dimethyl fumarate and teriflunomide significantly reduce the occurrence of clinical events in this population. These findings support the notion that early treatment initiation may positively influence the prognosis of these patients. However, several aspects should be taken into account before treating individuals with RIS in the real-world clinical setting, including an accurate identification of individuals with RIS to avoid misdiagnosis, a precise stratification of their risk of experiencing a first clinical event and further data supporting favorable balance between benefits and risks, even in the long term. This commentary provides an overview of the latest updates in RIS diagnosis, prognosis, and emerging treatment evidence.