Visual Snow Syndrome Improves With Modulation of Resting-State Functional MRI Connectivity After Mindfulness-Based Cognitive Therapy: An Open-Label Feasibility Study

BACKGROUND: Visual snow syndrome (VSS) is associated with functional connectivity (FC) dysregulation of visual networks (VNs). We hypothesized that mindfulness-based cognitive therapy, customized for visual symptoms (MBCT-vision), can treat VSS and modulate dysfunctional VNs. METHODS: An open-label feasibility study for an 8-week MBCT-vision treatment program was conducted. Primary (symptom severity; impact on daily life) and secondary (WHO-5; CORE-10) outcomes at Week 9 and Week 20 were compared with baseline. Secondary MRI outcomes in a subcohort compared resting-state functional and diffusion MRI between baseline and Week 20. RESULTS: Twenty-one participants (14 male participants, median 30 years, range 22-56 years) recruited from January 2020 to October 2021. Two (9.5%) dropped out. Self-rated symptom severity (0-10) improved: baseline (median [interquartile range (IQR)] 7 [6-8]) vs Week 9 (5.5 [3-7], P = 0.015) and Week 20 (4 [3-6], P < 0.001), respectively. Self-rated impact of symptoms on daily life (0-10) improved: baseline (6 [5-8]) vs Week 9 (4 [2-5], P = 0.003) and Week 20 (2 [1-3], P < 0.001), respectively. WHO-5 Wellbeing (0-100) improved: baseline (median [IQR] 52 [36-56]) vs Week 9 (median 64 [47-80], P = 0.001) and Week 20 (68 [48-76], P < 0.001), respectively. CORE-10 Distress (0-40) improved: baseline (15 [12-20]) vs Week 9 (12.5 [11-16.5], P = 0.003) and Week 20 (11 [10-14], P = 0.003), respectively. Within-subject fMRI analysis found reductions between baseline and Week 20, within VN-related FC in the i) left lateral occipital cortex (size = 82 mL, familywise error [FWE]-corrected P value = 0.006) and ii) left cerebellar lobules VIIb/VIII (size = 65 mL, FWE-corrected P value = 0.02), and increases within VN-related FC in the precuneus/posterior cingulate cortex (size = 69 mL, cluster-level FWE-corrected P value = 0.02). CONCLUSIONS: MBCT-vision was a feasible treatment for VSS, improved symptoms and modulated FC of VNs. This study also showed proof-of-concept for intensive mindfulness interventions in the treatment of neurological conditions

Improving explanation of motor disability with diffusion-based graph metrics at onset of the first demyelinating event

BACKGROUND: Conventional magnetic resonance imaging (MRI) does not account for all disability in multiple sclerosis. OBJECTIVE: The objective was to assess the ability of graph metrics from diffusion-based structural connectomes to explain motor function beyond conventional MRI in early demyelinating clinically isolated syndrome (CIS). METHODS: A total of 73 people with CIS underwent conventional MRI, diffusion-weighted imaging and clinical assessment within 3 months from onset. A total of 28 healthy controls underwent MRI. Structural connectomes were produced. Differences between patients and controls were explored; clinical associations were assessed in patients. Linear regression models were compared to establish relevance of graph metrics over conventional MRI. RESULTS: Local efficiency (p = 0.045), clustering (p = 0.034) and transitivity (p = 0.036) were reduced in patients. Higher assortativity was associated with higher Expanded Disability Status Scale (EDSS) (β = 74.9, p = 0.026) scores. Faster timed 25-foot walk (T25FW) was associated with higher assortativity (β = 5.39, p = 0.026), local efficiency (β = 27.1, p = 0.041) and clustering (β = 36.1, p = 0.032) and lower small-worldness (β = -3.27, p = 0.015). Adding graph metrics to conventional MRI improved EDSS (p = 0.045, ΔR2 = 4) and T25FW (p < 0.001, ΔR2 = 13.6) prediction. CONCLUSION: Graph metrics are relevant early in demyelination. They show differences between patients and controls and have relationships with clinical outcomes. Segregation (local efficiency, clustering, transitivity) was particularly relevant. Combining graph metrics with conventional MRI better explained disability

Using the Progression Independent of Relapse Activity Framework to Unveil the Pathobiological Foundations of Multiple Sclerosis

Progression independent of relapse activity (PIRA), a recent concept to formalize disability accrual in multiple sclerosis (MS) independent of relapses, has gained popularity as a potential clinical trial outcome. We discuss its shortcomings and appraise the challenges of implementing it in clinical settings, experimental trials, and research. The current definition of PIRA assumes that acute inflammation, which can manifest as a relapse, and neurodegeneration, manifesting as progressive disability accrual, can be disentangled by introducing specific time windows between the onset of relapses and the observed increase in disability. The term PIRMA (progression independent of relapse and MRI activity) was recently introduced to indicate disability accrual in the absence of both clinical relapses and new brain and spinal cord MRI lesions. Assessing PIRMA in clinical practice is highly challenging because it necessitates frequent clinical assessments and brain and spinal cord MRI scans. PIRA is commonly assessed using Expanded Disability Status Scale, a scale heavily weighted toward motor disability, whereas a more granular assessment of disability deterioration, including cognitive decline, using composite measures or other tools, such as digital tools, would possess greater utility. Similarly, using PIRA as an outcome measure in randomized clinical trials is also challenging and requires methodological considerations. The underpinning pathobiology of disability accumulation, that is not associated with relapses, may encompass chronic active lesions (slowly expanding lesions and paramagnetic rim lesions), cortical lesions, brain and spinal cord atrophy, particularly in the gray matter, diffuse and focal microglial activation, persistent leptomeningeal enhancement, and white matter tract damage. We propose to use PIRA to understand the main determinant of disability accrual in observational, cohort studies, where regular MRI scans are not included, and introduce the term of “advanced-PIRMA” to investigate the contributions to disability accrual of the abovementioned processes, using conventional and advanced imaging. This is supported by the knowledge that MRI reflects the MS pathogenic mechanisms better than purely clinical descriptors. Any residual disability accrual, which remains unexplained after considering all these mechanisms with imaging, will highlight future research priorities to help complete our understanding of MS pathogenesis

Prognostic value of single-subject grey matter networks in early multiple sclerosis

The identification of prognostic markers in early multiple sclerosis (MS) is challenging and requires reliable measures that robustly predict future disease trajectories. Ideally, such measures should make inferences at the individual level to inform clinical decisions. This study investigated the prognostic value of longitudinal structural networks to predict five-year EDSS progression in patients with relapsing-remitting MS (RRMS). We hypothesized that network measures, derived from magnetic resonance imaging (MRI), outperform conventional MRI measurements at identifying patients at risk of developing disability progression. This longitudinal, multicentre study within the Magnetic Resonance Imaging in MS (MAGNIMS) network included 406 patients with RRMS (mean age = 35.7 ± 9.1 years) followed up for five years (mean follow-up = 5.0 ± 0.6 years). Expanded Disability Status Scale (EDSS) was determined to track disability accumulation. A group of 153 healthy subjects (mean age = 35.0 ± 10.1 years) with longitudinal MRI served as controls. All subjects underwent MRI at baseline and again one year after baseline. Grey matter (GM) atrophy over one year and white matter (WM) lesion load were determined. A single-subject brain network was reconstructed from T1-weighted scans based on GM atrophy measures derived from a statistical parameter mapping (SPM)-based segmentation pipeline. Key topological measures, including network degree, global efficiency and transitivity, were calculated at single-subject level to quantify network properties related to EDSS progression. Areas under receiver operator characteristic (ROC) curves were constructed for GM atrophy, WM lesion load and the network measures, and comparisons between ROC curves were conducted. The applied network analyses differentiated patients with RRMS who experience EDSS progression over five years through lower values for network degree [H(2)=30.0, p<0.001] and global efficiency [H(2)=31.3, p<0.001] from healthy controls but also from patients without progression. For transitivity, the comparisons showed no difference between the groups (H(2)= 1.5, p=0.474). Most notably, changes in network degree and global efficiency were detected independent of disease activity in the first year. The described network reorganization in patients experiencing EDSS progression was evident in the absence of GM atrophy. Network degree and global efficiency measurements demonstrated superiority of network measures in the ROC analyses over GM atrophy and WM lesion load in predicting EDSS worsening (all p-values < 0.05). Our findings provide evidence that GM network reorganization over one year discloses relevant information about subsequent clinical worsening in RRMS. Early GM restructuring towards lower network efficiency predicts disability accumulation and outperforms conventional MRI predictors

Clinical relevance of cortical network dynamics in early primary progressive MS.

BACKGROUND: Structural cortical networks (SCNs) reflect the covariance between the cortical thickness of different brain regions, which may share common functions and a common developmental evolution. SCNs appear abnormal in neurodegenerative conditions such as Alzheimer's and Parkinson's diseases, but have never been assessed in primary progressive multiple sclerosis (PPMS). OBJECTIVE: The aim of this study was to test whether SCNs are abnormal in early PPMS and change over 5 years, and correlate with disability worsening. METHODS: A total of 29 PPMS patients and 13 healthy controls underwent clinical and brain magnetic resonance imaging (MRI) assessments for 5 years. Baseline and 5-year follow-up cortical thickness values were obtained and used to build correlation matrices, considered as weighted graphs to obtain network metrics. Bootstrap-based statistics assessed SCN differences between patients and controls and between patients with fast and slow progression. RESULTS: At baseline, patients showed features of lower connectivity (p = 0.02) and efficiency (p < 0.001) than controls. Over 5 years, patients, especially those with fastest clinical progression, showed significant changes suggesting an increase in network connectivity (p < 0.001) and efficiency (p < 0.02), not observed in controls. CONCLUSION: SCNs are abnormal in early PPMS. Longitudinal SCN changes demonstrated a switch from low- to high-efficiency networks especially among fast progressors, indicating their clinical relevance

Differentiating Multiple Sclerosis From AQP4-Neuromyelitis Optica Spectrum Disorder and MOG-Antibody Disease With Imaging

Background and objectives: Relapsing remitting multiple sclerosis (RRMS), aquaporin4 antibody-positive neuromyelitis optica spectrum disorder (AQP4-NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) may have overlapping clinical features. There is an unmet need for imaging markers that differentiate between them when serologic testing is unavailable or ambiguous. We assessed whether imaging characteristics typical of MS discriminate RRMS from AQP4-NMOSD and MOGAD, alone and in combination. Methods: Adult, non-acute patients with RRMS, APQ4-NMOSD, MOGAD and healthy controls, were prospectively recruited at the National Hospital for Neurology and Neurosurgery (London, UK), and the Walton Centre (Liverpool, UK) between 2014 and 2019. They underwent conventional and advanced brain, cord and optic nerve MRI, and optical coherence tomography. Results: A total of 91 consecutive patients (31 RRMS, 30 APQ4-NMOSD, 30 MOGAD) and 34 healthy controls were recruited. The most accurate measures differentiating RRMS from AQP4-NMOSD were the proportion of lesions with the central vein sign (CVS) (84% vs. 33%, accuracy/specificity/sensitivity: 91/88/93%, p&lt;0.001), followed by cortical lesions (median: 2 [range: 1-14] vs. 1 [0-1], accuracy/specificity/sensitivity: 84/90/77%, p=0.002), and white matter lesions (mean: 39.07 [±25.8] vs. 9.5 [±14], accuracy/specificity/sensitivity: 78/84/73%, p=0.001). The combination of higher proportion of CVS, cortical lesions and optic nerve magnetization transfer ratio reached the highest accuracy in distinguishing RRMS from AQP4-NMOSD (accuracy/specificity/sensitivity: 95/92/97%, p&lt;0.001).The most accurate measures favouring RRMS over MOGAD were: white matter lesions (39.07 [±25.8] vs. 1 [±2.3], accuracy/specificity/sensitivity: 94/94/93%, p=0.006), followed by cortical lesions (2 [1-14] vs. 1 [0-1], accuracy/specificity/sensitivity: 84/97/71%, p=0.004), and retinal nerve fibre layer thickness (RNFL) (mean: 87.54 [±13.83] vs 75.54 [±20.33], accuracy/specificity/sensitivity: 80/79/81%, p=0.009). Higher cortical lesion number combined with higher RNFL thickness best differentiated RRMS from MOGAD (accuracy/specificity/sensitivity: 84/92/77%, p&lt;0.001). Discussion: Cortical lesions, CVS and optic nerve markers achieve a high accuracy in distinguishing RRMS from APQ4-NMOSD and MOGAD. This information may be useful in clinical practice, especially outside the acute phase and when serologic testing is ambiguous or not promptly available. Classification of evidence: This study provides Class II evidence that selected conventional and advanced brain, cord, and optic nerve MRI and OCT markers distinguish adult patients with RRMS from APQ4-NMOSD and MOGAD

Validation of the 2023 International Diagnostic Criteria for MOGAD in a Selected Cohort of Adults and Children

BACKGROUND AND OBJECTIVES: To test the performance of the 2023 myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) criteria in adults and children with inflammatory demyelinating conditions who were tested for MOG antibodies (Abs). // METHODS: This was a retrospective study of patients tested for MOG-Abs from 2018 to 2022 in 2 specialist hospitals. The inclusion criteria comprised ≥1 attendance in an adult or pediatric demyelinating disease clinic and complete clinical and MRI records. The final clinical diagnosis of MOGAD, made by the treating neurologist, was taken as the benchmark against which the new criteria were tested. The international MOGAD diagnostic criteria were applied retrospectively; they stipulate at least 1 clinical or MRI supporting feature for MOGAD diagnosis in positive fixed MOG cell-based assay without a titer. The performance MOG-Ab testing alone for MOGAD diagnosis was also assessed and compared with that of MOGAD criteria using the McNemar test. // RESULTS: Of the 1,879 patients tested for MOG-Abs, 539 (135 pediatric and 404 adults) met the inclusion criteria. A clinical diagnosis of MOGAD was made in 86/539 (16%) patients (37 adults, 49 children), with a median follow-up of 3.6 years. The MOGAD diagnostic criteria had sensitivity of 96.5% (adults 91.9%, children 100%), specificity of 98.9% (adults 98.8%, children 98.9%), positive predictive value of 94.3% (adults 89.4%, children 98%), negative predictive value of 99.3% (adults 99.2%, children 100%), and accuracy of 98.5% (adults 98.3%, children 99.2%). When compared with MOG-Ab testing alone, a difference was seen only in adults: a significantly higher specificity (98.9% vs 95.6%, p = 0.0005) and nonstatistically significant lower sensitivity (91.9% vs 100%, p = 0.08). // DISCUSSION: The international MOGAD diagnostic criteria exhibit high performance in selected patients with inflammatory demyelinating diseases (who had a high pretest probability of having MOGAD) compared with best clinical judgment; their performance was better in children than in adults. In adults, the MOGAD criteria led to an improvement in specificity and positive predictive value when compared with MOG-Ab testing alone, suggesting that the requirement of at least 1 clinical or MRI supporting feature is important. Future work should address the generalizability of the diagnostic criteria to cohorts of greater clinical diversity seen within neurologic settings

A multi-shell multi-tissue diffusion study of brain connectivity in early multiple sclerosis.

BACKGROUND: The potential of multi-shell diffusion imaging to produce accurate brain connectivity metrics able to unravel key pathophysiological processes in multiple sclerosis (MS) has scarcely been investigated. OBJECTIVE: To test, in patients with a clinically isolated syndrome (CIS), whether multi-shell imaging-derived connectivity metrics can differentiate patients from controls, correlate with clinical measures, and perform better than metrics obtained with conventional single-shell protocols. METHODS: Nineteen patients within 3 months from the CIS and 12 healthy controls underwent anatomical and 53-direction multi-shell diffusion-weighted 3T images. Patients were cognitively assessed. Voxel-wise fibre orientation distribution functions were estimated and used to obtain network metrics. These were also calculated using a conventional single-shell diffusion protocol. Through linear regression, we obtained effect sizes and standardised regression coefficients. RESULTS: Patients had lower mean nodal strength (p = 0.003) and greater network modularity than controls (p = 0.045). Greater modularity was associated with worse cognitive performance in patients, even after accounting for lesion load (p = 0.002). Multi-shell-derived metrics outperformed single-shell-derived ones. CONCLUSION: Connectivity-based nodal strength and network modularity are abnormal in the CIS. Furthermore, the increased network modularity observed in patients, indicating microstructural damage, is clinically relevant. Connectivity analyses based on multi-shell imaging can detect potentially relevant network changes in early MS

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

Real-world clinical experience with Idebenone in the treatment of Leber hereditary optic neuropathy

Background: Leber hereditary optic neuropathy (LHON) leads to bilateral central vision loss. In a clinical trial setting, idebenone has been shown to be safe and to provide a trend toward improved visual acuity, but long-term evidence of effectiveness in real-world clinical practice is sparse. Methods: Open-label, multicenter, retrospective, noncontrolled analysis of long-term visual acuity and safety in 111 LHON patients treated with idebenone (900 mg/day) in an expanded access program. Eligible patients had a confirmed mitochondrial DNA mutation and had experienced the onset of symptoms (most recent eye) within 1 year before enrollment. Data on visual acuity and adverse events were collected as per normal clinical practice. Efficacy was assessed as the proportion of patients with either a clinically relevant recovery (CRR) or a clinically relevant stabilization (CRS) of visual acuity. In the case of CRR, time to and magnitude of recovery over the course of time were also assessed. Results: At time of analysis, 87 patients had provided longitudinal efficacy data. Average treatment duration was 25.6 months. CRR was observed in 46.0% of patients. Analysis of treatment effect by duration showed that the proportion of patients with recovery and the magnitude of recovery increased with treatment duration. Average gain in best-corrected visual acuity for responders was 0.72 logarithm of the minimal angle of resolution (logMAR), equivalent to more than 7 lines on the Early Treatment Diabetic Retinopathy Study (ETDRS) chart. Furthermore, 50% of patients who had a visual acuity below 1.0 logMAR in at least one eye at initiation of treatment successfully maintained their vision below this threshold by last observation. Idebenone was well tolerated, with most adverse events classified as minor. Conclusions: These data demonstrate the benefit of idebenone treatment in recovering lost vision and maintaining good residual vision in a real-world setting. Together, these findings indicate that idebenone treatment should be initiated early and be maintained more than 24 months to maximize efficacy. Safety results were consistent with the known safety profile of idebenone