Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning: The Brain-Predicted Disease Duration Gap.

BACKGROUND AND OBJECTIVES: Disentangling brain aging from disease-related neurodegeneration in patients with multiple sclerosis (PwMS) is increasingly topical. The brain-age paradigm offers a window into this problem but may miss disease-specific effects. In this study, we investigated whether a disease-specific model might complement the brain-age gap (BAG) by capturing aspects unique to MS. METHODS: In this retrospective study, we collected 3D T1-weighted brain MRI scans of PwMS to build (1) a cross-sectional multicentric cohort for age and disease duration (DD) modeling and (2) a longitudinal single-center cohort of patients with early MS as a clinical use case. We trained and evaluated a 3D DenseNet architecture to predict DD from minimally preprocessed images while age predictions were obtained with the DeepBrainNet model. The brain-predicted DD gap (the difference between predicted and actual duration) was proposed as a DD-adjusted global measure of MS-specific brain damage. Model predictions were scrutinized to assess the influence of lesions and brain volumes while the DD gap was biologically and clinically validated within a linear model framework assessing its relationship with BAG and physical disability measured with the Expanded Disability Status Scale (EDSS). RESULTS: We gathered MRI scans of 4,392 PwMS (69.7% female, age: 42.8 ± 10.6 years, DD: 11.4 ± 9.3 years) from 15 centers while the early MS cohort included 749 sessions from 252 patients (64.7% female, age: 34.5 ± 8.3 years, DD: 0.7 ± 1.2 years). Our model predicted DD better than chance (mean absolute error = 5.63 years, R2 = 0.34) and was nearly orthogonal to the brain-age model (correlation between DD and BAGs: r = 0.06 [0.00-0.13], p = 0.07). Predictions were influenced by distributed variations in brain volume and, unlike brain-predicted age, were sensitive to MS lesions (difference between unfilled and filled scans: 0.55 years [0.51-0.59], p < 0.001). DD gap significantly explained EDSS changes (B = 0.060 [0.038-0.082], p < 0.001), adding to BAG (ΔR2 = 0.012, p < 0.001). Longitudinally, increasing DD gap was associated with greater annualized EDSS change (r = 0.50 [0.39-0.60], p < 0.001), with an incremental contribution in explaining disability worsening compared with changes in BAG alone (ΔR2 = 0.064, p < 0.001). DISCUSSION: The brain-predicted DD gap is sensitive to MS-related lesions and brain atrophy, adds to the brain-age paradigm in explaining physical disability both cross-sectionally and longitudinally, and may be used as an MS-specific biomarker of disease severity and progression.

Improving criteria for dissemination in space in multiple sclerosis by including additional regions.

OBJECTIVE: We investigated the effects of adding regions to current dissemination in space (DIS) criteria for multiple sclerosis (MS). METHODS: Participants underwent brain, optic nerve, and spinal cord MRI. Baseline DIS was assessed by 2017 McDonald criteria and versions including optic nerve, temporal lobe, or corpus callosum as a fifth region (requiring 2/5), a version with all regions (requiring 3/7) and optic nerve variations requiring 3/5 and 4/5 regions. Performance was evaluated against MS diagnosis (2017 McDonald criteria) during follow-up. RESULTS: Eighty-four participants were recruited (53F, 32.8 ± 7.1 years). 2017 McDonald DIS criteria were 87% sensitive (95% CI: 76-94), 73% specific (50-89), and 83% accurate (74-91) in identifying MS. Modified criteria with optic nerve improved sensitivity to 98% (91-100), with specificity 33% (13-59) and accuracy 84% (74-91). Criteria including temporal lobe showed sensitivity 94% (84-98), specificity 50% (28-72), and accuracy 82% (72-90); criteria including corpus callosum showed sensitivity 90% (80-96), specificity 68% (45-86), and accuracy 85% (75-91). Criteria adding all three regions (3/7 required) had sensitivity 95% (87-99), specificity 55% (32-76), and accuracy 85% (75-91). When requiring 3/5 regions (optic nerve as the fifth), sensitivity was 82% (70-91), specificity 77% (55-92), and accuracy 81% (71-89); with 4/5 regions, sensitivity was 56% (43-69), specificity 95% (77-100), and accuracy 67% (56-77). INTERPRETATION: Optic nerve inclusion increased sensitivity while lowering specificity. Increasing required regions in optic nerve criteria increased specificity and decreased sensitivity. Results suggest considering the optic nerve for DIS. An option of 3/5 or 4/5 regions preserved specificity, and criteria adding all three regions had highest accuracy.

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) (ß = 74.9, p = 0.026) scores. Faster timed 25-foot walk (T25FW) was associated with higher assortativity (ß = 5.39, p = 0.026), local efficiency (ß = 27.1, p = 0.041) and clustering (ß = 36.1, p = 0.032) and lower small-worldness (ß = -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.

Advanced central nervous system imaging biomarkers in radiologically isolated syndrome: a mini review.

Radiologically isolated syndrome is characterised by central nervous system white-matter hyperintensities highly suggestive of multiple sclerosis in individuals without a neurological history of clinical demyelinating episodes. It probably represents the pre-symptomatic phase of clinical multiple sclerosis but is poorly understood. This mini review summarises our current knowledge regarding advanced imaging techniques in radiologically isolated syndrome that provide insights into its pathobiology and prognosis. The imaging covered will include magnetic resonance imaging-derived markers of central nervous system volumetrics, connectivity, and the central vein sign, alongside optical coherence tomography-related metrics.

First-line immunosuppression in neuromuscular diseases.

Autoimmune neuromuscular diseases are common and often treatable causes for peripheral nervous system dysfunction. If not optimally managed, they result in meaningful impairments and disability. The treating neurologist should aim to maximise clinical recovery with minimal iatrogenic risk. This requires careful patient and medication selection, appropriate counselling and close monitoring of clinical efficacy and safety. Here, we summarise our consensus departmental approach to first-line immunosuppression in neuromuscular diseases. We combine multispecialty evidence and expertise with a focus on autoimmune neuromuscular diseases to create guidance on starting, dosing and monitoring for toxic effects of the commonly used drugs. These include corticosteroids, steroid-sparing agents and cyclophosphamide. We also provide efficacy monitoring advice, as clinical response informs dosage and drug choice. The principles of this approach could be applied across much of the spectrum of immune-mediated neurological disorders where there is significant therapeutic crossover.

Using The Virtual Brain to study the relationship between structural and functional connectivity in patients with multiple sclerosis: a multicenter study.

The relationship between structural connectivity (SC) and functional connectivity (FC) captured from magnetic resonance imaging, as well as its interaction with disability and cognitive impairment, is not well understood in people with multiple sclerosis (pwMS). The Virtual Brain (TVB) is an open-source brain simulator for creating personalized brain models using SC and FC. The aim of this study was to explore SC-FC relationship in MS using TVB. Two different model regimes have been studied: stable and oscillatory, with the latter including conduction delays in the brain. The models were applied to 513 pwMS and 208 healthy controls (HC) from 7 different centers. Models were analyzed using structural damage, global diffusion properties, clinical disability, cognitive scores, and graph-derived metrics from both simulated and empirical FC. For the stable model, higher SC-FC coupling was associated with pwMS with low Single Digit Modalities Test (SDMT) score (F=3.48, P$\lt$0.05), suggesting that cognitive impairment in pwMS is associated with a higher SC-FC coupling. Differences in entropy of the simulated FC between HC, high and low SDMT groups (F=31.57, P$\lt$1e-5), show that the model captures subtle differences not detected in the empirical FC, suggesting the existence of compensatory and maladaptive mechanisms between SC and FC in MS.

Sarcoidosis and neuromyelitis optica in a patient with optic neuritis - a case report.

We present a case of atypical recurrent optic neuritis. A man in his 50s presented with right optic neuritis and profound visual loss, associated with elevated inflammatory markers. Lymph-node biopsy was consistent with sarcoidosis. Aquaporin-4 antibodies were also present. Three months following corticosteroid treatment, his right optic neuritis relapsed, again with raised inflammatory markers. He was started on azathioprine and prednisolone with good effect. A dual diagnosis of sarcoidosis and neuromyelitis optica with aquaporin-4 antibodies is very rare. Long-term immunosuppression is required. The case highlights the importance of identifying the features and cause of atypical optic neuritis.