Investigation of pathophysiological mechanisms in clinically isolated syndrome using advanced imaging techniques

This thesis concerns an observational study of patients recruited after their first episode of neurological symptoms suggestive of demyelination in the central nervous system and diagnosed either with clinically isolated syndrome or relapsing-remitting multiple sclerosis. In multiple sclerosis, brain tissues can exhibit extensive neuroaxonal microstructural and metabolic abnormalities, but little is known about their presence and significance at the time of the first demyelinating episode. I used a novel multi-parametric quantitative MRI approach, combining neurite orientation dispersion and density imaging (NODDI), which gives information about tissue microstructure, and 23Na MRI, which estimates total sodium concentration, a marker of metabolic dysfunction, in the brains of clinically isolated syndrome patients. I found microstructural and sodium homeostasis alterations in cortical areas of patients that showed clinical relevance. Within the diffuse axonal dispersion found in the normal-appearing white matter, the corpus callosum shared with lesions, signs of axonal damage and metabolic dysfunction, thus emerging as a possible target for early neuroprotective interventions. Structural cortical networks (SCNs) represent patterns of coordinated morphological modifications in cortical areas and they have shown pathophysiological changes in many brain disorders, including multiple sclerosis. I investigated alterations of SCNs at the individual level in this early cohort. 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 indicating that pathophysiological changes in the cortical morphology can influence clinical outcomes. Finally, I hypothesised that the patients in the cohort presenting with optic neuritis may have disturbances in neuropsychological functions related to visual processes. I found that cognitive visuospatial processing is affected after unilateral optic neuritis and improves over time with visual recovery, independently of the structural damage in the visual and central nervous system

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

Comparison of Neurite Orientation Dispersion and Density Imaging and Two-Compartment Spherical Mean Technique Parameter Maps in Multiple Sclerosis

Microestructura; Esclerosi múltiple; Tècnica de mitjana esfèricaMicroestructura; Esclerosis múltiple; Técnica de la media esféricaMicrostructure; Multiple sclerosis; Spherical mean techniqueBackground: Neurite orientation dispersion and density imaging (NODDI) and the spherical mean technique (SMT) are diffusion MRI methods providing metrics with sensitivity to similar characteristics of white matter microstructure. There has been limited comparison of changes in NODDI and SMT parameters due to multiple sclerosis (MS) pathology in clinical settings. Purpose: To compare group-wise differences between healthy controls and MS patients in NODDI and SMT metrics, investigating associations with disability and correlations with diffusion tensor imaging (DTI) metrics. Methods: Sixty three relapsing-remitting MS patients were compared to 28 healthy controls. NODDI and SMT metrics corresponding to intracellular volume fraction (vin), orientation dispersion (ODI and ODE), diffusivity (D) (SMT only) and isotropic volume fraction (viso) (NODDI only) were calculated from diffusion MRI data, alongside DTI metrics (fractional anisotropy, FA; axial/mean/radial diffusivity, AD/MD/RD). Correlations between all pairs of MRI metrics were calculated in normal-appearing white matter (NAWM). Associations with expanded disability status scale (EDSS), controlling for age and gender, were evaluated. Patient-control differences were assessed voxel-by-voxel in MNI space controlling for age and gender at the 5% significance level, correcting for multiple comparisons. Spatial overlap of areas showing significant differences were compared using Dice coefficients. Results: NODDI and SMT show significant associations with EDSS (standardised beta coefficient −0.34 in NAWM and −0.37 in lesions for NODDI vin; 0.38 and −0.31 for SMT ODE and vin in lesions; p < 0.05). Significant correlations in NAWM are observed between DTI and NODDI/SMT metrics. NODDI vin and SMT vin strongly correlated (r = 0.72, p < 0.05), likewise NODDI ODI and SMT ODE (r = −0.80, p < 0.05). All DTI, NODDI and SMT metrics detect widespread differences between patients and controls in NAWM (12.57% and 11.90% of MNI brain mask for SMT and NODDI vin, Dice overlap of 0.42). Data Conclusion: SMT and NODDI detect significant differences in white matter microstructure between MS patients and controls, concurring on the direction of these changes, providing consistent descriptors of tissue microstructure that correlate with disability and show alterations beyond focal damage. Our study suggests that NODDI and SMT may play a role in monitoring MS in clinical trials and practice.This study has received funding under the European Union's Horizon 2020 research and innovation programme under grant agreement No. 634541 (CDS-QuaMRI) and 666992. This study has also received support from the Engineering and Physical Sciences Research Council (EPSRC R006032/1, M020533/1, G007748, I027084, N018702), Spinal Research (UK), Wings for Life (Austria), Craig H. Neilsen Foundation (USA) for INSPIRED and UK Multiple Sclerosis Society (grants 892/08 and 77/2017). This study was supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. FP was supported by a Guarantors of Brain post-doctoral non-clinical fellowship. AT was supported by an MRC grant (MR/S026088/1). EK was supported from the NIHR Great Ormond Street Hospital Biomedical Research Centre. FG was currently supported by the investigator-initiated PREdICT study at the Vall d'Hebron Institute of Oncology (Barcelona), funded by AstraZeneca and CRIS Cancer Foundation. AstraZeneca was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication

Role of brain perfusion SPECT with 99mTc HMPAO in the assessment of response to drug therapy in patients with autoimmune vasculitis: a prospective study

Abstract BACKGROUND: The diagnosis of vasculitis in the brain remains a quite difficult achievement. To the best of our knowledge, there is no imaging method reported in literature which is capable of reaching to a diagnosis of vasculitis with very high sensitivity. AIM: The aim of this study was to determine whether perfusion brain single photon emission computed tomography (SPECT) can be usefully employed in monitoring the treatment of vasculitis, allowing treating only potentially responder patients and avoiding the side effects on patients who do not respond. MATERIALS AND METHODS: Twenty patients (two males and 18 females) suffering from systemic lupus erythematosus (SLE; n = 5), Behcet's disease (BD; n = 5), undifferentiated vasculitis (UV; n = 5), and Sjogren's syndrome (SS; n = 5) were included in the study. All patients underwent a wide neurological anamnestic investigation, a complete objective neurological examination and SPECT of the brain with 99mTc-hexamethyl-propylene-aminoxime (HMPAO). The brain SPECT was then repeated after appropriate medical treatment. The neurological and neuropsychiatric follow-up was performed at 6 months after the start of the treatment. RESULTS: Overall, the differences between the scintigraphic results obtained after and before the medical treatment indicated a statistically significant increase of the cerebral perfusion (CP). In 19 out of 200 regions of interest (ROI) studied, the difference between pre- and post treatment percentages had negative sign, indicating a worsening of CP. This latter event has occurred six times (five in the same patients) in the UV, 10 times (eight in the same patients) in the SLE, never in BD, and three times (two in the same patient) in the SS. CONCLUSION: The reported results seem to indicate the possibility of identifying, by the means of a brain SPECT, responder and nonresponder (unchanged or worsened CP) patients, affected by autoimmune vasculitis, to the therapy

Diffusion-based structural connectivity patterns of multiple sclerosis phenotypes

BACKGROUND: We aimed to describe the severity of the changes in brain diffusion-based connectivity as multiple sclerosis (MS) progresses and the microstructural characteristics of these networks that are associated with distinct MS phenotypes. METHODS: Clinical information and brain MRIs were collected from 221 healthy individuals and 823 people with MS at 8 MAGNIMS centres. The patients were divided into four clinical phenotypes: clinically isolated syndrome, relapsing-remitting, secondary progressive and primary progressive. Advanced tractography methods were used to obtain connectivity matrices. Then, differences in whole-brain and nodal graph-derived measures, and in the fractional anisotropy of connections between groups were analysed. Support vector machine algorithms were used to classify groups. RESULTS: Clinically isolated syndrome and relapsing-remitting patients shared similar network changes relative to controls. However, most global and local network properties differed in secondary progressive patients compared with the other groups, with lower fractional anisotropy in most connections. Primary progressive participants had fewer differences in global and local graph measures compared with clinically isolated syndrome and relapsing-remitting patients, and reductions in fractional anisotropy were only evident for a few connections. The accuracy of support vector machine to discriminate patients from healthy controls based on connection was 81%, and ranged between 64% and 74% in distinguishing among the clinical phenotypes. CONCLUSIONS: In conclusion, brain connectivity is disrupted in MS and has differential patterns according to the phenotype. Secondary progressive is associated with more widespread changes in connectivity. Additionally, classification tasks can distinguish between MS types, with subcortical connections being the most important factor

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

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

Inteligencia artificial en esclerosis múltiple

La inteligencia artificial (IA) es la rama de la ciencia que tiene como objetivo crear algoritmos capaces de llevar a cabo tareas que normalmente requieren inteligencia humana. La medicina ha experimentado un notable aumento en las aplicaciones de la IA gracias a computadoras cada vez más potentes y a la aparición de grandes repositorios de datos. La esclerosis múltiple (EM) es una enfermedad autoinmune crónica que afecta al sistema nervioso central con una patogénesis compleja, un proceso diagnóstico desafiante y una alta variabilidad entre personas, en gran parte inexplicada. Las aplicaciones de la IA en la EM tienen un gran potencial para respaldar mejor el diagnóstico, encontrar marcadores pronósticos y ayudar a comprender los mecanismos de la enfermedad. Esta revisión tiene como objetivo resumir los avances recientes de la IA en la EM para ilustrar sus logros, limitaciones y direcciones futuras

Visual Function and Brief Cognitive Assessment for Multiple Sclerosis in Optic Neuritis Clinically Isolated Syndrome Patients

Background:In this study, we hypothesized that clinically isolated syndrome-optic neuritis patients may have disturbances in neuropsychological functions related to visual processes.Methods:Forty-two patients with optic neuritis within 3 months from onset and 13 healthy controls were assessed at baseline and 6 months with MRI (brain volumes, lesion load, and optic radiation lesion volume) and optical coherence tomography (OCT) (peripapillary retinal nerve fiber layer [RNFL], ganglion cell and inner plexiform layers [GCIPLs], and inner nuclear layer). Patients underwent the brief cognitive assessment for multiple sclerosis, high-contrast and low-contrast letter acuity, and color vision.Results:At baseline, patients had impaired visual function, had GCIPL thinning in both eyes, and performed below the normative average in the visual-related tests: Symbol Digit Modalities Test and Brief Visuospatial Memory Test-Revised (BVMT-R). Over time, improvement in visual function in the affected eye was predicted by baseline GCIPL (P = 0.015), RNFL decreased, and the BVMT-R improved (P = 0.001). Improvement in BVMT-R was associated with improvement in the high-contrast letter acuity of the affected eye (P = 0.03), independently of OCT and MRI metrics.Conclusion:Cognitive testing, assessed binocularly, of visuospatial processing is affected after unilateral optic neuritis and improves over time with visual recovery. This is not related to structural markers of the visual or central nervous system