scholarly journals Contrasting the brain imaging features of MOG-Antibody disease, with AQP4-Antibody NMOSD and Multiple Sclerosis

2020 ◽  
Author(s):  
Silvia Messina ◽  
Romina Mariano ◽  
Adriana Roca-Fernandez ◽  
Ana Cavey ◽  
Maciej Jurynczyk ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Visual Acuity ◽  
White Matter ◽  
Grey Matter ◽  
Optic Chiasm ◽  
Lesion Volume ◽  
Imaging Features ◽  
Conventional Imaging ◽  
Cortical Lesions ◽  
Deep Grey Matter

Neuromyelitis optica associated with aquaporin-4-antibodies (NMOSD-AQP4) and myelin oligodentrocyte-glycoprotein antibody-associated disorder (MOGAD) have been recently recognised as different from multiple sclerosis. Although conventional MRI may help distinguish multiple sclerosis from antibody-mediated diseases, the use of quantitative and non-conventional imaging may give more pathological information and explain the clinical differences. We compared, using non-conventional imaging, brain MRI findings in 75 subjects in remission with NMOSD-AQP4, MOGAD, multiple sclerosis or healthy controls (HC). Volumetrics, white matter and cortical lesions, and tissue integrity measures using diffusion imaging, were analysed in the four groups along with their association with disability (expanded disability status scale [EDSS] and visual acuity). The volumetric analysis showed that, deep grey matter volumes were significantly lower in multiple sclerosis (p=0.0001) and MOGAD (p=0.02), compared to HC. Relapsing MOGAD had lower white matter, pallidus and hippocampus volumes than in monophasic (p<0.05). Optic chiasm volume was reduced only in NMOSD-AQP4 who had at least one episode of optic neuritis (ON) (NMOSD-AQP4-ON vs NMOSD-AQP4 p<0.001, HC p<0.001, MOGAD-ON p=0.04, multiple sclerosis-ON p=0.02) likely reflecting the recognised posterior location of NMOSD-AQP4-ON and its severity. Lesion volume was greatest in multiple sclerosis followed by MOGAD and in these two diseases, the lesion volume correlated with disease duration (multiple sclerosis R=0.46, p=0.05, MOGAD R=0.81, p<0.001), cortical thickness (multiple sclerosis R=-0.64, p=0.0042, MOGAD=-0.71, p=0.005) and deep grey matter volumes (multiple sclerosis R=-0.65, p=0.0034, MOGAD R=-0.93, p<0.001). Lesional-fractional anisotropy (FA) was reduced and mean diffusivity increased in all patients, but overall, FA was only reduced in the non-lesional tissue in multiple sclerosis (p=0.01), although focal reductions were noted in NMOSD-AQP4, reflecting mainly optic nerve and corticospinal tract pathways. Cortical/juxtacortical lesions were seen in a minority of MOGAD, while cortical/juxtacortical and purely cortical lesions were identified in the majority of multiple sclerosis and in none of the NMOSD-AQP4. Non-lesional FA in NMOSD-AQP4, lower white-matter volume and female sex in multiple sclerosis, and lower brainstem volume in MOGAD were the best predictors of EDSS disability (accounting for 46%, 49% and 19% respectively). Worse visual acuity associated with lower optic chiasm volume in NMOSD-AQP4 and lower thalamus volume in MOGAD (accounting for 58% and 35% respectively). Although MOGAD patients had good outcomes, deep grey matter atrophy was present. In contrast, NMOSD-AQP4 patients showed a relative sparing of deep grey matter volumes, despite greater residual disability as compared with MOGAD patients. NMOSD-AQP4 but not MOGAD patients showed reduced FA in non-lesional tissue.

Microstructural magnetic resonance imaging of cortical lesions in multiple sclerosis

2012 ◽  
Vol 19 (4) ◽  
pp. 418-426 ◽  
Author(s):  
M Filippi ◽  
P Preziosa ◽  
E Pagani ◽  
M Copetti ◽  
S Mesaros ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
White Matter ◽  
Magnetic Resonance ◽  
Diffusion Tensor ◽  
Neuronal Damage ◽  
Lesion Volume ◽  
Imaging Features ◽  
Cortical Lesions ◽  
Resonance Imaging

Background: Pathologic and magnetic resonance imaging (MRI) studies have shown that cortical lesions (CLs) are a frequent finding in multiple sclerosis (MS). Objective: To quantify microstructural damage in CLs and normal appearing (NA) cortex in relapse-onset MS patients at different stages of the disease. Methods: Brain double inversion recovery (DIR), diffusion tensor (DT) MRI and 3D T1-weighted scans were acquired from 35 relapsing–remitting (RR) patients, 23 secondary progressive (SP) patients, 12 benign (B) MS patients and 41 healthy controls (HC). Diffusivity values in CLs, cortex, white matter (WM) lesions and normal-appearing white matter (NAWM) were assessed. Results: Compared to HC, MS patients had a significantly lower fractional anisotropy (FA) and higher mean diffusivity (MD) in the cortex and NAWM. CLs had higher FA vs HC cortex and vs patients’ cortex. Compared to RRMS patients, SPMS patients had higher WM lesion volume, higher MD in the cortex, and more severe damage to the NAWM and WM lesions. Compared to SPMS patients, BMS patients had lower MD and FA of CLs. Damage in other compartments was similar between SPMS and BMS patients. Damage in CLs had a high power to discriminate BMS from SPMS (area under the curve: 79–91%), with high specificity (85%), sensitivity (100%) and accuracy (90%). Conclusions: Microstructural imaging features of CLs differ from those of WM lesions and are likely to reflect neuronal damage and microglial activation. The nature and extent of CL damage can be used to help distinguish the different MS clinical phenotypes.

scholarly journals Contrasting the brain imaging features of MOG-antibody disease, with AQP4-antibody NMOSD and multiple sclerosis

2021 ◽  
pp. 135245852110189
Author(s):  
Silvia Messina ◽  
Romina Mariano ◽  
Adriana Roca-Fernandez ◽  
Ana Cavey ◽  
Maciej Jurynczyk ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Grey Matter ◽  
Diffusion Imaging ◽  
White Matter Lesions ◽  
Lesion Volume ◽  
Imaging Features ◽  
Strongly Correlated ◽  
Deep Grey Matter ◽  
Magnetic Resonance Imaging Mri ◽  
Aqp4 Antibody

Background: Identifying magnetic resonance imaging (MRI) markers in myelin-oligodendrocytes-glycoprotein antibody-associated disease (MOGAD), neuromyelitis optica spectrum disorder-aquaporin-4 positive (NMOSD-AQP4) and multiple sclerosis (MS) is essential for establishing objective outcome measures. Objectives: To quantify imaging patterns of central nervous system (CNS) damage in MOGAD during the remission stage, and to compare it with NMOSD-AQP4 and MS. Methods: 20 MOGAD, 19 NMOSD-AQP4, 18 MS in remission with brain or spinal cord involvement and 18 healthy controls (HC) were recruited. Volumetrics, lesions and cortical lesions, diffusion-imaging measures, were analysed. Results: Deep grey matter volumes were lower in MOGAD ( p = 0.02) and MS ( p = 0.0001), compared to HC and were strongly correlated with current lesion volume (MOGAD R = −0.93, p < 0.001, MS R = −0.65, p = 0.0034). Cortical/juxtacortical lesions were seen in a minority of MOGAD, in a majority of MS and in none of NMOSD-AQP4. Non-lesional tissue fractional anisotropy (FA) was only reduced in MS ( p = 0.01), although focal reductions were noted in NMOSD-AQP4, reflecting mainly optic nerve and corticospinal tract pathways. Conclusion: MOGAD patients are left with grey matter damage, and this may be related to persistent white matter lesions. NMOSD-AQP4 patients showed a relative sparing of deep grey matter volumes, but reduced non-lesional tissue FA. Observations from our study can be used to identify new markers of damage for future multicentre studies.

Multi-parametric structural magnetic resonance imaging in relation to cognitive dysfunction in long-standing multiple sclerosis

2015 ◽  
Vol 22 (5) ◽  
pp. 608-619 ◽  
Author(s):  
Marita Daams ◽  
Martijn D Steenwijk ◽  
Menno M Schoonheim ◽  
Mike P Wattjes ◽  
Lisanne J Balk ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Cognitive Dysfunction ◽  
Cognitive Deficits ◽  
Grey Matter ◽  
White Matter Damage ◽  
Diffuse White Matter ◽  
Brain White Matter ◽  
Deep Grey Matter ◽  
Imaging Markers

Background: Cognitive deficits are common in multiple sclerosis. Most previous studies investigating the imaging substrate of cognitive deficits in multiple sclerosis included patients with relatively short disease durations and were limited to one modality/brain region. Objective: To identify the strongest neuroimaging predictors for cognitive dysfunction in a large cohort of patients with long-standing multiple sclerosis. Methods: Extensive neuropsychological testing and multimodal 3.0T MRI was performed in 202 patients with multiple sclerosis and 52 controls. Cognitive scores were compared between groups using Z-scores. Whole-brain, white matter, grey matter, deep grey matter and lesion volumes; cortical thickness, (juxta)cortical and cerebellar lesions; and extent and severity of diffuse white matter damage were measured. Stepwise linear regression was used to identify the strongest predictors for cognitive dysfunction. Results: All cognitive domains were affected in patients. Patients showed extensive atrophy, focal pathology and damage in up to 75% of the investigated white matter. Associations between imaging markers and average cognition were two times stronger in cognitively impaired patients than in cognitively preserved patients. The final model for average cognition consisted of deep grey matter DGMV volume and fractional anisotropy severity (adjusted R²=0.490; p<0.001). Conclusion: From all imaging markers, deep grey matter atrophy and diffuse white matter damage emerged as the strongest predictors for cognitive dysfunction in long-standing multiple sclerosis.

Different white matter lesion characteristics correlate with distinct grey matter abnormalities on magnetic resonance imaging in secondary progressive multiple sclerosis

2009 ◽  
Vol 15 (6) ◽  
pp. 687-694 ◽  
Author(s):  
J Furby ◽  
T Hayton ◽  
D Altmann ◽  
R Brenner ◽  
J Chataway ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Grey Matter ◽  
Progressive Multiple Sclerosis ◽  
Secondary Progressive Multiple Sclerosis ◽  
Lesion Volume ◽  
Secondary Degeneration ◽  
Secondary Progressive ◽  
Demyelinating Lesions ◽  
The Relationship

Background Although MRI measures of grey matter abnormality correlate with clinical disability in multiple sclerosis, it is uncertain whether grey matter abnormality measured on MRI is entirely due to a primary grey matter process or whether it is partly related to disease in the white matter. Methods To explore potential mechanisms of grey matter damage we assessed the relationship of white matter T2 lesion volume, T1 lesion volume, and mean lesion magnetisation transfer ratio (MTR), with MRI measures of tissue atrophy and MTR in the grey matter in 117 subjects with secondary progressive multiple sclerosis. Results Grey matter fraction and mean grey matter MTR were strongly associated with lesion volumes and lesion MTR mean ( r = ±0.63–0.72). In contrast, only weak to moderate correlations existed between white matter and lesion measures. In a stepwise regression model, T1 lesion volume was the only independent lesion correlate of grey matter fraction and accounted for 52% of the variance. Lesion MTR mean and T2 lesion volume were independent correlates of mean grey matter MTR, accounting for 57% of the variance. Conclusions Axonal transection within lesions with secondary degeneration into the grey matter may explain the relationship between T1 lesions and grey matter fraction. A parallel accumulation of demyelinating lesions in white and grey matter may contribute to the association of T2 lesion volume and lesion MTR with grey matter MTR.

scholarly journals Quantitative MRI phenotypes capture biological heterogeneity in multiple sclerosis patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ide Smets ◽  
An Goris ◽  
Marijne Vandebergh ◽  
Jelle Demeestere ◽  
Stefan Sunaert ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Risk Score ◽  
Grey Matter ◽  
Quantitative Mri ◽  
Grey Matter Volume ◽  
Magnetization Transfer Ratio ◽  
Lesion Volume ◽  
Total Brain ◽  
Multiple Sclerosis Patients

AbstractMagnetization transfer ratio (MTR) and brain volumetric imaging are (semi-)quantitative MRI markers capturing demyelination, axonal degeneration and/or inflammation. However, factors shaping variation in these traits are largely unknown. In this study, we collected a longitudinal cohort of 33 multiple sclerosis (MS) patients and extended it cross-sectionally to 213. We measured MTR in lesions, normal-appearing white matter (NAWM), normal-appearing grey matter (NAGM) and total brain, grey matter, white matter and lesion volume. We also calculated the polygenic MS risk score. Longitudinally, inter-patient differences at inclusion and intra-patient changes during follow-up together explained > 70% of variance in MRI, with inter-patient differences at inclusion being the predominant source of variance. Cross-sectionally, we observed a moderate correlation of MTR between NAGM and NAWM and, less pronounced, with lesions. Age and gender explained about 30% of variance in total brain and grey matter volume. However, they contributed less than 10% to variance in MTR measures. There were no significant associations between MRI traits and the genetic risk score. In conclusion, (semi-)quantitative MRI traits change with ongoing disease activity but this change is modest in comparison to pre-existing inter-patient differences. These traits reflect individual variation in biological processes, which appear different from those involved in genetic MS susceptibility.

scholarly journals Automated quantification of deep grey matter structures and white matter lesions using magnetic resonance imaging in relapsing remission multiple sclerosis

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Mina Rizkallah ◽  
Mohamed Hefida ◽  
Mohamed Khalil ◽  
Rasha Mahmoud Dawoud
Keyword(s):  
Multiple Sclerosis ◽  
Statistical Analysis ◽  
White Matter ◽  
Grey Matter ◽  
Brain Volume ◽  
Correlation Coefficients ◽  
White Matter Lesions ◽  
The Other ◽  
Automated Segmentation ◽  
Deep Grey Matter

Abstract Background Brain volume loss (BVL) is widespread in MS and occurs throughout the disease course at a rate considerably greater than in the general population. In MS, brain volume correlates with and predicts future disability, making BVL a relevant measure of diffuse CNS damage leading to clinical disease progression, as well as serving as a useful outcome in evaluating MS therapies. The aim of our study was to evaluate the role of automated segmentation and quantification of deep grey matter structures and white matter lesions in Relapsing Remitting Multiple Sclerosis patients using MR images and to correlate the volumetric results with different degrees of disability based on expanded disability status scale (EDSS) scores. Results All the patients in our study showed relative atrophy of the thalamus and the putamen bilaterally when compared with the normal control group. Statistical analysis was significant for the thalamus and the putamen atrophy (P value < 0.05). On the other hand, statistical analysis was not significant for the caudate and the hippocampus (P value > 0.05); there was a significant positive correlation between the white matter lesions volume and EDSS scores (correlation coefficient of 0.7505). On the other hand, there was a significant negative correlation between the thalamus and putamen volumes, and EDSS scores (correlation coefficients < − 0.9), while the volumes of the caudate and the hippocampus had a very weak and non-significant correlation with the EDSS scores (correlation coefficients > − 0.35). Conclusions The automated segmentation and quantification tools have a great role in the assessment of brain structural changes in RRMS patients, and that it became essential to integrate these tools in the daily medical practice for the great value they add to the current evaluation measures.

scholarly journals Reduced accuracy of MRI deep grey matter segmentation in multiple sclerosis: an evaluation of four automated methods against manual reference segmentations in a multi-center cohort

2020 ◽  
Vol 267 (12) ◽  
pp. 3541-3554 ◽  
Author(s):  
Alexandra de Sitter ◽  
◽  
Tom Verhoeven ◽  
Jessica Burggraaff ◽  
Yaou Liu ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Grey Matter ◽  
Majority Voting ◽  
Dice Similarity Coefficient ◽  
Lesion Volume ◽  
Impaired Performance ◽  
Segmentation Methods ◽  
Deep Grey Matter ◽  
Global And Local ◽  
Automated Methods

Abstract Background Deep grey matter (DGM) atrophy in multiple sclerosis (MS) and its relation to cognitive and clinical decline requires accurate measurements. MS pathology may deteriorate the performance of automated segmentation methods. Accuracy of DGM segmentation methods is compared between MS and controls, and the relation of performance with lesions and atrophy is studied. Methods On images of 21 MS subjects and 11 controls, three raters manually outlined caudate nucleus, putamen and thalamus; outlines were combined by majority voting. FSL-FIRST, FreeSurfer, Geodesic Information Flow and volBrain were evaluated. Performance was evaluated volumetrically (intra-class correlation coefficient (ICC)) and spatially (Dice similarity coefficient (DSC)). Spearman's correlations of DSC with global and local lesion volume, structure of interest volume (ROIV), and normalized brain volume (NBV) were assessed. Results ICC with manual volumes was mostly good and spatial agreement was high. MS exhibited significantly lower DSC than controls for thalamus and putamen. For some combinations of structure and method, DSC correlated negatively with lesion volume or positively with NBV or ROIV. Lesion-filling did not substantially change segmentations. Conclusions Automated methods have impaired performance in patients. Performance generally deteriorated with higher lesion volume and lower NBV and ROIV, suggesting that these may contribute to the impaired performance.

Deep grey matter T2 hypo-intensity in patients with paediatric multiple sclerosis

2011 ◽  
Vol 17 (6) ◽  
pp. 702-707 ◽  
Author(s):  
Antonia Ceccarelli ◽  
Maria A Rocca ◽  
Elisabetta Perego ◽  
Lucia Moiola ◽  
Angelo Ghezzi ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Caudate Nucleus ◽  
Grey Matter ◽  
Lesion Volume ◽  
Longitudinal Assessment ◽  
Paediatric Patients ◽  
Relapsing Remitting ◽  
Left Caudate ◽  
Deep Grey Matter ◽  
Dual Echo

Objective: T2 hypo-intensity on magnetic resonance imaging scans is thought to reflect pathological iron deposition in the presence of disease. In this pilot study, we evaluated the utility of the quantification of T2 hypo-intensities in paediatric patients by estimating deep grey matter (DGM) T2 hypo-intensities in paediatric patients with multiple sclerosis (MS) or clinically isolated syndromes (CIS), and their changes over 1 year. Methods: A dual-echo sequence was obtained from 45 paediatric patients (10 with CIS, 35 with relapsing–remitting MS, 8 with an onset of the disease before the age of 10 and 37 during adolescence) and 14 age-matched healthy controls (HC). Eleven patients were reassessed both clinically and with MRI after 1 year. Normalized T2 intensity in the basal ganglia and thalamus was quantified. Results: At baseline, DGM T2 intensity was similar between paediatric patients and HC in all the structures analysed, except for the head of the left caudate nucleus ( p = 0.001). DGM T2 intensity of the head of the left caudate nucleus was similar between paediatric CIS and RRMS patients, but it was reduced in adolescent-onset paediatric patients versus HC ( p = 0.002). In all patients, DGM T2 intensity of the head of the left caudate nucleus was correlated with T2 lesion volume ( r = −0.39, p = 0.007). DGM T2 intensity in all the structures analysed with longitudinal assessment remained stable over the follow-up in the cohort of patients. Conclusions: The quantification of DGM T2 intensity in paediatric patients may provide surrogate markers of neurodegeneration. In paediatric MS, DGM is likely to be affected by iron-related changes, which are likely to be, at least partially, secondary to WM damage.

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