Multiple Sclerosis Lesions Research Articles

Immunomodulatory therapy with glatiramer acetate reduces endoplasmic reticulum stress and mitochondrial dysfunction in experimental autoimmune encephalomyelitis

Endoplasmic reticulum (ER) stress and mitochondrial dysfunction are found in lesions of multiple sclerosis (MS) and animal models of MS such as experimental autoimmune encephalomyelitis (EAE), and may contribute to the neuronal loss that underlies permanent impairment. We investigated whether glatiramer acetate (GA) can reduce these changes in the spinal cords of chronic EAE mice by using routine histology, immunostaining, and electron microscopy. EAE spinal cord tissue exhibited increased inflammation, demyelination, mitochondrial dysfunction, ER stress, downregulation of NAD+ dependent pathways, and increased neuronal death. GA reversed these pathological changes, suggesting that immunomodulating therapy can indirectly induce neuroprotective effects in the CNS by mediating ER stress.

Retinal Periphlebitis May Be a Marker for Subphenotype in Multiple Sclerosis

Retinal periphlebitis (RPP) is a long-known entity in patients with multiple sclerosis (MS) and has not been revisited in the context of recent developments in MS pathogenesis and heterogeneity. We present six cases of RPP in three female and three male MS patients. They all have relapsing-remitting MS and did not have or had minor ocular symptoms. It is important to perform a thorough retinal examination in patients with MS, as peripheral and sectorial lesions could be unseen. A better knowledge on the concomitant involvement of retinal veins contributes to the understanding of immunopathology, with potentially distinct autoantigenic targets. RPP might serve as a subphenotype marker that may influence treatment choices in MS. Further research is needed.

Edges-enhanced Convolutional Neural Network for Multiple Sclerosis Lesions Segmentation

Edges-enhanced Convolutional Neural Network for Multiple Sclerosis Lesions Segmentation

Oral Cladribine Impairs Intermediate, but Not Conventional, Monocyte Transmigration in Multiple Sclerosis Patients across a Model Blood-Brain Barrier.

Multiple sclerosis (MS) is a disease in which the immune system damages components of the central nervous system (CNS), leading to the destruction of myelin and the formation of demyelinating plaques. This often occurs in episodic "attacks" precipitated by the transmigration of leukocytes across the blood-brain barrier (BBB), and repeated episodes of demyelination lead to substantial losses of axons within and removed from plaques, ultimately leading to progressive neurological dysfunction. Within leukocyte populations, macrophages and T and B lymphocytes are the predominant effectors. Among current immunotherapies, oral cladribine's impact on lymphocytes is well characterised, but little is known about its impact on other leukocytes such as monocytes and dendritic cells (DCs). The aim of this study was to determine the transmigratory ability of monocyte and DC subsets in healthy subjects and untreated and cladribine-treated relapse-remitting MS (RRMS) patients using a well-characterised model of the BBB. Peripheral blood mononuclear cells from subjects were added to an in vitro transmigration assay to assess cell migration. Our findings show that while prior treatment with oral cladribine inhibits the migration of intermediate monocytes, it has no impact on the transmigration of DC subsets. Overall, our data indicate a previously unrecognised role of cladribine on intermediate monocytes, known to accumulate in the brain active MS lesions.

Double inversion recovery to detect cervical spinal cord multiple sclerosis lesions.

Magnetic resonance imaging (MRI) plays a key role in diagnosing and monitoring multiple sclerosis (MS). Double inversion recovery (DIR) is a pulse sequence that has proven highly effective at detecting cortical lesions but is understudied in the spinal cord. We hypothesize that DIR images obtained during brain MRI can be of value in assessing the upper spinal cord of MS patients. We retrospectively examined brain MRI exams of 64 patients with established MS, who had also undergone cervical spine MRI. Two blinded MS expert readers, who assessed the scans for lesion numbers and rated lesion visibility and overall image quality, reviewed brain 3-dimensional DIR sagittal and coronal images. Standardized mean contrast-to-noise ratios (C/N) and standard deviation (SD) were calculated in representative lesions for each patient and compared to those of 3-dimensional FLAIR images. For the analysis of lesions categorized as "definite lesions," the sensitivity was 87%, specificity was 61%, and negative predictive value was 80%. On the other hand, for "definite" plus "probable" lesions, the sensitivity was 91%, the specificity was 54%, and negative predictive value was 86%. DIR demonstrated lesions with an average C/N of 7.56 with an SD of 1.77. FLAIR sequence demonstrated lesions with an average C/N of 0.67 and SD of 1.27. Sagittally acquired brain DIR can provide useful information on upper spinal cord lesions, with high C/N. In theory, this should facilitate the attainment of McDonald's or the Magnetic Resonance Imaging in MS (MAGNIMS) criteria in some cases, without a dedicated cervical spine MRI exam.

The signal intensity variation of multiple sclerosis (MS) lesions on magnetic resonance imaging (MRI) as a potential biomarker for patients' disability: A feasibility study.

Although many lesion-based MRI biomarkers in multiple sclerosis (MS) patients were investigated, none of the previous studies dealt with the signal intensity variations (SIVs) of MS lesions. In this study, the SIVs of MS lesions on direct myelin imaging and standard clinical sequences as possible MRI biomarkers for disability in MS patients were assessed. Twenty seven MS patients were included in this prospective study. IR-UTE, FLAIR, and MPRAGE sequences were employed on a 3T scanner. Regions of interest (ROIs) were manually drawn within the MS lesions, and the cerebrospinal fluid (CSF) and signal intensity ratios (SIR) were calculated from the derived values. Variations coefficients were determined from the standard deviations (Coeff 1) and the absolute differences (Coeff 2) of the SIRs. Disability grade was assessed by the expanded disability status scale (EDSS). Cortical/gray matter, subcortical, infratentorial, and spinal lesions were excluded. The mean diameter of the lesions was 7.8 ± 1.97 mm, while the mean EDSS score was 4.5 ± 1.73. We found moderate correlations between the EDSS and Coeff 1 and 2 on IR-UTE and MPRAGE images. Accordingly, Pearson's correlations on IR-UTE were R = 0.51 (p = 0.007) and R = 0.49 (p = 0.01) for Coeff 1 and 2, respectively. For MPRAGE, Pearson's correlations were R = 0.5 (p = 0.008) and R = 0.48 (p = 0.012) for Coeff 1 and 2, respectively. For FLAIR, only poor correlations could be found. The SIVs of MS lesions on IR-UTE and MPRAGE images, assessed by Coeff 1 and 2, could be used as novel potential MRI biomarkers for patients' disability.

Multi-arm U-Net with dense input and skip connectivity for T2 lesion segmentation in clinical trials of multiple sclerosis

T2 lesion quantification plays a crucial role in monitoring disease progression and evaluating treatment response in multiple sclerosis (MS). We developed a 3D, multi-arm U-Net for T2 lesion segmentation, which was trained on a large, multicenter clinical trial dataset of relapsing MS. We investigated its generalization to other relapsing and primary progressive MS clinical trial datasets, and to an external dataset from the MICCAI 2016 MS lesion segmentation challenge. Additionally, we assessed the model’s ability to reproduce the separation of T2 lesion volumes between treatment and control arms; and the association of baseline T2 lesion volumes with clinical disability scores compared with manual lesion annotations. The trained model achieved a mean dice coefficient of ≥ 0.66 and a lesion detection sensitivity of ≥ 0.72 across the internal test datasets. On the external test dataset, the model achieved a mean dice coefficient of 0.62, which is comparable to 0.59 from the best model in the challenge, and a lesion detection sensitivity of 0.68. Lesion detection performance was reduced for smaller lesions (≤ 30 μL, 3–10 voxels). The model successfully maintained the separation of the longitudinal changes in T2 lesion volumes between the treatment and control arms. Such tools could facilitate semi-automated MS lesion quantification; and reduce rater burden in clinical trials.

Comparison of OX40 expression in patients with multiple sclerosis and neuromyelitis optica as an approach to diagnosis

BackgroundPrevious studies have shown that CD134 (OX40) co-stimulation is involved in the pathogenesis of experimental autoimmune encephalomyelitis (EAE) models and the antigen is expressed within multiple sclerosis lesions in humans. OX40 (CD134) is thought to be a secondary co-stimulatory immune checkpoint molecule that is expressed by T cells. This study aimed to evaluate the mRNA expression of OX40 and its serum levels in the peripheral blood of patients with Multiple Sclerosis (MS) or Neuromyelitis Optica (NMO).MethodsPatients with MS (n = 60), NMO (n = 20), and 20 healthy subjects were recruited from Sina Hospital, Tehran, Iran. The diagnoses were confirmed by a specialist in clinical neurology. Peripheral venous blood was obtained from all subjects, and mRNA quantification of OX40 was conducted using real-time PCR. Serum samples were also obtained and the concentration of OX40 was determined using an enzyme-linked immunosorbent assay (ELISA).ResultsThere was a significant correlation between the mRNA expression and serum levels of OX40 and disability as assessed using the expanded disability status scale (EDSS) in the patients with MS, but not in the patients with NMO. Expression of OX40 mRNA was significantly higher in the peripheral blood of MS patients compared to healthy individuals and NMO patients (*P < 0.05). In addition, serum OX40 concentrations were also significantly higher in patients with MS patients compared with healthy subjects (9.08 ± 2.48 vs. 1.49 ± 0.54 ng/ml; P = 0.041).ConclusionsIt appears that an increased expression of OX40 may be associated with the hyperactivation of T cells in patients with MS, and this may play a role in the pathogenesis of the disease.

Schwann Cell Remyelination in the Multiple Sclerosis Central Nervous System

Multiple sclerosis (MS) is a central nervous system (CNS) demyelinating disease. Failure to remyelinate successfully is common in MS lesions, often with consequent neuronal/axonal damage. CNS myelin is normally produced by oligodendroglial cells. Remyelination by Schwann cells (SchC) has been reported in spinal cord demyelination, in which SchCs are in close proximity to CNS myelin. We identified an MS cerebral lesion that was remyelinated by SchCs. This prompted us to query the extent of SchC remyelination in the brain and spinal cords of additional autopsied MS specimens. CNS tissues were obtained from the autopsies of 14 MS cases. Remyelinated lesions were identified by Luxol fast blue-periodic-acid Schiff and solochrome cyanine staining. Deparaffinized sections containing remyelinated lesions were stained with anti–glial fibrillary acid protein to identify reactive astrocytes. Glycoprotein P zero (P0) is a protein exclusive to peripheral but not CNS myelin. Areas of SchC remyelination were identified by staining with anti-P0. Myelinated regions in the index case cerebral lesion were confirmed to be of SchC origin using anti-P0 staining. Subsequently, 64 MS lesions from 14 autopsied MS cases were examined, and 23 lesions in 6 cases showed remyelination by SchCs. Lesions from the cerebrum, brainstem, and spinal cord were examined in each case. When present, SchC remyelination was most commonly located adjacent to the venules and associated with a lower surrounding density of glial fibrillary acid protein+ reactive astrocytes than areas of only oligodendroglial cell remyelination. The difference was significant only for spinal cord and brainstem lesions but not for lesions located in the brain. In conclusion, we demonstrated SchC remyelination in the cerebrum, brainstem, and spinal cord of 6 autopsied MS cases. To our knowledge, this is the first report of supratentorial SchC remyelination in MS.

Multiple sclerosis versus cerebral small vessel disease in MRI: a practical approach using qualitative and quantitative signal intensity differences in white matter lesions.

Multiple sclerosis (MS) and cerebral small vessel disease (CSVD) are relatively common radiological entities that occasionally necessitate differential diagnosis. To investigate the differences in magnetic resonance imaging (MRI) signal intensity (SI) between MS and CSVD related white matter lesions. On 1.5-T and 3-T MRI scanners, 50 patients with MS (380 lesions) and 50 patients with CSVD (395 lesions) were retrospectively evaluated. Visual inspection was used to conduct qualitative analysis on diffusion-weighted imaging (DWI)_b1000 to determine relative signal intensity. The thalamus served as the reference for quantitative analysis based on SI ratio (SIR). The statistical analysis utilized univariable and multivariable methods. There were analyses of patient and lesion datasets. On a dataset restricted by age (30-50 years), additional evaluations, including unsupervised fuzzy c-means clustering, were performed. Using both quantitative and qualitative features, the optimal model achieved a 100% accuracy, sensitivity, and specificity with an area under the curve (AUC) of 1 in patient-wise analysis. With an AUC of 0.984, the best model achieved a 94% accuracy, sensitivity, and specificity when using only quantitative features. The model's accuracy, sensitivity, and specificity were 91.9%, 84.6%, and 95.8%, respectively, when using the age-restricted dataset. Independent predictors were T2_SIR_max (optimal cutoff=2.1) and DWI_b1000_SIR_mean (optimal cutoff=1.1). Clustering also performed well with an accuracy, sensitivity, and specificity of 86.5%, 70.6%, and 100%, respectively, in the age-restricted dataset. SI characteristics derived from DWI_b1000 and T2-weighted-based MRI demonstrate excellent performance in differentiating white matter lesions caused by MS and CSVD.

Microstructural alterations in different types of lesions and their perilesional white matter in relapsing-remitting multiple sclerosis based on diffusion kurtosis imaging.

In multiple sclerosis (MS), contrast enhancement lesions and chronic active lesions have been demonstrated to have different degrees of inflammation. Accordingly, they exist different degrees of tissue damage, one is short and acute, and another is slow and longstanding. This study aimed to explore whether diffusion parameters can differentiate different types of lesions, and investigate the microstructural damage between different types of MS lesions by using diffusion magnetic resonance imaging (dMRI) and its correlation with clinical biomarkers of disability and cognitive states. We retrospectively identified 77 contrast enhancement lesions (CELs), 384 iron rim lesions (IRLs), 393 non-iron rim lesions (NIRLs), their corresponding perilesional white matter (PLWM), and 68 normal-appearing white matter (NAWM) from 68 relapsing-remitting MS (RRMS). Additionally, 44 white matter in healthy controls (WM in HCs) were also enrolled in this study. The DTI and DKI parameters were measured in the above white matter, including kurtosis fractional anisotropy (KFA), fractional anisotropy (FA), mean kurtosis (MK), and mean diffusivity (MD). All the patients were assessed with the Digital Span Test (DST), the Symbol Digit Modalities Test (SDMT), the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and the Expanded Disability Status Scale (EDSS). The lowest KFA, FA, MK values and the highest MD values were found in CELs, followed by IRLs, NIRLs, NAWM, and WM in HCs. In KFA and FA values, there were significant differences between each type of lesion, as well as each type of PLWM (P < 0.05). The MK values of CELs and IRLs were significantly lower than NIRLs, but inversely for MD (P < 0.05). There were no differences between CELs and IRLs for MK (P=1) and MD (P=0.261). The results of MK and MD values in CELs-PLWM and IRLs-PLWM were similar to the CELs and IRLs. There were no significant differences between NAWM and WM in HCs in all the enrolled diffusion parameters (P >0.05) and the FA values between NIRLs-PLWM and NAWM or between NIRLs-PLWM and WM in HCs were no significant differences (P >0.05). The KFA and MD values in IRLs-PLWM (r =0.443, P =0.021; r =-0.518, P =0.006) were correlated with the DST scores and the KFA of CELs-PLWM (r =0.396, P =0.041) was correlated with SDMT scores. Our findings demonstrate that the KFA values have the potential to distinguish different types of MS white matter tissues. Furthermore, the diffusion parameters can reflect the microstructure abnormalities in different MS lesions and might help us better understand the pathological mechanism and lesion evolution.

Learning from multiple annotators for medical image segmentation

Supervised machine learning methods have been widely developed for segmentation tasks in recent years. However, the quality of labels has high impact on the predictive performance of these algorithms. This issue is particularly acute in the medical image domain, where both the cost of annotation and the inter-observer variability are high. Different human experts contribute estimates of the ”actual” segmentation labels in a typical label acquisition process, influenced by their personal biases and competency levels. The performance of automatic segmentation algorithms is limited when these noisy labels are used as the expert consensus label. In this work, we use two coupled CNNs to jointly learn, from purely noisy observations alone, the reliability of individual annotators and the expert consensus label distributions. The separation of the two is achieved by maximally describing the annotator’s “unreliable behavior” (we call it “maximally unreliable”) while achieving high fidelity with the noisy training data. We first create a toy segmentation dataset using MNIST and investigate the properties of the proposed algorithm. We then use three public medical imaging segmentation datasets to demonstrate our method’s efficacy, including both simulated (where necessary) and real-world annotations: 1) ISBI2015 (multiple-sclerosis lesions); 2) BraTS (brain tumors); 3) LIDC-IDRI (lung abnormalities). Finally, we create a real-world multiple sclerosis lesion dataset (QSMSC at UCL: Queen Square Multiple Sclerosis Center at UCL, UK) with manual segmentations from 4 different annotators (3 radiologists with different level skills and 1 expert to generate the expert consensus label). In all datasets, our method consistently outperforms competing methods and relevant baselines, especially when the number of annotations is small and the amount of disagreement is large. The studies also reveal that the system is capable of capturing the complicated spatial characteristics of annotators’ mistakes.

Designing and Characterization of Tregitope-Based Multi-Epitope Vaccine Against Multiple Sclerosis: An Immunoinformatic Approach.

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system(CNS). It is widely accepted that the development and progression of MS result from aberrant activation of potentially encephalitogenic reactive-T cells against CNS antigens. The pathologic roles of both CD4+ (T helper; Th) and CD8+ T cells have been demonstrated in MS lesions. In the present work, we applied a series of bioinformatics tools to design a dendritic cell (DC)-targeting Tregitope-based multi-epitope vaccine for MS to induce tolerance in pathogenic myelin-specific T cells. The 3D structure of anti-DEC205 scFv and the remaining part of the vaccine were modeled by ROSIE Antibody server and ITASSER software, respectively. AIDA web server (ab initio domain assembly server) was applied to assemble two parts of the vaccine and build the full construct. Following modeled structure refinement and validation, physicochemical properties, and allergenicity of the vaccine were assessed. In the final step, in silico cloning was done to ensure high-level expression in the desired host. This vaccine consists of three main parts; 1) Anti-DEC205 scFv antibody, 2) multiepitope vaccine part composed of multiple pathogenic CD4+, and CD8+ T cell epitopes originated from multiple known antigens in MS patients, as well as T-regulatory (Treg)-inducing epitopes (Tregitopes), and 3) vasoactive intestinal peptide (VIP). All parts of the final vaccine were joined together with the help of proper linkers. After vaccine construction, the three-D structure, as well as different physicochemical and immunological features of the vaccine were predicted. Finally, in silico gene cloning was also carried out to assure efficient production of protein vaccine in Escherichia coli K12 expression strain. Computational study revealed that this vaccination can regulate MS disease progression and even relapse by harnessing pathogenic T cells.

Accelerated Simultaneous T2 and T2* Mapping of Multiple Sclerosis Lesions Using Compressed Sensing Reconstruction of Radial RARE-EPI MRI.

(1) Background: Radial RARE-EPI MRI facilitates simultaneous T2 and T2* mapping (2in1-RARE-EPI). With modest undersampling (R = 2), the speed gain of 2in1-RARE-EPI relative to Multi-Spin-Echo and Multi-Gradient-Recalled-Echo references is limited. Further reduction in scan time is crucial for clinical studies investigating T2 and T2* as imaging biomarkers. We demonstrate the feasibility of further acceleration, utilizing compressed sensing (CS) reconstruction of highly undersampled 2in1-RARE-EPI. (2) Methods: Two-fold radially-undersampled 2in1-RARE-EPI data from phantoms, healthy volunteers (n = 3), and multiple sclerosis patients (n = 4) were used as references, and undersampled (Rextra = 1-12, effective undersampling Reff = 2-24). For each echo time, images were reconstructed using CS-reconstruction. For T2 (RARE module) and T2* mapping (EPI module), a linear least-square fit was applied to the images. T2 and T2* from CS-reconstruction of undersampled data were benchmarked against values from CS-reconstruction of the reference data. (3) Results: We demonstrate accelerated simultaneous T2 and T2* mapping using undersampled 2in1-RARE-EPI with CS-reconstruction is feasible. For Rextra = 6 (TA = 01:39 min), the overall MAPE was ≤8% (T2*) and ≤4% (T2); for Rextra = 12 (TA = 01:06 min), the overall MAPE was <13% (T2*) and <5% (T2). (4) Conclusion: Substantial reductions in scan time are achievable for simultaneous T2 and T2* mapping of the brain using highly undersampled 2in1-RARE-EPI with CS-reconstruction.

Quantitative magnetic resonance imaging reflects different levels of histologically determined myelin densities in multiple sclerosis, including remyelination in inactive multiple sclerosis lesions.

Magnetic resonance imaging (MRI) of focal or diffuse myelin damage or remyelination may provide important insights into disease progression and potential treatment efficacy in multiple sclerosis (MS). We performed post-mortem MRI and histopathological myelin measurements in seven progressive MS cases to evaluate the ability of three myelin-sensitive MRI scans to distinguish different stages of MS pathology, particularly chronic demyelinated and remyelinated lesions. At 3 Tesla, we acquired two different myelin water imaging (MWI) scans and magnetisation transfer ratio (MTR) data. Histopathology included histochemical stainings for myelin phospholipids (LFB) and iron as well as immunohistochemistry for myelin proteolipid protein (PLP), CD68 (phagocytosing microglia/macrophages) and BCAS1 (remyelinating oligodendrocytes). Mixed-effects modelling determined which histopathological metric best predicted MWF and MTR in normal-appearing and diffusely abnormal white matter, active/inactive, inactive, remyelinated and ischemic lesions. Both MWI measures correlated well with each other and histology across regions, reflecting the different stages of MS pathology. MTR data showed a considerable influence of components other than myelin and a strong dependency on tissue storage duration. Both MRI and histology revealed increased myelin densities in inactive compared with active/inactive lesions. Chronic inactive lesions harboured single scattered myelin fibres indicative of low-level remyelination. Mixed-effects modelling showed that smaller differences between white matter areas were linked to PLP densities and only to a small extent confounded by iron. MWI reflects differences in myelin lipids and proteins across various levels of myelin densities encountered in MS, including low-level remyelination in chronic inactive lesions.

Tissue-resident memory T cells in the multiple sclerosis brain and their relationship to Epstein-Barr virus infected B cells

Presence of EBV infected B cells and EBV-specific CD8 T cells in the multiple sclerosis (MS) brain suggests a role for virus-driven immunopathology in brain inflammation. Tissue-resident memory (Trm) T cells differentiating in MS lesions could provide local protection against EBV reactivation. Using immunohistochemical techniques to analyse canonical tissue residency markers in postmortem brains from control and MS cases, we report that CD103 and/or CD69 are mainly expressed in a subset of CD8+ T cells that intermingle with and contact EBV infected B cells in the infiltrated MS white matter and meninges, including B-cell follicles. Some Trm-like cells were found to express granzyme B and PD-1, mainly in white matter lesions. In the MS brain, Trm cells could fail to constrain EBV infection while contributing to sustain inflammation.

Lesion network localization of depression in multiple sclerosis

Multiple sclerosis (MS), a demyelinating disease that causes focal white matter lesions, is commonly associated with depression. However, it remains unclear whether depression risk is selectively increased by specific white matter lesion locations. Recent work shows that stroke lesions and therapeutic neuromodulation sites that modify depression severity are connected to a common brain circuit, providing an a priori template. Here we assessed whether this circuit is relevant for white matter lesions in MS. In a clinical and radiological database of individuals with MS (n = 281), we estimated the whole-brain connectivity of each person’s white matter lesion locations using a normative connectome database (n = 1,000). Functional connectivity between MS lesion locations and our a priori depression circuit was correlated with depression severity in MS (P = 0.013) and specific to depression versus other MS-related symptoms (P = 0.0058). A data-driven circuit for MS depression showed similar topography to our a priori depression circuit (P = 0.015). The peak of this data-driven MS depression circuit was in the ventral midbrain, including the ventral tegmental area (familywise-error-corrected P < 0.05). These findings lend insight into the localization of MS depression that may help guide targeting for therapeutic brain stimulation. Using lesion network mapping, Siddiqi, Kletenik et al. have identified a white matter lesion network for depression in people with multiple sclerosis.

Combining in vivo proton exchange rate (k ex) MRI with quantitative susceptibility mapping to further stratify the gadolinium-negative multiple sclerosis lesions.

Conventional gadolinium (Gd)-enhanced MRI is currently used for stratifying the lesion activity of multiple sclerosis (MS) despite limited correlation with disability and disease activity. The stratification of MS lesion activity needs further improvement to better support clinics. To investigate if the novel proton exchange rate (k ex ) MRI combined with quantitative susceptibility mapping (QSM) may help to further stratify non-enhanced (Gd-negative) MS lesions. From December 2017 to December 2020, clinically diagnosed relapsing-remitting MS patients who underwent MRI were consecutively enrolled in this IRB-approved retrospective study. The customized MRI protocol covered conventional T2-weighted, T2-fluid-attenuated-inversion-recovery, pre- and post-contrast T1-weighted imaging, and quantitative sequences, including k ex MRI based on direct-saturation removed omega plots and QSM. Each MS lesion was evaluated based on its Gd-enhancement as well as its susceptibility and k ex elevation compared to the normal appearing white matter. The difference and correlation concerning lesion characteristics and imaging contrasts were analyzed using the Mann-Whitney U test or Kruskal-Wallis test, and Spearman rank analysis with p < 0.05 considered significant. A total of 322 MS lesions from 30 patients were identified with 153 Gd-enhanced and 169 non-enhanced lesions. We found that the k ex elevation of all lesions significantly correlated with their susceptibility elevation (r = 0.30, p < 0.001). Within the 153 MS lesions with Gd-enhancement, ring-enhanced lesions showed higher k ex elevation than the nodular-enhanced ones' (p < 0.001). Similarly, lesions with ring-hyperintensity in QSM also had higher k ex elevation than the lesions with nodular-QSM-hyperintensity (p < 0.001). Of the 169 Gd-negative lesions, three radiological patterns were recognized according to lesion manifestations on the k ex map and QSM images: Pattern I (k ex + and QSM+, n = 114, 67.5%), Pattern II (only k ex + or QSM+, n = 47, 27.8%) and Pattern III (k ex - and QSM-, n = 8, 4.7%). Compared to Pattern II and III, Pattern I had higher k ex (p < 0.001) and susceptibility (p < 0.05) elevation. The percentage of Pattern I of each subject was negatively correlated with the disease duration (r = -0.45, p = 0.015). As a potential imaging biomarker for inflammation due to oxidative stress, in vivo k ex MRI combined with QSM is promising in extending the clinical classification of MS lesions beyond conventional Gd-enhanced MRI.

Quantitative susceptibility mapping for differentiating multiple sclerosis from cerebral small vessel disease

Background and Purpose: With the increasing prevalence of cerebrovascular risk factors in young adults, accurate differentiation of multiple sclerosis (MS) from cerebral small vessel disease (SVD) remains challenging because of the significant overlap in the appearance of white matter lesions on conventional magnetic resonance (MR) images. The purpose of this study was to use quantitative susceptibility mapping (QSM) to differentiate patients with MS from patients with SVD. Materials and Methods: Thirty-two patients with relapsing-remitting MS and 40 patients with SVD were selected in this institution review board-approved retrospective study. All patient examinations included QSM and T2-weighted FLAIR (T2w). All T2w hyperintense lesions were analyzed on QSM for susceptibility relative to normal-appearing white matter and were evaluated for the presence of hyperintense rims and the central vein sign. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic accuracy of differentiating MS patients from SVD patients. Results: The mean susceptibility value of SVD lesions was significantly lower than MS lesions (2.31 ± 9.68 ppb vs. 27.77 ± 20.27 ppb, p &lt; 0.001). Of MS patients and MS lesions, 68.8% and 22.2% had hyperintense rims on QSM, respectively. Of MS patients and MS lesions, 75% and 37.6% had a central vein sign on QSM, respectively. Lesion susceptibility values allowed accurate differentiation MS from SVD with an area under the ROC curve (AUC) = 0.848 for lesion differentiation, AUC = 0.999 for patient differentiation, and an optimal cut-off susceptibility value of 14.88 ppb. Conclusions: Magnetic susceptibility measured using QSM allows accurate differentiation of MS patients from SVD patients.

The ipsilateral silent period and its link to cortical lesions in multiple sclerosis

The ipsilateral silent period and its link to cortical lesions in multiple sclerosis