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Different types of white matter lesions in CNS inflammatory diseases. (a). Typical MRI findings in MS: T2-hyperintense periventricular and juxtacortical lesions. (b). T1 scan showing ring and open ring gadolinium enhancement pattern of lesions present in Fig.1a. (c). Subcortical FLAIR-hyperintense white matter lesions in a patient with APS secondary to SLE. (d). Cortical-subcortical malacia after an ischaemic stroke in the same patient with APS secondary to SLE presented in fig. 1c. (e). T2 dark fluid-hyperintense lesion in area postrema in a patient with SLE which needs to be differentiated from NMOSD. (f). Diffuse T2-hyperintense lesion at the level Th1 to Th4 affecting white as well as gray matter of spinal cord in NMO patient. Small T2-hyperintense lesions visible also at the level of Th8 and Th10.
Source publication
Multiple sclerosis (MS) is the most common acquired demyelinating disorder of the central nervous system (CNS). Diagnosing MS can be very challenging owing to its variable clinical features and lack of specific tests. Magnetic resonance imaging (MRI) is a key measure in this process. Although white matter lesions on brain MRI are regarded as a hall...
Contexts in source publication
Context 1
... the diagnostic criteria of MS, MRI is highly advantageous in detecting findings suggestive of disorders other than MS. Awareness of such features seems to be essential for understanding the concept of 'no better explanation' (Charil et al., Oct). Table 1 shows common MS MRI findings and "red flags"-suggestive of other inflammatory CNS diseases. Fig. 1 (a-f) demonstrates different types of white matter lesions. Although cerebrospinal fluid (CSF) examination is not obligatory to set the diagnosis of MS, 2017 revisions of McDonald criteria has emphasized the significance of the presence of CSF-specific oligoclonal bands (OCBs), which may substitute MRI criterion for DIT in patients ...
Context 2
... of alternative diagnoses (Wingerchuk et al., 2015). AQP4 is the key target in NMO pathogenesis. AQP4 is an astrocyte water channel protein which promotes the movement of water across cell membranes in response to osmotic gradients ( Papadopoulos and Verkman, 2012). AQP4 is primarily expressed in astrocyte foot processes, in particular within the fig. 1c. (e). T2 dark fluid-hyperintense lesion in area postrema in a patient with SLE which needs to be differentiated from NMOSD. (f). Diffuse T2-hyperintense lesion at the level Th1 to Th4 affecting white as well as gray matter of spinal cord in NMO patient. Small T2-hyperintense lesions visible also at the level of Th8 and Th10. optic ...
Citations
... MRI is currently the most valuable tool in diagnosis and differential diagnosis. However, complex radiological findings can overlap, leading to misinterpretation, confusion or misdiagnosis (4,5). ...
... MS diagnosis and its distinctions from other demyelinating diseases or MS mimics can be challenging [7]. The current diagnostic criteria, 2017 McDonald criteria, use a combination of clinical, radiological, and laboratory features to guide clinicians [8]. ...
Brain and spinal cord imaging plays a pivotal role in aiding clinicians with the diagnosis and monitoring of multiple sclerosis. Nevertheless, the significance of magnetic resonance imaging in MS extends beyond its clinical utility. Advanced imaging modalities have facilitated the in vivo detection of various components of MS pathogenesis, and, in recent years, MRI biomarkers have been utilized to assess the response of patients with relapsing–remitting MS to the available treatments. Similarly, MRI indicators of neurodegeneration demonstrate potential as primary and secondary endpoints in clinical trials targeting progressive phenotypes. This review aims to provide an overview of the latest advancements in brain and spinal cord neuroimaging in MS.
... MS lesions occur at different times and in different CNS locations. For this reason, MS lesions are sometimes said to be "scattered in time and space" [1]. The definite etiology of MS is still not completely understood; however, different factors are thought to contribute to the disease occurrence. ...
... Active tissue damage has been related to activated microglia and macrophages. As a result, neurodegenerative changes develop, affecting axons, neurons, and synapses [1]. When myelin, the protective membrane that insulates nerve fibers, is damaged and signals to and from the brain are disrupted, which causes a range of unpredictable symptoms [5]. ...
Multiple sclerosis (MS) is an autoimmune disease affecting the central nervous system (CNS). The diagnosis of MS is based on clinical signs and symptoms as well as findings in magnetic resonance imaging (MRI) sequences by demonstrating the spatial and temporal dispersion of white matter lesions, which are thought to be typical of MS in distribution, shape, extent, and signal abnormalities. Spinal cord MRI can identify asymptomatic lesions and rule out malignancies or spinal stenosis in patients for whom brain imaging is not helpful in making an MS diagnosis. This study examines the MRI features of Saudi Arabian patients clinically proven to have MS with typical lesions exclusively evident in the spinal cord. This retrospective cross-sectional study was carried out in 151 patients who are confirmed cases of MS based on clinical findings and MRI results. Patients’ MRI data were reviewed from the picture archiving and communication system (PACS). The study revealed that MS incidence was higher in females than males and that the number of people diagnosed with MS increased in middle age. Cervical cord plaques and cervical cord curve straightening were the most frequent changes (67% and 56%, respectively), indicating that MRI can complement and even replace clinical data in MS diagnosis, leading to earlier, more precise diagnoses and speedier starts to treatment.
... [5][6][7][8][9] Simply, excluding other CNS diseases is how a diagnosis for MS is routinely achieved. [10][11][12] Thus, a rapid, reliable, and non-invasive diagnostic test specific for MS would benefit patients' health and well-being. [13][14][15][16][17] Identifying biomarkers to aid in the diagnosis of human diseases is a well-established and successful endeavor that has the potential to decrease long-term healthcare costs. ...
... CSF metabolome links diverse metabolic pathways to MS. 12 The 32 metabolites altered in the CSF of PMS patients relative to healthy controls (Table S1) were directly associated with a range of cellular or biological processes that contribute to the pathology of MS. The 32 CSF metabolites were primarily amino acids and metabolites related to glycolysis and TCA, which included succinate, acetate, lactate, and glycerol that were all decreased in PMS. ...
... Common central neurological disorders, such as multiple sclerosis and Parkinson's disease, impose a substantial economic burden on society [3,4]. After decades of research, central nervous system disorders continue to pose diagnostic and therapeutic difficulties, with limited diagnostic and therapeutic options [5]. Central nervous system disorders have complex etiologies that defy reduction to a single cause. ...
Background
People with psoriasis are at a higher risk for having central neurological problems, according to previous studies; however, it is unclear if there is a genetic link between the risk of developing psoriasis and developing central neurological disorders. In this study, the possible link between genetically predisposed psoriasis and the risk of common central nervous system disorders was comprehensively investigated.
Methods
There was no overlap in the participant populations between the psoriasis and central neurological disorders genome-wide association studies, which provide the genetic resources. Inverse variance weighting, often used as Mendelian randomization (MR) analysis, is the main method. To guarantee the accuracy of our findings, a number of sensitivity studies were carried out.
Results
MR analysis revealed that although psoriasis was reported to increase the risk of Parkinson's disease (OR = 4.42, 95%CI[-3.81～6.79], P = 0.58) and epilepsy (OR = 4.71, 95%CI[-2.20～5.30], P = 0.42) in this study, they did not reach statistical significance. At the same time, this study did not observe that psoriasis would increase the risk of multiple sclerosis (OR = 0.01, 95%CI [-12.61～3.83], P = 0.30) and migraine (OR = 0.99, 95%CI [0.94～1.05], P = 0.78), they also did not reach statistical significance. Under all sensitivity assessments, the results remained stable.
Conclusions
Psoriasis does not appear to raise the risk of migraine, Parkinson's disease, multiple sclerosis, or epilepsy, according to our study.
... In systemic diseases with central nervous system involvement (SDCNS), clinical presentation and findings of magnetic resonance imaging (MRI) may be similar to those of MS. Our recently published review [5] summarized the latest data describing similarities and differences between MS and SDCNS, including radiological characteristics. Although MRI is one of the most important paraclinical tools in the diagnosis of MS, its specificity is not satisfactory [6]. ...
... In our study, we also found significantly higher T2LV and T1LV in MS than in SDCNS patients. These results underscore focal white matter destruction as a process more pronounced in MS than in SDCNS patients beginning from the earliest phases of the disease, which is concordant with the understanding of CNS pathology in MS [5,14,58]. Additionally, this observation seems to support a less clear association of CNS symptoms with focal brain pathology in systemic diseases. Importantly, our findings corroborate the results of a previously published study which also detected differences in white matter lesion load between patients with MS and SLE-CNSI [15]. ...
Conventional brain magnetic resonance imaging (MRI) in systemic diseases with central nervous system involvement (SDCNS) may imitate MRI findings of multiple sclerosis (MS). In order to better describe the MRI characteristics of these conditions, in our study we assessed brain volume parameters in MS (n = 58) and SDCNS (n = 41) patients using two-dimensional linear measurements (2DLMs): bicaudate ratio (BCR), corpus callosum index (CCI) and width of third ventricle (W3V). In SDCNS patients, all 2DLMs were affected by age (CCI p = 0.005, BCR p < 0.001, W3V p < 0.001, respectively), whereas in MS patients only BCR and W3V were (p = 0.001 and p = 0.015, respectively). Contrary to SDCNS, in the MS cohort BCR and W3V were associated with T1 lesion volume (T1LV) (p = 0.020, p = 0.009, respectively) and T2 lesion volume (T2LV) (p = 0.015, p = 0.009, respectively). CCI was associated with T1LV in the MS cohort only (p = 0.015). Moreover, BCR was significantly higher in the SDCNS group (p = 0.01) and CCI was significantly lower in MS patients (p = 0.01). The best predictive model to distinguish MS and SDCNS encompassed gender, BCR and T2LV as the explanatory variables (sensitivity 0.91; specificity 0.68; AUC 0.86). Implementation of 2DLMs in the brain MRI analysis of MS and SDCNS patients allowed for the identification of diverse patterns of local brain atrophy in these clinical conditions.
... As an example, a study in 2020 used a CNN to differentiate MS from NMO based on MRI images, achieving an accuracy rate of 71.1%. 71 Wingerchuk et al. conducted extensive research on neuromyelitis Optica spectrum disorders (NMOSD). Their research has contributed significantly to the development of diagnostic criteria for NMOSD, which is an infrequent autoimmune disorder that mostly affects the spinal cord and optic nerves.In their work, the importance of early and precise diagnosis of NMOSD was emphasized, leading to timely diagnosis and appropriate management and treatment of the disease. ...
Multiple sclerosis (MS) is a complex autoimmune disease characterized by inflammatory processes, demyelination, neurodegeneration, and axonal damage within the central nervous system (CNS). Retinal imaging, particularly Optical coherence tomography (OCT), has emerged as a crucial tool for investigating MS-related retinal injury. The integration of artificial intelligence(AI) has shown promise in enhancing OCT analysis for MS. Researchers are actively utilizing AI algorithms to accurately detect and classify MS-related abnormalities, leading to improved efficiency in diagnosis, monitoring, and personalized treatment planning. The prognostic value of AI in predicting MS disease progression has garnered substantial attention. Machine learning (ML) and deep learning (DL) algorithms can analyze longitudinal OCT data to forecast the course of the disease, providing critical information for personalized treatment planning and improved patient outcomes. Early detection of high-risk patients allows for targeted interventions to mitigate disability progression effectively. As such, AI-driven approaches yielded remarkable abilities in classifying distinct MS subtypes based on retinal features, aiding in disease characterization and guiding tailored therapeutic strategies. Additionally, these algorithms have enhanced the accuracy and efficiency of OCT image segmentation, streamlined diagnostic processes, and reduced human error. This study reviews the current research studies on the integration of AI,including ML and DL algorithms, with OCT in the context of MS. It examines the advancements, challenges, potential prospects, and ethical concerns of AI-powered techniques in enhancing MS diagnosis, monitoring disease progression, revolutionizing patient care, the development of patient screening tools, and supported clinical decision-making based on OCT images.
... The clinical manifestations of MS are diverse, and the core diagnostic points are neurological deficits disseminated in time and space. The diagnosis of MS is challenging, and it should be prudent to differentiate it from other diseases with similar clinical manifestations (2,3), especially in other inflammatory demyelinating diseases, such as neuromyelitis optica spectrum disorders (NMOSD), and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Therefore, MS-related biomarkers have become the focus of ongoing research. ...
Background
Cerebrospinal fluid oligoclonal band (CSF-OCB) is an established biomarker in diagnosing multiple sclerosis (MS), however, there are no nationwide data on CSF-OCB prevalence and its diagnostic performance in Chinese MS patients, especially in the virtue of common standard operation procedure (SOP).
Methods
With a consensus SOP and the same isoelectric focusing system, we conducted a nationwide multi-center study on OCB status in consecutively, and recruited 483 MS patients and 880 non-MS patients, including neuro-inflammatory diseases (NID, n = 595) and non-inflammatory neurological diseases (NIND, n=285). Using a standardized case report form (CRF) to collect the clinical, radiological, immunological, and CSF data, we explored the association of CSF-OCB positivity with patient characters and the diagnostic performance of CSF-OCB in Chinese MS patients. Prospective source data collection, and retrospective data acquisition and statistical data analysis were used.
Findings
369 (76.4%) MS patients were OCB-positive, while 109 NID patients (18.3%) and 6 NIND patients (2.1%) were OCB-positive, respectively. Time from symptom onset to diagnosis was significantly shorter in OCB-positive than that in OCB-negative MS patients (13.2 vs 23.7 months, P=0.020). The prevalence of CSF-OCB in Chinese MS patients was significantly higher in high-latitude regions (41°-50°N)(P=0.016), and at high altitudes (>1000m)(P=0.025). The diagnostic performance of CSF-OCB differentiating MS from non-MS patients yielded a sensitivity of 76%, a specificity of 87%.
Interpretation
The nationwide prevalence of CSF-OCB was 76.4% in Chinese MS patients, and demonstrated a good diagnostic performance in differentiating MS from other CNS diseases. The CSF-OCB prevalence showed a correlation with high latitude and altitude in Chinese MS patients.
... It is a non-parametric and unsupervised way of automatic threshold selection for segmentation of images. It is ideal as in it expands the between-class change, a notable measure utilized in factual discriminant examination [14,21]. ...
Texture analysis plays an important role in many image processing applications to describe the objects. On the other hand, visual Fabric Defect Detection (FDD) is a highly research field in the computer vision. Surface defect refers to abnormalities in the texture of the surface. So, in this paper a dual purpose benchmark dataset is proposed for texture image analysis and surface defect detection. The first framework is based Segmentation with Contrast Limited Histogram Equalization (CLAHE) and finally FE for Classification (SCFC). The SCFC depends on improvement using CLAHE in addition to pre-processing followed by segmentation by OT and finally FE for classification task. The second scheme is relied on merging the features of A Trous Algorithm with Homomorphic Method (HM) (AH) following by Segmentation and Feature Extraction (FE) for Classification (AHSFC). The AHSFC depends on enhancement using AH in addition to pre-processing followed by segmentation using Optimum Global Thresholding (OT) and finally FE for the detection or classification task. The performance quality metrics for the suggested techniques are entropy, average gradient, contrast, Sobel edge magnitude, sensitivity, specificity, precision, accuracy and identification time.Simulation results prove that the success of both techniques in detecting the FDD. By comparing the first and the second presented algorithms, it is clear that the second suggested technique gives superior for the FDD the clothing.
... While our results support other studies that show the bene ts to prediction of combining measurements from several layers of the retina [22,23], we agree that pure OCT data constitute a very useful tool that, via a simple, inexpensive, and innocuous method, can achieve even greater precision than magnetic resonance imaging. Numerous experts recommend using OCT as an additional method in standard MS diagnosis [19,24,25]. ...
Background/Objectives
Study of retinal structure based on optical coherence tomography (OCT) data can facilitate early diagnosis of relapsing-remitting multiple sclerosis (RRMS). Although artificial intelligence can provide highly reliable diagnoses, the results obtained must be explainable.
Subjects/Methods
The study included 79 recently diagnosed RRMS patients and 69 age matched healthy control subjects. Thickness (Avg) and inter-eye difference (Diff) features are obtained in 4 retinal layers using the posterior pole protocol. Each layer is divided into 6 analysis zones. The Support Vector Machine plus Recursive Feature Elimination with Leave-One-Out Cross Validation (SVM-RFE-LOOCV) approach is used to find the subset of features that reduces dimensionality and optimizes the performance of the classifier.
Results
SVM-RFE-LOOCV was used to identify OCT features with greatest capacity for early diagnosis, determining the area of the papillomacular bundle to be the most influential. A correlation was observed between loss of layer thickness and increase in functional disability. There was also greater functional deterioration in patients with greater asymmetry between left and right eyes. The classifier based on the top-ranked features obtained sensitivity = 0.86 and specificity = 0.90.
Conclusions
There was consistency between the features identified as relevant by the SVM-RFE-LOOCV approach and the retinotopic distribution of the retinal nerve fibers and the optic nerve head. This simple method contributes to implementation of an assisted diagnosis system and its accuracy exceeds that achieved with magnetic resonance imaging of the central nervous system, the current gold standard. This paper provides novel insights into RRMS affectation of the neuroretina.
