Multiple sclerosis (MS) is one of the most prevalent chronic inflammatory diseases caused by demyelination and axonal damage in the central nervous system. Structural retinal imaging via optical ...coherence tomography (OCT) shows promise as a noninvasive biomarker for monitoring of MS. There are successful reports regarding the application of Artificial Intelligence (AI) in the analysis of cross-sectional OCTs in ophthalmologic diseases. However, the alteration of thicknesses of various retinal layers in MS is noticeably subtle compared to other ophthalmologic diseases. Therefore, raw cross-sectional OCTs are replaced with multilayer segmented OCTs for discrimination of MS and healthy controls (HCs).
To conform to the principles of trustworthy AI, interpretability is provided by visualizing the regional layer contribution to classification performance with the proposed occlusion sensitivity approach. The robustness of the classification is also guaranteed by showing the effectiveness of the algorithm while being tested on the new independent dataset. The most discriminative features from different topologies of the multilayer segmented OCTs are selected by the dimension reduction method. Support vector machine (SVM), random forest (RF), and artificial neural network (ANN) are used for classification. Patient-wise cross-validation (CV) is utilized to evaluate the performance of the algorithm, where the training and test folds contain records from different subjects.
The most discriminative topology is determined to square with a size of 40 pixels and the most influential layers are the ganglion cell and inner plexiform layer (GCIPL) and inner nuclear layer (INL). Linear SVM resulted in 88% Accuracy (with standard deviation (std) = 0.49 in 10 times of execution to indicate the repeatability), 78% precision (std=1.48), and 63% recall (std=1.35) in the discrimination of MS and HCs using macular multilayer segmented OCTs.
The proposed classification algorithm is expected to help neurologists in the early diagnosis of MS. This paper distinguishes itself from other studies by employing two distinct datasets, which enhances the robustness of its findings in comparison with previous studies with lack of external validation. This study aims to circumvent the utilization of deep learning methods due to the limited quantity of the available data and convincingly demonstrates that favorable outcomes can be achieved without relying on deep learning techniques.
Abstract Uric acid (UA) is a hydrophilic antioxidant product associated with multiple sclerosis (MS). We conducted a randomized case-control study to evaluate the serum level of UA in different ...phases of MS in comparison with levels in a healthy control population. Serum UA was checked in 130 patients with relapsing-remitting MS (85 patients in remitting and 45 patients in relapsing phase) and 50 age-matched controls using a quantitative enzyme-linked immunosorbent assay (ELISA). The mean concentrations of UA in serum was 6.41(±3.18) mg/dL in patients with remitting MS, 4.76(±1.66) mg/dL in patients with relapsing MS and 6.33(±2.94) mg/dL in controls. There was a significant difference between mean UA concentration in relapsing MS and remitting MS ( p < 0.001), and between patients with relapsing MS and controls ( p = 0.002); however, the difference between levels for patients in the remitting phase of MS and the control group was not significant ( p = 0.87). It seems probable that UA has a role in the prevention of disease activity in MS.
Gender issues and the female preponderance in neuromyelitis optica spectrum disorder (NMOSD) have been investigated before, yet the interplay between NMOSD and menstrual characteristics has remained ...unknown. Thus, the aim was to compare menstrual cycle patterns and their symptoms in NMOSD patients and healthy women.
This cross-sectional study was conducted during 2015–2016 in Isfahan, Iran, and included female patients aged>14years with a diagnosis of NMOSD and healthy subjects as controls. Data regarding age at menarche, menstrual characteristics, history of premenstrual syndrome (PMS) and possible perimenstrual symptoms were collected. Also, NMOSD patients were asked to report changes in their menstrual cycles after onset of the disorder.
The final study population included 32 NMOSD and 33 healthy controls. These groups did not differ regarding their demographics (P>0.05), and age at menarche in the NMOSD and control groups was 13.31±1.49 years and 13.48±1.44 years, respectively (P=0.637). The controls experienced PMS more frequently (78.8% vs. 40.6% in the NMOSD patients; P=0.03), with no significant differences in other menstrual features between groups (P>0.05). However, changes in menstruation after NMOSD onset were reported by 43.8% of patients, with an increase in menstrual irregularities from 15.6% to 43.7% (P=0.012); other menstrual characteristics did not differ after disease onset (P>0.05).
Menstruation do not differ between healthy controls and NMOSD patients before the onset of disease whereas, after its onset, those affected experienced more irregularities in their menstrual cycles. This may be an effect of NMOSD and its underlying disorders on menstruation and suggests that further interventions may be required for affected women.
Several machine learning studies have used optical coherence tomography (OCT) for multiple sclerosis (MS) classification with promising outcomes. Infrared reflectance scanning laser ophthalmoscopy ...(IR-SLO) captures high-resolution fundus images, commonly combined with OCT for fixed B-scan positions. However, no machine learning research has utilized IR-SLO images for automated MS diagnosis.PurposeSeveral machine learning studies have used optical coherence tomography (OCT) for multiple sclerosis (MS) classification with promising outcomes. Infrared reflectance scanning laser ophthalmoscopy (IR-SLO) captures high-resolution fundus images, commonly combined with OCT for fixed B-scan positions. However, no machine learning research has utilized IR-SLO images for automated MS diagnosis.This study utilized a dataset comprised of IR-SLO images and OCT data from Isfahan, Iran, encompassing 32 MS and 70 healthy individuals. A number of convolutional neural networks (CNNs)-namely, VGG-16, VGG-19, ResNet-50, ResNet-101, and a custom architecture-were trained with both IR-SLO images and OCT thickness maps as two separate input datasets. The highest performing models for each modality were then integrated to create a bimodal model that receives the combination of OCT thickness maps and IR-SLO images. Subject-wise data splitting was employed to prevent data leakage among training, validation, and testing sets.MethodsThis study utilized a dataset comprised of IR-SLO images and OCT data from Isfahan, Iran, encompassing 32 MS and 70 healthy individuals. A number of convolutional neural networks (CNNs)-namely, VGG-16, VGG-19, ResNet-50, ResNet-101, and a custom architecture-were trained with both IR-SLO images and OCT thickness maps as two separate input datasets. The highest performing models for each modality were then integrated to create a bimodal model that receives the combination of OCT thickness maps and IR-SLO images. Subject-wise data splitting was employed to prevent data leakage among training, validation, and testing sets.Overall, images of the 102 patients from the internal dataset were divided into test, validation, and training subsets. Subsequently, we employed a bootstrapping approach on the training data through iterative sampling with replacement. The performance of the proposed bimodal model was evaluated on the internal test dataset, demonstrating an accuracy of 92.40% ± 4.1% (95% confidence interval CI, 83.61-98.08), sensitivity of 95.43% ± 5.75% (95% CI, 83.71-100.0), specificity of 92.82% ± 3.72% (95% CI, 81.15-96.77), area under the receiver operating characteristic (AUROC) curve of 96.99% ± 2.99% (95% CI, 86.11-99.78), and area under the precision-recall curve (AUPRC) of 97.27% ± 2.94% (95% CI, 86.83-99.83). Furthermore, to assess the model generalization ability, we examined its performance on an external test dataset following the same bootstrap methodology, achieving promising results, with accuracy of 85.43% ± 0.08% (95% CI, 71.43-100.0), sensitivity of 97.33% ± 0.06% (95% CI, 83.33-100.0), specificity of 84.6% ± 0.10% (95% CI, 71.43-100.0), AUROC curve of 99.67% ± 0.02% (95% CI, 95.63-100.0), and AUPRC of 99.65% ± 0.02% (95% CI, 94.90-100.0).ResultsOverall, images of the 102 patients from the internal dataset were divided into test, validation, and training subsets. Subsequently, we employed a bootstrapping approach on the training data through iterative sampling with replacement. The performance of the proposed bimodal model was evaluated on the internal test dataset, demonstrating an accuracy of 92.40% ± 4.1% (95% confidence interval CI, 83.61-98.08), sensitivity of 95.43% ± 5.75% (95% CI, 83.71-100.0), specificity of 92.82% ± 3.72% (95% CI, 81.15-96.77), area under the receiver operating characteristic (AUROC) curve of 96.99% ± 2.99% (95% CI, 86.11-99.78), and area under the precision-recall curve (AUPRC) of 97.27% ± 2.94% (95% CI, 86.83-99.83). Furthermore, to assess the model generalization ability, we examined its performance on an external test dataset following the same bootstrap methodology, achieving promising results, with accuracy of 85.43% ± 0.08% (95% CI, 71.43-100.0), sensitivity of 97.33% ± 0.06% (95% CI, 83.33-100.0), specificity of 84.6% ± 0.10% (95% CI, 71.43-100.0), AUROC curve of 99.67% ± 0.02% (95% CI, 95.63-100.0), and AUPRC of 99.65% ± 0.02% (95% CI, 94.90-100.0).Incorporating both modalities improves the performance of automated diagnosis of MS, showcasing the potential of utilizing IR-SLO as a complementary tool alongside OCT.ConclusionsIncorporating both modalities improves the performance of automated diagnosis of MS, showcasing the potential of utilizing IR-SLO as a complementary tool alongside OCT.Should the results of our proposed bimodal model be validated in future work with larger and more diverse datasets, diagnosis of MS based on both OCT and IR-SLO can be reliably integrated into routine clinical practice.Translational RelevanceShould the results of our proposed bimodal model be validated in future work with larger and more diverse datasets, diagnosis of MS based on both OCT and IR-SLO can be reliably integrated into routine clinical practice.
Every patient diagnosed with definite multiple sclerosis (MS) should begin disease modifying therapies. Cinnomer
contains 40 mg glatiramer acetate (GA) and is available in prefilled syringes and ...autoinjector devices.
A phase IV multicenter study was conducted to explore the safety and effectiveness of Cinnomer
in the treatment of MS. Study-related data were collected for 14 months.
Totally, 368 Iranian relapsing-remitting MS patients in nine cities were enrolled. The patients were either treatment naïve (n=191) or switchers (n=177). Cinnomer
treatment was associated with a significant reduction in annual relapse rate (ARR) (RR: 0.65, 95% CI: 0.43, 0.98). Final mean Expanded Disability Status Scale (EDSS) scores showed improvement from baseline (difference: -0.21, 95% confidence interval (CI): -0.34, -0.08). There was a significant decrease in gad-enhancing lesions during treatment (difference: -0.38, 95% CI: -0.64, -0.12). The mean score for the depression measure (21-item BDI-II questionnaire) significantly improved (difference: -2.39, 95% CI: -3.74, -1.03). There was a significant change in the "psychological well-being" dimension (
=0.02) (in line with BDI-II scores) and "rejection" MusiQoL dimensions (
=0.04). The adverse events documented throughout the study were not unexpected for GA and were principally not serious.
Safety measures were in line with the known profiles of GA. The results suggest that Cinnomer
is effective with respect to clinical outcomes and from the patient's perspective and in reducing MRI-measured MS activity.
The prevalence of familial MS (FMS) in Iran was 19% which is higher than the global prevalence estimated in recent studies. Considering the complex nature of multiple sclerosis (MS) and the role of ...genetics in the susceptibility of the disease, consanguineous marriage might be a predisposing factor for familial history of MS and its associated multifactorial complications.
Taking into consideration that only a few small-scale studies have addressed this topic, this study aimed to assess the rate of parental consanguinity (PC) and its potential clinical impacts among FMS patients in different geographical regions of Iran with various ethnicities.
This cross-sectional registry-based study was performed on nationwide MS registry of Iran (NMSRI) data collected from 2018 to 2022, especially data relevant to FMS patients. Using a standard questionnaire, baseline characteristics, clinical presentations and symptoms, diagnostic and treatments at regional and national levels were registered. Telephone follow up were implemented by trained registrars to collect parental consanguinity among 2847 FMS. SPSS26 was used for all analysis. Statistical significance was set at P-value < 0.05.
The data of 1909 FMS patients, 1441 (75.5%) females and 468 (24.5%) males with mean age (SD) of 37.08 ± 9.55, from 11 provinces of Iran were evaluated. Of these, 358 cases reported having PC (18.8%) and 1551 cases were non-PC families (81.2%). The former was much more among females than males (75.7% vs 24.3%, respectively). Remarkably, marriage between two first-degree was the most frequent type of PC (107 cases, 5.6%). Further, the mean age (SD) of disease onset was 28.92 ± 8.73 years. The mean age (SD) of MS onset in PC was 28.39 years ± 8.28 and in non-PC was 29.05 ± 8.82 years, respectively (P_value = 0.20). The most common form of the disease was relapsing-remitting MS (73.1%) which was followed by secondary-progressive MS (12.7%). However, PRMS is the rarest form among cases (0.8%). There was not a significant difference in the mean Expanded Disability Status Scale (EDSS) scores between PC and non-PC families (2.16 vs. 2.15, P-value = 0.9).
Overall, our results indicate the highest rate of FMS in Tehran and Isfahan (Persians ethnicity), as the developed and industrial cities provinces with high rates of parental consanguinity among patients.
Multiple sclerosis (MS) mainly affects young women which may be important since having the disease may affect the desire of the sufferers to get pregnant; and on the other hand, pregnancy may change ...the disability status as it changes the hormonal and pharmacological equilibrium. Therefore, we aimed to investigate the impact of basic and reproductive characteristics (i.e., pregnancy history and outcomes in both pre- and post-MS periods) on the pregnancy tendency and the level of disability caused by MS (i.e. through Expanded Disability Status Scale (EDSS) in affected Iranian women.
A secondary data analysis was done on the data gathered through the nationwide MS registry of Iran (NMSRI) from 2018 to 2021. NMSRI is the official MS registry of Iran holding a standardized minimum data set on Iranian patients with MS (PwMS) including demographics, clinical presentations, types of MS, diagnostic and treatments, reproductive and pregnancy history, and EDDS scores. All aforementioned data were registered by trained neurologists with sufficient quality checks in multiple steps. An EDSS cut-off point of 3.5-4 was determined to differentiate mild MS cases from others . All the steps taken were in complete adherence with the tenets of the declaration of Helsinki.
Among 5349 PwMS registered in NMSRI, 914 were single, while 245 and 3070 did not have pregnancy and EDSS data, respectively. Thus, 1120 patients with a mean age of 34.2, and disease duration of 6 years were included in the analysis. Age at diagnosis (P=0.02), age at study time and disease duration (P<0.001) had significant associations with MS type. Patients tend to have more pregnancies, parities and abortions (P<0.001) in the pre-MS period. Regarding chronic diseases, hypertension, diabetes, cardiovascular diseases, and hypothyroidism were more prevalent after MS diagnosis. An abortion history before MS diagnosis was associated with EDSS score ≥ 4 (OR: 2.05; P=0.035). Furthermore, EDSS scores were significantly higher in patients with pregnancy or abortion history in the post-MS period (P= 0.02 and 0.04, respectively); however, setting the EDSS cut-off wiped the association out. There was also a decreasing trend of abortions in PwMS who had an EDSS score ≥ 4 (OR: 2.34; P=0.015).
Pregnancy, parity and abortion may affect the disability in PwMS regardless of their current, first symptoms and diagnosis age and MS type. Besides, the chance of parity may be affected by a higher disability score, which should be considered in the clinical setting.
Summary
Cerebral phaeohyphomycosis is frequently a fatal disease caused by truly neurotropic dematiaceous fungi. Although rare, this infection occurs especially among immunocompetent patients, and ...the clinical symptoms are often misdiagnosed as a cerebral tumour or bacterial brain abscess. The appropriate diagnosis and therapy of cerebral infections by melanized fungi are very challenging if they are caused by mysterious fungi with unknown ecological niche. We reported the second case of cerebral phaeohyphomycosis due to Rhinocladiella mackenziei in Iran and the first culture‐confirmed case. In this report, the differential diagnosis and histopathological findings are discussed and a review of the literature is provided.
The prevalence of multiple sclerosis (MS) shows considerable variability all over the world. According to Kurtzke, Iran is considered to have a low prevalence.
To estimate the period prevalence and ...risk factors of MS in Isfahan, central part of Iran.
A cross-sectional case register study conducted between 2004 and 2005. In the province of Isfahan, Iran, all patients known to have definite MS during 2004 and 2005, being alive and resident within Isfahan as well as being a member of the Isfahan MS Association were included in the study. Demographic and case-related information was recorded. 1,391 definite MS patients (308 men and 1,083 women) from the Isfahan MS Association, Iran, have been identified. The disease was confirmed using clinical information and MRI findings by a neurologist and radiologist. The patients were evaluated by interview and a questionnaire. Population data were obtained from the year 1999 Iran Census. The mean (SD) age of the participants was 32.5 (9.3) years with a mean (SD) duration of the disease of 6.4 (5.1) years for men and 6.9 (5.3) years for women.
The period prevalence of MS was 35.5 per 100,000 95% confidence interval (CI) 33.6-37.3 in a population of 3,923,255, with a higher rate in women than men 54.5 (95% CI: 51.1-57.8) for women and 14.9 (95% CI: 13.3-16.6) for men. The female/male ratio was 3.6 (95% CI: 3.2-4.1). The direct age-adjusted period prevalence was 59.5 per 100,000 (95% CI: 44.8-75.2) for women and 17.0 per 100,000 (95% CI: 8.9-25.1) for men. MS rates were highest among 30- to 39-year-olds and decreased with increasing age. Sensory and visual disturbances were the most common initial presentations with a prevalence of 51.1% (95% CI: 48.4-53.7) and 47.0% (95% CI: 44.4-49.7), respectively.
Isfahan could be considered as an area with a medium to high risk of MS. This is in sharp contrast with the gradient hypothesis.
The time to diagnosis of multiple sclerosis (MS) is of great importance for early treatment, thereby reducing the disability and burden of the disease. The purpose of this study was to determine the ...time from the onset of clinical symptoms to the diagnosis of MS and to evaluate the factors associated with a late diagnosis in Iranian MS patients.
The present cross-sectional study was conducted on patients with MS who were registered in the National MS Registry System of Iran (NMSRI).
Overall, 23291 MS patients registered in 18 provinces of Iran were included in this study. The mean (standard deviation) interval between the onset of the disease and diagnosis of MS was 13.42 (32.40) months, and the median was one month. The diagnostic interval of 41.6% of patients was less than one month, and 14.8% of them had a one-month time to diagnosis. Patients with an age of onset below 18 years and those diagnosed after the age of 50 years had a longer time to diagnosis (P<0.001). Patients with primary progressive MS (PPMS) had the longest time to diagnose and those with relapsing-remitting MS (RRMS) had the shortest time (P<0.001). The results of negative binominal regression showed that the average rate of delay in diagnosis in women was 12% less than that in men. The average delay in diagnosis in patients with a positive family history of MS was 23% more than that in others. The rate of delay in the diagnosis of patients with PPMS and secondary progressive MS was 2.22 and 1.66 times higher, respectively, compared with RRMS.
The findings of the present study revealed that more than half of the MS patients were diagnosed within a one-month interval from the symptom onset, which is an acceptable period. More attention should be paid to patients’ access to medical facilities and MS specialists.
•The mean time from clinical symptoms onset to diagnosis of MS was 13.42 months.•in cases registered in the National MS Registry of Iran.•More than half of the MS cases were diagnosed within one-month interval.•Age at symptoms onset, age at the time of diagnosis, male sex and type of MS.•were associated factors to a late diagnosis in Iranian MS subjects.
