3,853 research outputs found

    Cognitive Impairment in Neuromyelitis Optica Spectrum Disorders: A Review of Clinical and Neuroradiological Features

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    Neuromyelitis optica spectrum disorders (NMOSD) are mostly relapsing autoimmune inflammatory disorders of the central nervous system (CNS) with optic neuritis, myelitis, and brainstem syndromes as clinical hallmarks. With a reported prevalence of up to 70%, cognitive impairment is frequent, but often unrecognized and an insufficiently treated burden of the disease. The most common cognitive dysfunctions are decline in attention andmemory performance.Magnetic resonance imaging can be used to access structural correlates of neuropsychological disorders. Cognitive impairment is not only a highly underestimated symptom in patients with NMOSD, but potentially also a clinical correlate of attack-independent changes in NMOSD, which are currently under debate. This article reviews cognitive impairment in NMOSD and discusses associations between structural changes of the CNS and cognitive deficits

    Active contour method for ILM segmentation in ONH volume scans in retinal OCT

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    The optic nerve head (ONH) is affected by many neurodegenerative and autoimmune inflammatory conditions. Optical coherence tomography can acquire high-resolution 3D ONH scans. However, the ONH's complex anatomy and pathology make image segmentation challenging. This paper proposes a robust approach to segment the inner limiting membrane (ILM) in ONH volume scans based on an active contour method of Chan-Vese type, which can work in challenging topological structures. A local intensity fitting energy is added in order to handle very inhomogeneous image intensities. A suitable boundary potential is introduced to avoid structures belonging to outer retinal layers being detected as part of the segmentation. The average intensities in the inner and outer region are then resealed locally to account for different brightness values occurring among the ONH center. The appropriate values for the parameters used in the complex computational model are found using an optimization based on the differential evolution algorithm. The evaluation of results showed that the proposed framework significantly improved segmentation results compared to the commercial solution

    Imaging markers of disability in aquaporin-4 immunoglobulin G seropositive neuromyelitis optica: a graph theory study

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    Neuromyelitis optica spectrum disorders lack imaging biomarkers associated with disease course and supporting prognosis. This complex and heterogeneous set of disorders affects many regions of the central nervous system, including the spinal cord and visual pathway. Here, we use graph theory-based multimodal network analysis to investigate hypothesis-free mixed networks and associations between clinical disease with neuroimaging markers in 40 aquaporin-4-immunoglobulin G antibody seropositive patients (age = 48.16 ± 14.3 years, female:male = 36:4) and 31 healthy controls (age = 45.92 ± 13.3 years, female:male = 24:7). Magnetic resonance imaging measures included total brain and deep grey matter volumes, cortical thickness and spinal cord atrophy. Optical coherence tomography measures of the retina and clinical measures comprised of clinical attack types and expanded disability status scale were also utilized. For multimodal network analysis, all measures were introduced as nodes and tested for directed connectivity from clinical attack types and disease duration to systematic imaging and clinical disability measures. Analysis of variance, with group interactions, gave weights and significance for each nodal association (hyperedges). Connectivity matrices from 80% and 95% F-distribution networks were analyzed and revealed the number of combined attack types and disease duration as the most connected nodes, directly affecting changes in several regions of the central nervous system. Subsequent multivariable regression models, including interaction effects with clinical parameters, identified associations between decreased nucleus accumbens (β = −0.85, P = 0.021) and caudate nucleus (β = −0.61, P = 0.011) volumes with higher combined attack type count and longer disease duration, respectively. We also confirmed previously reported associations between spinal cord atrophy with increased number of clinical myelitis attacks. Age was the most important factor associated with normalized brain volume, pallidum volume, cortical thickness and the expanded disability status scale score. The identified imaging biomarker candidates warrant further investigation in larger-scale studies. Graph theory-based multimodal networks allow for connectivity and interaction analysis, where this method may be applied in other complex heterogeneous disease investigations with different outcome measures

    Reliability of Intra-Retinal Layer Thickness Estimates

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    Purpose Measurement of intra-retinal layer thickness using optical coherence tomography (OCT) has become increasingly prominent in multiple sclerosis (MS) research. Nevertheless, the approaches used for determining the mean layer thicknesses vary greatly. Insufficient data exist on the reliability of different thickness estimates, which is crucial for their application in clinical studies. This study addresses this lack by evaluating the repeatability of different thickness estimates. Methods Studies that used intra-retinal layer segmentation of macular OCT scans in patients with MS were retrieved from PubMed. To investigate the repeatability of previously applied layer estimation approaches, we generated datasets of repeating measurements of 15 healthy subjects and 13 multiple sclerosis patients using two OCT devices (Cirrus HD-OCT and Spectralis SD-OCT). We calculated each thickness estimate in each repeated session and analyzed repeatability using intra-class correlation coefficients and coefficients of repeatability. Results We identified 27 articles, eleven of them used the Spectralis SD-OCT, nine Cirrus HD-OCT, two studies used both devices and two studies applied RTVue-100. Topcon OCT-1000, Stratus OCT and a research device were used in one study each. In the studies that used the Spectralis, ten different thickness estimates were identified, while thickness estimates of the Cirrus OCT were based on two different scan settings. In the simulation dataset, thickness estimates averaging larger areas showed an excellent repeatability for all retinal layers except the outer plexiform layer (OPL). Conclusions Given the good reliability, the thickness estimate of the 6mm-diameter area around the fovea should be favored when OCT is used in clinical research. Assessment of the OPL was weak in general and needs further investigation before OPL thickness can be used as a reliable parameter

    Dysphagia Affecting Quality of Life in Cerebellar Ataxia—a Large Survey

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    Dysphagia is a common symptom in neurodegenerative disorders and is generally associated with increased mortality. In the clinical care setting of ataxia patients, no systematical and standardized assessment of dysphagia is employed. Its impact on patients’ health-related quality of life is not well understood. To assess the impact of dysphagia in ataxia patients on diet, body weight, and health-related quality of life. We conducted a large survey using self-reported questionnaires for swallowing-related quality of life (Swal-QOL) and a food frequency list in combination with retrospective clinical data of 119 patients with cerebellar ataxia treated in the neurological outpatient clinic of a large German university hospital. Seventeen percent of ataxia patients suffered from dysphagia based on the Swal-QOL score. Less than 1% of all patients reported dysphagia as one of their most disabling symptoms. Dysphagia was associated with unintentional weight loss (p = 0.02) and reduced health-related quality of life (p = 0.01) but did not affect individual nutritional habits (p > 0.05; Chi-squared test). Dysphagia is a relevant symptom in cerebellar ataxia. A systematic screening for dysphagia in patients with cerebellar ataxia would be desirable to enable early diagnosis and treatment

    Uncovering convolutional neural network decisions for diagnosing multiple sclerosis on conventional MRI using layer-wise relevance propagation

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    Machine learning-based imaging diagnostics has recently reached or even superseded the level of clinical experts in several clinical domains. However, classification decisions of a trained machine learning system are typically non-transparent, a major hindrance for clinical integration, error tracking or knowledge discovery. In this study, we present a transparent deep learning framework relying on convolutional neural networks (CNNs) and layer-wise relevance propagation (LRP) for diagnosing multiple sclerosis (MS). MS is commonly diagnosed utilizing a combination of clinical presentation and conventional magnetic resonance imaging (MRI), specifically the occurrence and presentation of white matter lesions in T2-weighted images. We hypothesized that using LRP in a naive predictive model would enable us to uncover relevant image features that a trained CNN uses for decision-making. Since imaging markers in MS are well-established this would enable us to validate the respective CNN model. First, we pre-trained a CNN on MRI data from the Alzheimer's Disease Neuroimaging Initiative (n = 921), afterwards specializing the CNN to discriminate between MS patients and healthy controls (n = 147). Using LRP, we then produced a heatmap for each subject in the holdout set depicting the voxel-wise relevance for a particular classification decision. The resulting CNN model resulted in a balanced accuracy of 87.04% and an area under the curve of 96.08% in a receiver operating characteristic curve. The subsequent LRP visualization revealed that the CNN model focuses indeed on individual lesions, but also incorporates additional information such as lesion location, non-lesional white matter or gray matter areas such as the thalamus, which are established conventional and advanced MRI markers in MS. We conclude that LRP and the proposed framework have the capability to make diagnostic decisions of..

    Pain in AQP4-IgG-positive and MOG-IgG-positive neuromyelitis optica spectrum disorders

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    Background: Pain is a frequent symptom in aquaporin-4-immunoglobulin-G-positive neuromyelitis optica spectrum disorders (AQP4-IgG-pos. NMOSD). Data on pain in myelin-oligodendrocyteglycoprotein- immunoglobulin-G autoimmunity with a clinical NMOSD phenotype (MOG-IgG-pos. NMOSD) are scarce. Objective: The objective of this paper is to investigate pain in MOG-IgG-pos. NMOSD, AQP4-IgG-pos. NMOSD and NMOSD without AQP4/MOG-IgG detection (AQP4/MOG-IgG-neg. NMOSD). Methods: Forty-nine MOG-IgG-pos. (n=14), AQP4-IgG-pos. (n=29) and AQP4/MOG-IgG-neg. (n=6) NMOSD patients were included in this cross-sectional baseline analysis from an ongoing observational study. We identified spinal cord lesions on magnetic resonance imaging, assessed pain by the painDETECT and McGill Pain questionnaires, quality of life by Short Form Health Survey, and depression by Beck Depression Inventory. Results: Twelve MOG-IgG-pos. NMOSD patients (86%), 24 AQP4-IgG-pos. NMOSD patients (83%), and all AQP4/MOG-IgG-neg. NMOSD patients (100%) suffered from pain. MOG-IgG-pos. NMOSD patients had mostly neuropathic pain and headache; AQP4-IgG-pos. and AQP4/MOG-IgG-neg. NMOSD patients had mostly neuropathic pain. A history of myelitis was less frequent in MOG-IgGpos. NMOSD than in AQP4-IgG-pos. NMOSD patients. Pain influenced quality of life in all patients. Thirty-six percent of patients with pain received pain medication; none of them were free of pain. Conclusions: Pain is a frequent symptom of patients with MOG-IgG-pos. NMOSD and is as important as in AQP4-IgG-pos. and AQP4/MOG-IgG-neg. NMOSD. Despite its impact on quality of life, pain is insufficiently alleviated by medication

    Quantitative Multi-Parameter Mapping Optimized for the Clinical Routine

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    Using quantitative multi-parameter mapping (MPM), studies can investigate clinically relevant microstructural changes with high reliability over time and across subjects and sites. However, long acquisition times (20 min for the standard 1-mm isotropic protocol) limit its translational potential. This study aimed to evaluate the sensitivity gain of a fast 1.6-mm isotropic MPM protocol including post-processing optimized for longitudinal clinical studies. 6 healthy volunteers (35 +/- 7 years old; 3 female) were scanned at 3T to acquire the following whole-brain MPM maps with 1.6 mm isotropic resolution: proton density (PD), magnetization transfer saturation (MT), longitudinal relaxation rate (R1), and transverse relaxation rate (R2*). MPM maps were generated using two RF transmit field (B1+) correction methods: (1) using an acquired B1+ map and (2) using a data-driven approach. Maps were generated with and without Gibb's ringing correction. The intra-/inter-subject coefficient of variation (CoV) of all maps in the gray and white matter, as well as in all anatomical regions of a fine-grained brain atlas, were compared between the different post-processing methods using Student's t-test. The intra-subject stability of the 1.6-mm MPM protocol is 2-3 times higher than for the standard 1-mm sequence and can be achieved in less than half the scan duration. Intra-subject variability for all four maps in white matter ranged from 1.2-5.3% and in gray matter from 1.8 to 9.2%. Bias-field correction using an acquired B1+ map significantly improved intra-subject variability of PD and R1 in the gray (42%) and white matter (54%) and correcting the raw images for the effect of Gibb's ringing further improved intra-subject variability in all maps in the gray (11%) and white matter (10%). Combining Gibb's ringing correction and bias field correction using acquired B1+ maps provides excellent stability of the 7-min MPM sequence with 1.6 mm resolution suitable for the clinical routine

    Standardization of T1w/T2w Ratio Improves Detection of Tissue Damage in Multiple Sclerosis

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    Normal appearing white matter (NAWM) damage develops early in multiple sclerosis (MS) and continues in the absence of new lesions. The ratio of T1w and T2w (T1w/T2w ratio), a measure of white matter integrity, has previously shown reduced intensity values in MS NAWM. We evaluate the validity of a standardized T1w/T2w ratio (sT1w/T2w ratio) in MS and whether this method is sensitive in detecting MS-related differences in NAWM. T1w and T2w scans were acquired at 3 Tesla in 47 patients with relapsing-remitting MS and 47 matched controls (HC). T1w/T2w and sT1w/T2w ratios were then calculated. We compared between-group variability between T1w/T2w and sT1w/T2w ratio in HC and MS and assessed for group differences. We also evaluated the relationship between the T1w/T2w and sT1w/T2w ratios and clinically relevant variables. Compared to the classic T1w/T2w ratio, the between-subject variability in sT1w/T2w ratio showed a significant reduction in MS patients (0 <. 0.001) and HC < 0.001). However, only sT1w/T2w ratio values were reduced in patients compared to HC (p < 0.001). The sT1w/T2w ratio intensity values were significantly influenced by age, T2 lesion volume and group status (MS vs. HC) (adjusted R-2 = 0.30, p 0.001). We demonstrate the validity of the sT1w/T2w ratio in MS and that it is more sensitive to MS-related differences in NAWM compared to T1w/T2w ratio. The sT1w/T2w ratio shows promise as an easily-implemented measure of NAWM in MS using readily available scans and simple post-processing methods

    a pilot study

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    Muscular weakness in myasthenia gravis (MG) is commonly assessed using Quantitative Myasthenia Gravis Score (QMG). More objective and quantitative measures may complement the use of clinical scales and might detect subclinical affection of muscles. We hypothesized that muscular weakness in patients with MG can be quantified with the non-invasive Quantitative Motor (Q-Motor) test for Grip Force Assessment (QGFA) and Involuntary Movement Assessment (QIMA) and that pathological findings correlate with disease severity as measured by QMG. Methods This was a cross-sectional pilot study investigating patients with confirmed diagnosis of MG. Data was compared to healthy controls (HC). Subjects were asked to lift a device (250 and 500 g) equipped with electromagnetic sensors that measured grip force (GF) and three- dimensional changes in position and orientation. These were used to calculate the position index (PI) and orientation index (OI) as measures for involuntary movements due to muscular weakness. Results Overall, 40 MG patients and 23 HC were included. PI and OI were significantly higher in MG patients for both weights in the dominant and non-dominant hand. Subgroup analysis revealed that patients with clinically ocular myasthenia gravis (OMG) also showed significantly higher values for PI and OI in both hands and for both weights. Disease severity correlates with QIMA performance in the non-dominant hand. Conclusion Q-Motor tests and particularly QIMA may be useful objective tools for measuring motor impairment in MG and seem to detect subclinical generalized motor signs in patients with OMG. Q-Motor parameters might serve as sensitive endpoints for clinical trials in MG
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