Evaluation of transorbital sonography measures of optic nerve diameter in the context of global and regional brain volume in multiple sclerosis.

Transorbital sonography (TOS) could be a swift and convenient method to detect the atrophy of the optic nerve, possibly providing a marker that might reflect other quantitative structural markers of multiple sclerosis (MS). Here we evaluate the utility of TOS as a complementary tool for assessing optic nerve atrophy, and investigate how TOS-derived measures correspond to volumetric brain markers in MS. We recruited 25 healthy controls (HC) and 45 patients with relapsing-remitting MS and performed B-mode ultrasonographic examination of the optic nerve. Patients additionally underwent MRI scans to obtain T1-weighted, FLAIR and STIR images. Optic nerve diameters (OND) were compared between HC, MS patients with and without history of optic neuritis (non-ON) using a mixed-effects ANOVA model. The relationship between within-subject-average OND and global and regional brain volumetric measures was investigated using FSL SIENAX, voxel-based morphometry and FSL FIRST. OND was significantly different between HC-MS (HC = 3.2 ± 0.4 mm, MS = 3 ± 0.4 mm; p < 0.019) and we found significant correlation between average OND and normalised whole brain (ß = 0.42, p < 0.005), grey matter (ß = 0.33, p < 0.035), white matter (ß = 0.38, p < 0.012) and ventricular cerebrospinal fluid volume (ß = - 0.36, p < 0.021) in the MS group. History of ON had no impact on the association between OND and volumetric data. In conclusion, OND is a promising surrogate marker in MS, that can be simply and reliably measured using TOS, and its derived measures correspond to brain volumetric measures. It should be further explored in larger and longitudinal studies.

Modulation of cortical resting state functional connectivity during a visuospatial attention task in Parkinson's disease.

Visual dysfunction is a recognized early symptom of Parkinson's disease (PD) that partly scales motor symptoms, yet its background is heterogeneous. With additional deficits in visuospatial attention, the two systems are hard to disentangle and it is not known whether impaired functional connectivity in the visual cortex is translative in nature or disrupted attentional modulation also contributes. In this study, we investigate functional connectivity modulation during a visuospatial attention task in patients with PD. In total, 15 PD and 16 age-matched healthy controls performed a visuospatial attention task while undergoing fMRI, in addition to a resting-state fMRI scan. Tensorial independent component analysis was used to investigate task-related network activity patterns. Independently, an atlas-based connectivity modulation analysis was performed using the task potency method. Spearman's rank correlation was calculated between task-related network expression, connectivity modulation, and clinical characteristics. Task-related networks including mostly visual, parietal, and prefrontal cortices were expressed to a significantly lesser degree in patients with PD (p < 0.027). Resting-state functional connectivity did not differ between the healthy and diseased cohorts. Connectivity between the precuneus and ventromedial prefrontal cortex was modulated to a higher degree in patients with PD (p < 0.004), while connections between the posterior parietal cortex and primary visual cortex, and also the superior frontal gyrus and opercular cortex were modulated to a lesser degree (p < 0.001 and p < 0.011). Task-related network expression and superior frontal gyrus-opercular cortex connectivity modulation were significantly associated with UPDRSIII motor scores and the Hoehn-Yahr stages (R = -0.72, p < 0.006 and R = -0.90, p < 0.001; R = -0.68, p < 0.01 and R = -0.71, p < 0.007). Task-related networks function differently in patients with PD in association with motor symptoms, whereas impaired modulation of visual and default-mode network connectivity was not correlated with motor function.

Reproducibility of Lesion Count in Various Subregions on MRI Scans in Multiple Sclerosis.

Purpose: Lesion number and burden can predict the long-term outcome of multiple sclerosis, while the localization of the lesions is also a good predictive marker of disease progression. These biomarkers are used in studies and in clinical practice, but the reproducibility of lesion count is not well-known. Methods: In total, five raters evaluated T2 hyperintense lesions in 140 patients with multiple sclerosis in six localizations: periventricular, juxtacortical, deep white matter, infratentorial, spinal cord, and optic nerve. Black holes on T1-weighted images and brain atrophy were subjectively measured on a binary scale. Reproducibility was measured using the intraclass correlation coefficient (ICC). ICCs were also calculated for the four most accurate raters to see how one outlier can influence the results. Results: Overall, moderate reproducibility (ICC 0.5-0.75) was shown, which did not improve considerably when the most divergent rater was excluded. The areas that produced the worst results were the optic nerve region (ICC: 0.118) and atrophy judgment (ICC: 0.364). Comparing high- and low-lesion burdens in each region revealed that the ICC is higher when the lesion count is in the mid-range. In the periventricular and deep white matter area, where lesions are common, higher ICC was found in patients who had a lower lesion count. On the other hand, juxtacortical lesions and black holes that are less common showed higher ICC when the subjects had more lesions. This difference was significant in the juxtacortical region when the most accurate raters compared patients with low (ICC: 0.406 CI: 0.273-0.546) and high (0.702 CI: 0.603-0.785) lesion loads. Conclusion: Lesion classification showed high variability by location and overall moderate reproducibility. The excellent range was not achieved, owing to the fact that some areas showed poor performance. Hence, putting effort toward the development of artificial intelligence for the evaluation of lesion burden should be considered.

Functional Connectivity Lateralisation Shift of Resting State Networks is Linked to Visuospatial Memory and White Matter Microstructure in Relapsing-Remitting Multiple Sclerosis.

Laterality patterns of resting state networks (RSN) change in various neuropsychiatric conditions. Multiple sclerosis (MS) causes neuro-cognitive symptoms involving dysfunctional large-scale brain networks. Yet, whether healthy laterality patterns of RSNs are maintained in MS and whether altered laterality patterns explain disease symptoms has not been explicitly investigated. We analysed functional MRI and diffusion tensor imaging data from 24 relapsing-remitting MS patients and 25 healthy participants. We performed group-level independent component analysis and used dual regression to estimate individual versions of well-established RSNs. Voxelwise laterality indices were calculated for each RSN. Group differences were assessed via a general linear model-based approach. The relationship between functional laterality and white matter microstructural asymmetry was assessed using Tract-Based Spatial Statistics. Spearman's correlation was calculated between laterality indices and Brief International Cognitive Assessment for Multiple Sclerosis scores. Functional laterality of the dorsal attention network showed a significant leftward shift in the MS group in the posterior intraparietal sulcus (p < 0.033). Default-mode network laterality showed a significant leftward shift in the MS group in the angular gyrus (p < 0.005). Diminished dorsal attention network laterality was associated with increased fractional anisotropy asymmetry in the superior longitudinal fasciculus (p < 0.02). In the default-mode network, leftward laterality of the angular gyrus was associated with higher BVMT-R scores (R = - 0.52, p < 0.023). Our results confirm previous descriptions of RSN dysfunction in relapsing-remitting MS and show that altered functional connectivity lateralisation patterns of RSNs might contibute to cognitive performance and structural remodellation even in patients with mild clinical symptoms.

Connection between microstructural alterations detected by diffusion MRI and cognitive dysfunction in MS: A model-free analysis approach.

BACKGROUND: Cognitive decline is a prominent symptom of MS. Clear connection between cognitive status and white matter microstructural changes has not been unequivocally observed to date. OBJECTIVE: To characterise the relationship between white matter microstructure and cognitive performance a partial least squares (PLS) approach was used. METHODS: 53 RR MS patients' T1 and DTI images and BICAMS subtests were used in our analysis. Standard FSL pipeline was used to obtain diffusion parameters. A PLS approach was applied to reveal the diffusion parameter patterns responsible for the cognitive dysfunction. RESULTS: The first latent variable (LV) was mainly associated with demyelination, while the second and third explained axonal damage. While the first two LV represented mainly Brief Visuospatial Memory Test (BVMT) and Single Digit Modality Test (SDMT), the third LV depicted diffusion alterations mainly the verbal subtest. The first LVs spatial map showed demyelination in the corpus callosum. The second LVs spatial map showed the diffusion alterations in the thalamus. The third LV depicted diffusion alterations in the putative left superior longitudinal fascicle. CONCLUSION: Visual memory demanding tasks versus language functions depend on distinct patterns of diffusion parameters and the spatial organisation. Axial diffusivity alterations, a putative marker of irreversible axonal loss explained around 20% of variability in the cognitive functions.

The effect of lesion location on visuospatial attentional bias in patients with multiple sclerosis.

OBJECTIVE: Lateralization of visuospatial attention in healthy people, known as pseudoneglect, results in leftward bias during the Landmark or line bisection tasks. Cognitive dysfunctions in patients with multiple sclerosis (MS) might affect the visuospatial attentional abilities as well. In this study, we aimed to examine the association between atrophy and lesion location and the extent of lateralization of visuospatial attentional bias in patients with MS. METHOD: Visuospatial attentional bias was measured in 35 relapsing-remitting MS patients using the Landmark task. To evaluate the relation between spatial attentional bias and gray matter atrophy, voxel-based morphometry was performed on T1-weighted magnetic resonance (MR) images. In order to examine the effect of lesion location on visuospatial attentional bias, lesion-symptom mapping was conducted on the manually segmented lesions. RESULTS: The variability of visuospatial attentional bias was higher in MS patients compared to healthy controls (p < .04). Lesion probability mapping showed that lesions located along the left superior longitudinal fascicle are associated with the extent of visuospatial bias (p < .05). No correlation was found between gray matter atrophy and the attentional bias of the patients. CONCLUSIONS: Our results indicate that lesions affecting the integrity of white matter pathways in the fronto-parietal attentional network might be accountable for the higher variability of spatial attentional bias in patients with MS. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Resting-state functional heterogeneity of the right insula contributes to pain sensitivity.

Previous studies have described the structure and function of the insular cortex in terms of spatially continuous gradients. Here we assess how spatial features of insular resting state functional organization correspond to individual pain sensitivity. From a previous multicenter study, we included 107 healthy participants, who underwent resting state functional MRI scans, T1-weighted scans and quantitative sensory testing on the left forearm. Thermal and mechanical pain thresholds were determined. Connectopic mapping, a technique using non-linear representations of functional organization was employed to describe functional connectivity gradients in both insulae. Partial coefficients of determination were calculated between trend surface model parameters summarizing spatial features of gradients, modal and modality-independent pain sensitivity. The dominant connectopy captured the previously reported posteroanterior shift in connectivity profiles. Spatial features of dominant connectopies in the right insula explained significant amounts of variance in thermal (R2 = 0.076; p < 0.001 and R2 = 0.031; p < 0.029) and composite pain sensitivity (R2 = 0.072; p < 0.002). The left insular gradient was not significantly associated with pain thresholds. Our results highlight the functional relevance of gradient-like insular organization in pain processing. Considering individual variations in insular connectopy might contribute to understanding neural mechanisms behind pain and improve objective brain-based characterization of individual pain sensitivity.

Two Classes of T1 Hypointense Lesions in Multiple Sclerosis With Different Clinical Relevance.

Background: Hypointense lesions on T1-weighted images have important clinical relevance in multiple sclerosis patients. Traditionally, spin-echo (SE) sequences are used to assess these lesions (termed black holes), but Fast Spoiled Gradient-Echo (FSPGR) sequences provide an excellent alternative. Objective: To determine whether the contrast difference between T1 hypointense lesions and the surrounding normal white matter is similar on the two sequences, whether different lesion types could be identified, and whether the clinical relevance of these lesions types are different. Methods: Seventy-nine multiple sclerosis patients' lesions were manually segmented, then registered to T1 sequences. Median intensity values of lesions were identified on all sequences, then K-means clustering was applied to assess whether distinct clusters of lesions can be defined based on intensity values on SE, FSPGR, and FLAIR sequences. The standardized intensity of the lesions in each cluster was compared to the intensity of the normal appearing white matter in order to see if lesions stand out from the white matter on a given sequence. Results: 100% of lesions on FSPGR images and 69% on SE sequence in cluster #1 exceeded a standardized lesion distance of Z = 2.3 (p < 0.05). In cluster #2, 78.7% of lesions on FSPGR and only 17.7% of lesions on SE sequence were above this cutoff value, meaning that these lesions were not easily seen on SE images. Lesion count in the second cluster (lesions less identifiable on SE) significantly correlated with the Expanded Disability Status Scale (EDSS) (R: 0.30, p ≤ 0.006) and with disease duration (R: 0.33, p ≤ 0.002). Conclusion: We showed that black holes can be separated into two distinct clusters based on their intensity values on various sequences, only one of which is related to clinical parameters. This emphasizes the joint role of FSPGR and SE sequences in the monitoring of MS patients and provides insight into the role of black holes in MS.

The sensitivity and specificity of chest CT in the diagnosis of COVID-19.

PURPOSE: The identification of patients infected by SARS-CoV-2 is highly important to control the disease; however, the clinical presentation is often unspecific and a large portion of the patients develop mild or no symptoms at all. For this reason, there is an emphasis on evaluating diagnostic tools for screening. Chest CT scans are emerging as a useful tool in the diagnostic process of viral pneumonia cases associated with COVID-19. This review examines the sensitivity, specificity, and feasibility of chest CT in detecting COVID-19 compared with real-time polymerase chain reaction (RT-PCR). METHODS: Sensitivity and specificity of chest CT in detecting COVID-19 in its various phases was compared using RT-PCR as a gold standard. A "reverse calculation approach" was applied and treated chest CT as a hypothetical gold standard and compared RT-PCR to it point out the flaw of the standard approach. RESULTS: High sensitivity (67-100%) and relatively low specificity (25-80%) was reported for the CT scans. However, the sensitivity of RT-PCR was reported to be modest (53-88%), hence cannot serve as an appropriate ground truth. The "reverse calculation approach" showed that CT could have a higher specificity (83-100%) if we consider the modest sensitivity of the RT-PCR. CONCLUSIONS: The sensitivity and specificity of the chest CT in diagnosing COVID-19 and the radiation exposure have to be judged together. Arguments are presented that chest CT scans have added value in diagnosing COVID-19 especially in patients, who exhibit typical clinical symptoms and have negative RT-PCR results in highly infected regions. KEY POINTS: • CT scans have higher specificity if we take into account the low sensitivity of the RT-PCR. • Avoid chest CT as a sole diagnostic approach for COVID-19 infection. • Patients who had negative RT-PCR result with typical clinical symptoms in highly infected regions or with close contact of COVID-19-infected patients; the use of chest CT is warranted.

Altered brain network function during attention-modulated visual processing in multiple sclerosis.

BACKGROUND: Multiple sclerosis may damage cognitive performance in several domains, including attention. Although attention network deficits were described during rest, studies that investigate their function during task performance are scarce. OBJECTIVE: To investigate connectivity within and between task-related networks in multiple sclerosis during a visual attention task as a function of cognitive performance. METHODS: A total of 23 relapsing-remitting multiple sclerosis (RRMS) patients and 29 healthy controls underwent task-functional magnetic resonance imaging (fMRI) scans using a visual attention paradigm on a 3T scanner. Scans were analysed using tensor-independent component analysis (TICA). Functional connectivity was calculated within and between components. We assessed cognitive function with the Brief International Cognitive Assessment for MS (BICAMS) battery. RESULTS: TICA extracted components related to visual processing, attention, executive function and the default-mode network. Subject scores of visual/attention-related and executive components were greater in healthy controls (p < 0.032, p < 0.023). Connectivity between visual/attention-related and default-mode components was higher in patients (p < 0.043), correlating with Brief Visuospatial Memory Test-Revised (BVMT-R) scores (R = -0.48, p < 0.036). Patients showed reduced connectivity between the right intraparietal sulcus (rIPS) and frontal eye field (rFEF), and bilateral frontal eye fields (p < 0.012, p < 0.003). Reduced rIPS-rFEF connectivity came with lower Symbol Digit Modalities Test (SDMT)/BVMT-R scores in patients (R = 0.53, p < 0.02, R = 0.46, p < 0.049). CONCLUSION: Attention-related networks show altered connectivity during task performance in RRMS patients, scaling with cognitive disability.

Brain MRI Diffusion Encoding Direction Number Affects Tract-Based Spatial Statistics Results in Multiple Sclerosis.

BACKGROUND AND PURPOSE: Diffusion tensor imaging (DTI) is a promising approach to detect the underlying brain pathology. These alterations can be seen in several diseases such as multiple sclerosis. Tract-based spatial statistics (TBSS) is an easy to use and robust way for analyzing diffusion data. The effect of acquisition parameters of DTI on TBSS has not been evaluated, especially the number of diffusion encoding directions (NDED), which is directly proportional with scan time. METHODS: We analyzed a large set of DTI data of healthy controls (N = 126) and multiple sclerosis patients (N = 78). The highest NDED (60 directions) was reduced and a tensor calculation was done separately for every subset. We calculated the mean and standard deviation of DTI parameters under the white matter mask. Moreover, the FMRIB Software Library TBSS pipeline was used on DTI images with 15, 30, 45, and 60 directions to compare differences between groups. Mean DTI parameters were compared between groups as a function of NDED. RESULTS: The mean value of FA and AD decreased with increasing number of directions. This was more pronounced in areas with smaller FA values. RD and MD were constant. The skeleton size reduced with elevating NDED along with the number of significant voxels. The TBSS analysis showed significant differences between groups throughout the majority of the skeleton and the group difference was associated with NDED. CONCLUSION: Our results suggested that results of TBSS depended on the NDED, which should be considered when comparing DTI data with varying protocols.

Temporal instability of salience network activity in migraine with aura.

This study aims to investigate whether intranetwork dynamic functional connectivity and causal interactions of the salience network is altered in the interictal term of migraine. Thirty-two healthy controls, 37 migraineurs without aura, and 20 migraineurs with aura were recruited. Participants underwent a T1-weighted scan and resting-state fMRI protocol inside a 1.5T MR scanner. We obtained average spatial maps of resting-state networks using group independent component analysis, which yielded subject-specific time series through a dual regression approach. Salience network regions of interest (bilateral insulae and prefrontal cortices, dorsal anterior cingulate cortex) were obtained from the group average map through cluster-based thresholding. To describe intranetwork connectivity, average and dynamic conditional correlation was calculated. Causal interactions between the default-mode, dorsal attention, and salience network were characterised by spectral Granger's causality. Time-averaged correlation was lower between the right insula and prefrontal cortex in migraine without aura vs with aura and healthy controls (P < 0.038, P < 0.037). Variance of dynamic conditional correlation was higher in migraine with aura vs healthy controls and migraine with aura vs without aura between the right insula and dorsal anterior cingulate cortex (P < 0.011, P < 0.026), and in migraine with aura vs healthy controls between the dorsal anterior cingulate and left prefrontal cortex (P < 0.021). Causality was weaker in the <0.05 Hz frequency range between the salience and dorsal attention networks in migraine with aura (P < 0.032). Overall, migraineurs with aura exhibit more fluctuating connections in the salience network, which also affect network interactions, and could be connected to altered cortical excitability and increased sensory gain.

Are Migraine With and Without Aura Really Different Entities?

Background: Migraine research is booming with the rapidly developing neuroimaging tools. Structural and functional alterations of the migrainous brain were detected with MRI. The outcome of a research study largely depends on the working hypothesis, on the chosen measurement approach and also on the subject selection. Against all evidence from the literature that migraine subtypes are different, most of the studies handle migraine with and without aura as one disease. Methods: Publications from PubMed database were searched for terms of "migraine with aura," "migraine without aura," "interictal," "MRI," "diffusion weighted MRI," "functional MRI," "compared to," "atrophy" alone and in combination. Conclusion: Only a few imaging studies compared the two subforms of the disease, migraine with aura, and without aura, directly. Functional imaging investigations largely agree that there is an increased activity/activation of the brain in migraine with aura as compared to migraine without aura. We propose that this might be the signature of cortical hyperexcitability. However, structural investigations are not equivocal. We propose that variable contribution of parallel, competing mechanisms of maladaptive plasticity and neurodegeneration might be the reason behind the variable results.

Altered Resting State Functional Activity and Microstructure of the White Matter in Migraine With Aura.

Introduction: Brain structure and function were reported to be altered in migraine. Importantly our earlier results showed that white matter diffusion abnormalities and resting state functional activity were affected differently in the two subtypes of the disease, migraine with and without aura. Resting fluctuation of the BOLD signal in the white matter was reported recently. The question arising whether the white matter activity, that is strongly coupled with gray matter activity is also perturbed differentially in the two subtypes of the disease and if so, is it related to the microstructural alterations of the white matter. Methods: Resting state fMRI, 60 directional DTI images and high-resolution T1 images were obtained from 51 migraine patients and 32 healthy volunteers. The images were pre-processed and the white matter was extracted. Independent component analysis was performed to obtain white matter functional networks. The differential expression of the white matter functional networks in the two subtypes of the disease was investigated with dual-regression approach. The Fourier spectrum of the resting fMRI fluctuations were compared between groups. Voxel-wise correlation was calculated between the resting state functional activity fluctuations and white matter microstructural measures. Results: Three white matter networks were identified that were expressed differently in migraine with and without aura. Migraineurs with aura showed increased functional connectivity and amplitude of BOLD fluctuation. Fractional anisotropy and radial diffusivity showed strong correlation with the expression of the frontal white matter network in patients with aura. Discussion: Our study is the first to describe changes in white matter resting state functional activity in migraine with aura, showing correlation with the underlying microstructure. Functional and structural differences between disease subtypes suggest at least partially different pathomechanism, which may necessitate handling of these subtypes as separate entities in further studies.

Gray Matter Atrophy to Explain Subclinical Oculomotor Deficit in Multiple Sclerosis.

Eye movement deficits are frequently noted in multiple sclerosis during bedside clinical examination, but subtle dysfunction may remain undetected and might only be identified with advanced approaches. While classical neurology provides insight into the complex functional anatomy of oculomotor functions, little is known about the structural background of this dysfunction in MS. Thirty four clinically stable, treated relapsing-remitting MS patients with mild disability and 34 healthy controls were included in our study. Group difference and correlation with clinical parameters were analyzed in case of the latency, peak-velocity, gain, dysconjugacy index, and performance during a saccade and anti-saccade task. High-resolution T1 weighted, T2 FLAIR, and double inversion recovery images were acquired on 3T to evaluate the correlation between behavioral and MRI parameters, such as T2 lesion and T1 black-hole burden, global brain, gray, and white matter atrophy. VBM style analysis was used to identify the focal gray matter atrophy responsible for oculomotor dysfunction. Significantly increased latency in the prosaccade task and significantly worse performance in the anti-saccade task were found in MS patients. The detailed examination of conjugated eye movements revealed five subclinical internuclear ophthalmoparesis cases. The peak velocity and latency of the anti-saccade movement correlated with the number of black holes, but none of the eye movement parameters were associated with the T2 lesion burden or location. Global gray matter volume correlated with saccade and anti-saccade latency, whereas white matter and total brain volume did not. Local gray matter atrophy in the left inferio-parietal lobule and temporo-occipital junction correlated with anti-saccade peak velocity. Our results show that neurodegeneration-like features of the MRI (black-hole, gray matter atrophy) are the best predictors of eye movement deficit in MS. Concurring with the clinico-radiological paradox, T2 lesion burden cannot explain the behavioral results. Importantly, anti-saccade peak velocity correlates with gray matter atrophy in the left parietal regions, which are frequently implicated in attention tasks.