Objective biomarkers of depression: A study of Granger causality and wavelet coherence in resting-state fMRI.

BACKGROUND AND PURPOSE: The lack of a robust diagnostic biomarker makes understanding depression from a neurobiological standpoint an important goal, especially in the context of brain imaging. METHODS: In this study, we aim to create novel image-based features for objective diagnosis of depression. Resting-state network time series are used to investigate neurodynamics with the help of wavelet coherence and Granger causality (G-causality). Three new features are introduced: total wavelet coherence, wavelet lead coherence, and wavelet coherence blob analysis. The fourth feature, pair-wise conditional G-causality, is used to establish the causality between resting-state networks. We use the proposed features to classify depression in adult subjects. RESULTS: We obtained an accuracy of 86% in the wavelet lead coherence, 80% in Granger causality, and 86% in wavelet coherence blob analysis. Subjects with depression showed hyperconnectivity between the dorsal attention network and the auditory network as well as between the posterior default mode network and the dorsal attention network. Hypoconnectivity was found between the anterior default mode network and the auditory network as well as the right frontoparietal network and the lateral visual network. An abnormal co-activation pattern was found between cerebellum and the lateral motor network according to the wavelet coherence blob analysis. CONCLUSION: Based on abnormal functional dynamics between brain networks, we were able to identify subjects with depression with high accuracy. The findings of this study contribute to the understanding of the impaired emotional and attention processing associated with depression, as well as decreased motor activity.

In-vitro engineered human cerebral tissues mimic pathological circuit disturbances in 3D.

In-vitro modeling of brain network disorders such as epilepsy remains a major challenge. A critical step is to develop an experimental approach that enables recapitulation of in-vivo-like three-dimensional functional complexity while allowing local modulation of the neuronal networks. Here, by promoting matrix-supported active cell reaggregation, we engineered multiregional cerebral tissues with intact 3D neuronal networks and functional interconnectivity characteristic of brain networks. Furthermore, using a multi-chambered tissue-culture chip, we show that our separated but interconnected cerebral tissues can mimic neuropathological signatures such as the propagation of epileptiform discharges.

The effects of multi-echo fMRI combination and rapid T2*-mapping on offline and real-time BOLD sensitivity.

A variety of strategies are used to combine multi-echo functional magnetic resonance imaging (fMRI) data, yet recent literature lacks a systematic comparison of the available options. Here we compare six different approaches derived from multi-echo data and evaluate their influences on BOLD sensitivity for offline and in particular real-time use cases: a single-echo time series (based on Echo 2), the real-time T2*-mapped time series (T2*FIT) and four combined time series (T2*-weighted, tSNR-weighted, TE-weighted, and a new combination scheme termed T2*FIT-weighted). We compare the influences of these six multi-echo derived time series on BOLD sensitivity using a healthy participant dataset (N = 28) with four task-based fMRI runs and two resting state runs. We show that the T2*FIT-weighted combination yields the largest increase in temporal signal-to-noise ratio across task and resting state runs. We demonstrate additionally for all tasks that the T2*FIT time series consistently yields the largest offline effect size measures and real-time region-of-interest based functional contrasts and temporal contrast-to-noise ratios. These improvements show the promising utility of multi-echo fMRI for studies employing real-time paradigms, while further work is advised to mitigate the decreased tSNR of the T2*FIT time series. We recommend the use and continued exploration of T2*FIT for offline task-based and real-time region-based fMRI analysis. Supporting information includes: a data repository (https://dataverse.nl/dataverse/rt-me-fmri), an interactive web-based application to explore the data (https://rt-me-fmri.herokuapp.com/), and further materials and code for reproducibility (https://github.com/jsheunis/rt-me-fMRI).

7T dynamic contrast-enhanced MRI for the detection of subtle blood-brain barrier leakage.

BACKGROUND AND PURPOSE: Dynamic contrast-enhanced MRI (DCE-MRI) can be employed to assess the blood-brain barrier (BBB) integrity. Detection of BBB leakage at lower field strengths (≤3T) is cumbersome as the signal is noisy, while leakage can be subtle. Utilizing the increased signal-to-noise ratio at higher field strengths, we explored the application of 7T DCE-MRI for assessing BBB leakage. METHODS: A dual-time resolution DCE-MRI method was implemented at 7T and a slow injection rate (0.3 ml/s) and low dose (3 mmol) served to obtain signal changes linearly related to the gadolinium concentration, that is, minimized for T2* degradation effects. With the Patlak graphical approach, the leakage rate (Ki ) and blood plasma volume fraction (vp ) were calculated. The method was evaluated in 10 controls, an ischemic stroke patient, and a patient with a transient ischemic attack. RESULTS: Ki and vp were significantly higher in gray matter compared to white matter of all participants. These Ki values were higher in both patients compared to the control subjects. Finally, for the lesion identified in the ischemic stroke patient, higher leakage values were observed compared to normal-appearing tissue. CONCLUSION: We demonstrate how a dual-time resolution DCE-MRI protocol at 7T, with administration of half the clinically used contrast agent dose, can be used for assessing subtle BBB leakage. Although the feasibility of DCE-MRI for assessing the BBB integrity at 3T is well known, we showed that a continuous sampling DCE-MRI method tailored for 7T is also capable of assessing leakage with a high sensitivity over a range of Ki values.

Emulative, coherent, and causal dynamics between large-scale brain networks are neurobiomarkers of Accelerated Cognitive Ageing in epilepsy.

Accelerated cognitive ageing (ACA) is an ageing co-morbidity in epilepsy that is diagnosed through the observation of an evident IQ decline of more than 1 standard deviation (15 points) around the age of 50 years old. To understand the mechanism of action of this pathology, we assessed brain dynamics with the use of resting-state fMRI data. In this paper, we present novel and promising methods to extract brain dynamics between large-scale resting-state networks: the emulative power, wavelet coherence, and granger causality between the networks were extracted in two resting-state sessions of 24 participants (10 ACA, 14 controls). We also calculated the widely used static functional connectivity to compare the methods. To find the best biomarkers of ACA, and have a better understanding of this epilepsy co-morbidity we compared the aforementioned between-network neurodynamics using classifiers and known machine learning algorithms; and assessed their performance. Results show that features based on the evolutionary game theory on networks approach, the emulative powers, are the best descriptors of the co-morbidity, using dynamics associated with the default mode and dorsal attention networks. With these dynamic markers, linear discriminant analysis could identify ACA patients at 82.9% accuracy. Using wavelet coherence features with decision-tree algorithm, and static functional connectivity features with support vector machine, ACA could be identified at 77.1% and 77.9% accuracy respectively. Granger causality fell short of being a relevant biomarker with best classifiers having an average accuracy of 67.9%. Combining the features based on the game theory, wavelet coherence, Granger-causality, and static functional connectivity- approaches increased the classification performance up to 90.0% average accuracy using support vector machine with a peak accuracy of 95.8%. The dynamics of the networks that lead to the best classifier performances are known to be challenged in elderly. Since our groups were age-matched, the results are in line with the idea of ACA patients having an accelerated cognitive decline. This classification pipeline is promising and could help to diagnose other neuropsychiatric disorders, and contribute to the field of psychoradiology.

Treatment with Diazepam in Acute Stroke Prevents Poststroke Seizures: A Substudy of the EGASIS Trial.

OBJECTIVE: The frequency of seizures after stroke is high, with a severe impact on the quality of life. However, little is known about their prevention. Therefore, we investigated whether early administration of diazepam prevents the development of seizures in acute stroke patients. METHODS: We performed a substudy of the EGASIS trial, a multicenter double-blind, randomized trial in which acute stroke patients were treated with diazepam or placebo for 3 days. Follow-up was after 2 weeks and 3 months. The occurrence of seizures was registered prospectively as one of the prespecified secondary outcomes. RESULTS: 784 EGASIS patients were eligible for this substudy (389 treated with diazepam [49.6%] and 395 treated with placebo [50.4%]). Seizures were reported in 19 patients (2.4% of the total patient group). Seizures occurred less frequently in patients treated with diazepam (1.5 vs. 3.3% in the placebo group); however, this difference was only statistically significant in patients with a cortical anterior circulation infarction (0.9% in the diazepam group vs. 4.6% in the placebo group, incidence rate ratio 0.20, 95% CI: 0.05-0.78, p = 0.02, NNT = 27). CONCLUSION: We found that a 3-day treatment with diazepam after acute cortical anterior circulation stroke prevents the occurrence of seizures in the first 3 months following stroke.

A Bayesian method for inference of effective connectivity in brain networks for detecting the Mozart effect.

Several studies claim that listening to Mozart music affects cognition and can be used to treat neurological conditions like epilepsy. Research into this Mozart effect has not addressed how dynamic interactions between brain networks, i.e. effective connectivity, are affected. The Granger-causality analysis is often used to infer effective connectivity. First, we investigate if a new method, Bayesian topology identification, can be used as an alternative. Both methods are evaluated on simulation data, where the Bayesian method outperforms the Granger-causality analysis in the inference of connectivity graphs of dynamic networks, especially for short data lengths. In the second part, the Bayesian method is extended to enable the inference of changes in effective connectivity between groups of subjects. Next, we apply both methods to fMRI scans of 16 healthy subjects, who were scanned before and after the exposure to Mozart's sonata K448 at least 2 hours a day for 7 days. Here, we investigate if the effective connectivity of the subjects significantly changed after listening to Mozart music. The Bayesian method detected changes in effective connectivity between networks related to cognitive processing and control in the connection from the central executive to the superior sensori-motor network, in the connection from the posterior default mode to the fronto-parietal right network, and in the connection from the anterior default mode to the dorsal attention network. This last connection was only detected in a subgroup of subjects with a longer listening duration. Only in this last connection, an effect was found by the Granger-causality analysis.

Neurocognitive and behavioural profile in Panayiotopoulos syndrome.

AIM: To determine neurocognitive performance and behavioural problems in children with Panayiotopoulos syndrome. METHOD: All 18 children (10 females, 8 males; mean age 4y 7mo; SD 1y 10mo) diagnosed with Panayiotopoulos syndrome at the Kempenhaeghe Epilepsy Center in the Netherlands between 2010 and 2017 were analysed retrospectively. All underwent a neuropsychological/behavioural assessment, an academic assessment, and a 24-hour electroencephalogram. RESULTS: Mean full-scale IQ (93.5; range 76-123; p=0.04) and performance IQ (93.2; range 76-126; p=0.04) were within the normal range, although significantly lower compared to the normative mean. Verbal IQ (96.3; range 76-118) and processing speed (96.1; range 74-114) were not significantly lower. Simple auditory/visual reaction times, visual attention, visual-motor integration, and verbal memory were significantly lower compared to normative values. On average, patients with Panayiotopoulos syndrome were 8 months behind in arithmetic speed and 11 months behind in reading speed for the number of months in school. Behavioural questionnaires revealed significantly higher scores on reported internalizing behavioural problems. INTERPRETATION: Children with Panayiotopoulos syndrome demonstrated diffuse cognitive dysfunction in full-scale IQ, performance IQ, visual attention, visual-motor integration, and verbal memory. A high incidence of internalizing behavioural problems was reported. This strongly suggests neuropsychological and behavioural comorbidity in children with Panayiotopoulos syndrome. WHAT THIS PAPER ADDS: Children with Panayiotopoulos syndrome are at risk for cognitive deficits in various cognitive domains. Children with Panayiotopoulos syndrome are also prone to internalizing behavioural problems. Mild-to-severe academic underachievement was present in more than half of the children with Panayiotopoulos syndrome.

EEG-based classification of epilepsy and PNES: EEG microstate and functional brain network features.

Epilepsy and psychogenic non-epileptic seizures (PNES) often show over-lap in symptoms, especially at an early disease stage. During a PNES, the electrical activity of the brain remains normal but in case of an epileptic seizure the brain will show epileptiform discharges on the electroencephalogram (EEG). In many cases an accurate diagnosis can only be achieved after a long-term video monitoring combined with EEG recording which is quite expensive and time-consuming. In this paper using short-term EEG data, the classification of epilepsy and PNES subjects is analyzed based on signal, functional network and EEG microstate features. Our results showed that the beta-band is the most useful EEG frequency sub-band as it performs best for classifying subjects. Also the results depicted that when the coverage feature of the EEG microstate analysis is calculated in beta-band, the classification shows fairly high accuracy and precision. Hence, the beta-band and the coverage are the most important features for classification of epilepsy and PNES patients.

Volumetric and Functional Activity Lateralization in Healthy Subjects and Patients with Focal Epilepsy: Initial Findings in a 7T MRI Study.

BACKGROUND AND PURPOSE: In 30% of the patients with focal epilepsy, an epileptogenic lesion cannot be visually detected with structural MRI. Ultra-high field MRI may be able to identify subtle pathology related to the epileptic focus. We set out to assess 7T MRI-derived volumetric and functional activity lateralization of the hippocampus, hippocampal subfields, temporal and frontal lobe in healthy subjects and MRI-negative patients with focal epilepsy. METHODS: Twenty controls and 10 patients with MRI-negative temporal or frontal lobe epilepsy (TLE and FLE, respectively) underwent a 7T MRI exam. T1 -weigthed imaging and resting-state fMRI was performed. T1 -weighted images were segmented to yield volumes, while from fMRI data, the fractional amplitude of low frequency fluctuations was calculated. Subsequently, volumetric and functional lateralization was calculated from left-right asymmetry. RESULTS: In controls, volumetric lateralization was symmetric, with a slight asymmetry of the hippocampus and subiculum, while functional lateralization consistently showed symmetry. Contrarily, in epilepsy patients, regions were less symmetric. In TLE patients with known focus, volumetric lateralization in the hippocampus and hippocampal subfields was indicative of smaller ipsilateral volumes. These patients also showed clear functional lateralization, though not consistently ipsilateral or contralateral to the epileptic focus. TLE patients with unknown focus showed an obvious volumetric lateralization, facilitating the localization of the epileptic focus. Lateralization results in the FLE patients were less consistent with the epileptic focus. CONCLUSION: MRI-derived volume and fluctuation amplitude are highly symmetric in controls, whereas in TLE, volumetric and functional lateralization effects were observed. This highlights the potential of the technique.

Functional brain network characteristics are associated with epilepsy severity in childhood absence epilepsy.

While cognitive impairments are not generally considered to be part of the childhood absence epilepsy (CAE) syndrome, some recent studies report cognitive, mainly attentional, deficits. Here we set out to investigate the whole brain functional network of children with CAE and controls. Furthermore, the possible relation of the functional network abnormalities with epilepsy and neurocognitive characteristics is studied. Seventeen children with childhood CAE (aged 9.2 ±â€¯2.1 years) and 15 controls (aged 9.8 ±â€¯1.8 years) were included. Resting state functional MRI was acquired to study the functional network. Using graph theoretical analysis, three global metrics of the functional network were investigated: the characteristic path length, the clustering coefficient, and the small-worldness. A multivariable linear regression model including age, sex, and subject motion as covariates was used to investigate group differences in the graph metrics. Subsequently, relations of the graph metrics with epilepsy and neurocognitive characteristics were assessed. Longer path lengths, weaker clustering and a lower small-world network topology were observed in children with CAE compared to controls. Moreover, longer path lengths were related to a longer duration of CAE and a higher number of absence seizure per hour. Clustering and small-worldness were not significantly related to epilepsy or neurocognitive characteristics. The organization of the functional network of children with CAE is less efficient compared to controls, and is related to disease duration. These preliminary findings suggest that CAE is associated with alterations in the functional network.

Constructing an Axonal-Specific Myelin Developmental Graph and its Application to Childhood Absence Epilepsy.

BACKGROUND AND PURPOSE: The process of myelination starts in utero around 20 weeks of gestation and continues through adulthood. We first set out to characterize the maturation of the tract-specific myelin content in healthy subjects from childhood (7-12 years) into adulthood (18-32 years). Second, we apply the resulting development graph to children with childhood absence epilepsy (CAE), a pediatric epilepsy that was previously characterized by changes in myelin content. METHODS: In a prospective cross-sectional study, 15 healthy children (7-12 years), 14 healthy adult participants (18-32 years) and 17 children with a clinical diagnosis of CAE (6-12 years) were included. For each participant, diffusion weighted images were acquired to reconstruct bundles of white matter tracts and multi-echo multi-slice GRASE images were acquired for myelin-water estimation. Subsequently, a tract-specific myelin development graph was constructed using the percentual difference in myelin-water content from childhood (12 year) to adulthood (25 year). RESULTS: The graph revealed myelination patterns, where tracts in the central regions myelinate prior to peripheral tracts and intra-hemispheric tracts as well as tracts in the left hemisphere myelinate prior to inter-hemispheric tracts and tracts in the right hemisphere, respectively. No significant differences were found in myelin-water content between children with CAE and healthy children for neither the early developing tracts, nor the tracts that develop in a later stage. However, the difference between the myelin-water of late and early developing tracts is significantly smaller in the children with CAE. CONCLUSION: These results indicate that CAE is associated with widespread neurodevelopmental myelin differences.

On the merits of non-invasive myelin imaging in epilepsy, a literature review.

Myelin is a vital element of normal brain development and structure. Myelination is most prominent during the first two years of life and proceeds until the age of 30. Abnormal myelination is related to several neurological and neuropsychiatric disorders such as Alzheimer's disease and multiple sclerosis. Recently, abnormal myelin content has also been reported in children with epilepsy. Furthermore, more and more literature hints at a link between abnormal myelination and epilepsy, hence it is worthwhile to evaluate the benefits of non-invasive myelin imaging. In this literature review, we provide an overview of the current evidence of myelin abnormalities in epilepsy from imaging and histological studies. After preselection, 21 histological and 21 in vivo imaging studies were identified. Primarily, epilepsy is found to be associated with a reduced myelin content. This review shows that the currently available literature does not provide a complete view into the nature of myelin abnormalities in epilepsy. However, the reported literature is indicative of a relation between the pathophysiology of epilepsy and the myelin content. More studies that apply myelin-specific imaging techniques are needed to determine whether the myelin abnormalities are an underlying cause of epilepsy, or a consequence of the excessive activity in epilepsy.

Indirect frontocingulate structural connectivity predicts clinical response to accelerated rTMS in major depressive disorder

Background: Repetitive transcranial magnetic stimulation (rTMS) is an established treatment for major depressive disorder (MDD), but its clinical efficacy remains rather modest. One reason for this could be that the propagation of rTMS effects via structural connections from the stimulated area to deeper brain structures (such as the cingulate cortices) is suboptimal. Methods: We investigated whether structural connectivity ­ derived from diffusion MRI data ­ could serve as a biomarker to predict treatment response. We hypothesized that stronger structural connections between the patient-specific stimulation position in the left dorsolateral prefrontal cortex (dlPFC) and the cingulate cortices would predict better clinical outcomes. We applied accelerated intermittent theta burst stimulation (aiTBS) to the left dlPFC in 40 patients with MDD. We correlated baseline structural connectivity, quantified using various metrics (fractional anisotropy, mean diffusivity, tract density, tract volume and number of tracts), with changes in depression severity scores after aiTBS. Results: Exploratory results (p < 0.05) showed that structural connectivity between the patient-specific stimulation site and the caudal and posterior parts of the cingulate cortex had predictive potential for clinical response to aiTBS. Limitations: We used the diffusion tensor to perform tractography. A main limitation was that multiple fibre directions within voxels could not be resolved, which might have led to missing connections in some patients. Conclusion: Stronger structural frontocingular connections may be of essence to optimally benefit from left dlPFC rTMS treatment in MDD. Even though the results are promising, further investigation with larger numbers of patients, more advanced tractography algorithms and classic daily rTMS treatment paradigms is warranted. Clinical trial registration: http://clinicaltrials.gov/show/NCT01832805

Correction to: Towards a Better Understanding of Cognitive Deficits in Absence Epilepsy: a Systematic Review and Meta-Analysis.

Due to an error during the editorial phase, a correction regarding Fig. 2 is added to the original article: "Towards a Better Understanding of Cognitive Deficits in Absence Epilepsy: a Systematic Review and Meta-Analysis". Please see below correct Fig. 2.

Towards a Better Understanding of Cognitive Deficits in Absence Epilepsy: a Systematic Review and Meta-Analysis.

Cognition in absence epilepsy (AE) is generally considered undisturbed. However, reports on cognitive deficits in AE in recent years have suggested otherwise. This review systematically assesses current literature on cognitive performance in children with AE. A systematic literature search was performed in Pubmed, Embase, Cochrane and Web of Science. All studies reporting on cognitive performance in children with AE were considered. In total 33 studies were eligible for inclusion. Neuropsychological tests were classified into the following domains: intelligence; executive function; attention; language; motor & sensory-perceptual examinations; visuoperceptual/visuospatial/visuoconstructional function; memory and learning; achievement. Random-effect meta-analyses were conducted by estimating the pooled mean and/or pooling the mean difference in case-control studies. Full-scale IQ in children with AE was estimated at 96.78 (95%CI:94.46-99.10) across all available studies and in case-control studies IQ was on average 8.03 (95%CI:-10.45- -5.61) lower. Verbal IQ was estimated at 97.98 (95%CI:95.80-100.16) for all studies and 9.01 (95%CI:12.11- -5.90) points lower in case-control studies. Performance IQ was estimated at 97.23 (93.24-101.22) for all available studies and 5.32 (95%CI:-8.27-2.36) points lower in case-control studies. Lower performance was most often reported in executive function (cognitive flexibility, planning, and verbal fluency) and attention (sustained, selective and divided attention). Reports on school difficulties, neurodevelopmental problems, and attentional problems were high. In conclusion, in contrast to common beliefs, lower than average neurocognitive performance was noted in multiple cognitive domains, which may influence academic and psychosocial development.

Lower myelin-water content of the frontal lobe in childhood absence epilepsy.

OBJECTIVE: The frontal lobe in childhood absence epilepsy (CAE) might be affected due to the suggested involvement of the frontal lobe during absence seizures and reports on attentional deficits. Previously, subtle white matter abnormalities have been reported in CAE. However, the impact of one of the most characteristic components of the white matter, the myelin content, remains underdetermined. Therefore, this study investigated whether the myelin content in frontal areas is adversely affected in CAE compared to controls. METHODS: Seventeen children with childhood absence epilepsy (mean age ± standard deviation [SD], 9.2 ± 2.1 years) and 15 age- and sex-matched controls (mean age ± SD, 9.8 ± 1.8 years) underwent neuropsychological assessment and a magnetic resonance imaging (MRI) examination. T2 relaxometry scans were used to distinguish myelin-water from tissue water and to determine the myelin-water fraction (MWF) in the frontal, temporal, parietal, occipital, and insular lobes. A linear regression model including age and sex as covariates was used to investigate group differences. Furthermore, the relationship of MWF with cognitive performance and epilepsy characteristics was determined. RESULTS: The frontal lobe revealed a significantly lower myelin-water content in children with CAE compared to controls over the developmental age range of 6-12 years (5.7 ± 1.0% vs 6.6 ± 1.1%, P = 0.02). This association was not found for any of the other four lobes (P > 0.10). No significant relation was found between myelin-water content and cognitive performance or epilepsy characteristics. SIGNIFICANCE: The lower frontal myelin-water content of children with CAE in comparison with healthy controls probably reflects an altered neurodevelopmental aspect in CAE, of which the underlying mechanisms still need to be unraveled.

Cognitive development in absence epilepsy during long-term follow-up.

Absence epilepsy (AE) has been associated with lower than average cognitive functioning, which are clinically relevant in some and may predispose to problems later in life. This study aimed to assess cognitive development during long-term follow-up in children with AE. Thirty-one children with AE, who had undergone two neuropsychological assessments between 2010 and 2017 were analyzed retrospectively. Cognitive measurements were 1.7 ± 0.95 years apart. The difference in neurocognitive test scores was assessed on a group level and on an individual level using reliable change methodology. Results show that sustained attention was lower at the first measurement compared to the normative mean. Sustained attention improved during follow-up and 7 out of 14 children showed improvement after correction for practice effects. Receptive vocabulary showed a decline over time, but did not differ from the normative mean. Significant lower mean group scores were present for performance IQ, perceptual organization, processing speed, simple reaction times, and visual motor integration, while being stable over time in the majority of children. Cognitive development was not associated with seizure freedom. Mild-to-severe academic underachievement was present in 65% and comorbidities that might affect learning in 38%. This study in children with AE showed improvement in sustained attention during long-term follow-up while other cognitive weaknesses persisted over time, regardless of seizure freedom.

Applicability and reproducibility of 2D multi-slice GRASE myelin water fraction with varying acquisition acceleration.

Non-invasive quantification of the in vivo myelin content may provide valuable information regarding healthy maturation of the brain, as well as insights into demyelination of several neurological disorders. However, these scans are often long thereby limiting acquisition of large brain parts in clinically feasible acquisition times. Therefore, fast acquisition of whole brain myelin content is important. To avoid errors related to slice-selective pulses, most of the previous whole brain studies on myelin content relied on a 3D acquisition. However, multi-slice (2D) acquisition methods are often faster, and less susceptible to motion artifacts. Therefore, multi-slice approaches can be beneficial in a clinical setting. We investigated the applicability and reproducibility of whole brain multi-slice GRASE myelin-water imaging with post-acquisition slice-profile correction in healthy volunteers (aged 25-32y). The applicability was evaluated using the agreement between the multi-slice GRASE and the reference method for myelin-water imaging, single-slice multi spin-echo (MSE) acquisition. Additionally, we assessed the effect of varying acquisition acceleration using parallel imaging on the reproducibility values. First, the multi-slice myelin-water maps showed good agreement with the single-slice reference method, with a bias of at most 1.2% in absolute MWF values. Second, we found an average within-subject coefficient of variation (CoV) of 5.9% and an average intra-class correlation coefficient (ICC) of 0.90 for myelin-water estimation using a multi-slice GRASE sequence without parallel acceleration (scan time 14:06 min), while acquisition with a parallel acceleration factor of 2 resulted in a slightly worse average within-subject CoV of 6.4% and an average ICC of 0.83 at half the scan time. Hence, a multi-slice GRASE acquisition with parallel acceleration factor 2 and a scan time of 7:30 min still provides an excellent reproducibility.

Mood, anxiety, and perceived quality of life in adults with epilepsy and intellectual disability.

OBJECTIVE: Depression and anxiety symptoms are common among patients with epilepsy, but are relatively under-researched in patients with both epilepsy and intellectual disability (ID). The aim was to investigate whether epilepsy and ID characteristics are associated with mood, anxiety, and quality of life. MATERIALS AND METHODS: Adult patients with epilepsy and ID who rely on tertiary epilepsy care were included (N = 189). Mood, anxiety, and quality of life were assessed by standardized questionnaires. Epilepsy and ID characteristics were retrieved from patient charts or determined by psychometric instruments. RESULTS: Elevated levels of depressive and anxiety symptoms were present in 21.7% and 12.7%, respectively. Anxiety was significantly associated with a focal epilepsy type and ID domain discrepancy (substantial difference between two domains of adaptive behavior), but was negatively related to seizure frequency and drug load of mood-stabilizing antiepileptic drugs. Depressive symptoms were not significantly related to epilepsy characteristics, but a severe ID and ID domain discrepancy was associated with more depressive symptoms. Quality of life was significantly worse in those with multiple seizure types and ID domain discrepancy. CONCLUSION: Whereas anxiety and quality of life are associated with individual epilepsy characteristics, this could not be confirmed for depressive symptoms in patients with epilepsy and ID, despite its high prevalence.