Fixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities.

Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "Fixel-Based Analysis" (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities.

Clinical benefit of presurgical EEG-fMRI in difficult-to-localize focal epilepsy: A single-institution retrospective review.

OBJECTIVE: The aim of this report is to present our clinical experience of electroencephalography-functional magnetic resonance imaging (EEG-fMRI) in localizing the epileptogenic focus, and to evaluate the clinical impact and challenges associated with the use of EEG-fMRI in pharmacoresistant focal epilepsy. METHODS: We identified EEG-fMRI studies (n = 118) in people with focal epilepsy performed at our center from 2003 to 2018. Participants were referred from our Comprehensive Epilepsy Program in an exploratory research effort to address often difficult clinical questions, due to complex and difficult-to-localize epilepsy. We assessed the success of each study, the clinical utility of the result, and when surgery was performed, the postoperative outcome. RESULTS: Overall, 50% of EEG-fMRI studies were successful, meaning that data were of good quality and interictal epileptiform discharges were recorded. With an altered recruitment strategy since 2012 with increased inclusion of patients who were inpatients for video-EEG monitoring, we found that this patients in this selected group were more likely to have epileptic discharges detected during EEG-fMRI (96% of inpatients vs 29% of outpatients, P<.0001). To date, 48% (57 of 118) of patients have undergone epilepsy surgery. In 10 cases (17% of the 59 successful studies) the EEG-fMRI result had a "critical impact" on the surgical decision. These patients were difficult to localize because of subtle abnormalities, apparently normal MRI, or extensive structural abnormalities. All 10 had a good seizure outcome at 1 year after surgery (mean follow-up 6.5 years). SIGNIFICANCE: EEG-fMRI results can assist identification of the epileptogenic focus in otherwise difficult-to-localize cases of pharmacoresistant focal epilepsy. Surgery determined largely by localization from the EEG-fMRI result can lead to good seizure outcomes. A limitation of this study is its retrospective design with nonconsecutive recruitment. Prospective clinical trials with well-defined inclusion criteria are needed to determine the overall benefit of EEG-fMRI for preoperative localization and postoperative outcome in focal epilepsy.

Bilateral volume reduction in posterior hippocampus in psychosis of epilepsy.

OBJECTIVE: Psychosis of epilepsy (POE) occurs more frequently in temporal lobe epilepsy, raising the question as to whether abnormalities of the hippocampus are aetiologically important. Despite decades of investigation, it is unclear whether hippocampal volume is reduced in POE, perhaps due to small sample sizes and methodological limitations of past research. METHODS: In this study, we examined the volume of the total hippocampus, and the hippocampal head, body and tail, in a large cohort of patients with POE and patients with epilepsy without psychosis (EC). One hundred adults participated: 50 with POE and 50 EC. Total and subregional hippocampal volumes were manually traced and compared between (1) POE and EC; (2) POE with temporal lobe epilepsy, extratemporal lobe epilepsy and generalised epilepsy; and (3) patients with POE with postictal psychosis (PIP) and interictal psychosis (IP). RESULTS: Compared with EC the POE group had smaller total left hippocampus volume (13.5% decrease, p<0.001), and smaller left hippocampal body (13.3% decrease, p=0.002), and left (41.5% decrease, p<0.001) and right (36.4% decrease, p<0.001) hippocampal tail volumes. Hippocampal head volumes did not differ between groups. CONCLUSION: Posterior hippocampal volumes are bilaterally reduced in POE. Volume loss was observed on a posteroanterior gradient, with severe decreases in the tail and moderate volume decreases in the body, with no difference in the hippocampal head. Posterior hippocampal atrophy is evident to a similar degree in PIP and IP. Our findings converge with those reported for the paradigmatic psychotic disorder, schizophrenia, and suggest that posterior hippocampal atrophy may serve as a biomarker of the risk for psychosis, including in patients with epilepsy.

Fibre-specific white matter reductions in Alzheimer's disease and mild cognitive impairment.

Alzheimer's disease is increasingly considered a large-scale network disconnection syndrome, associated with progressive aggregation of pathological proteins, cortical atrophy, and functional disconnections between brain regions. These pathological changes are posited to arise in a stereotypical spatiotemporal manner, targeting intrinsic networks in the brain, most notably the default mode network. While this network-specific disruption has been thoroughly studied with functional neuroimaging, changes to specific white matter fibre pathways within the brain's structural networks have not been closely investigated, largely due to the challenges of modelling complex white matter structure. Here, we applied a novel technique known as 'fixel-based analysis' to comprehensively investigate fibre tract-specific differences at a within-voxel level (called 'fixels') to assess potential axonal loss in subjects with Alzheimer's disease and mild cognitive impairment. We hypothesized that patients with Alzheimer's disease would exhibit extensive degeneration across key fibre pathways connecting default network nodes, while patients with mild cognitive impairment would exhibit selective degeneration within fibre pathways connecting regions previously identified as functionally implicated early in Alzheimer's disease. Diffusion MRI data from Alzheimer's disease (n = 49), mild cognitive impairment (n = 33), and healthy elderly control subjects (n = 95) were obtained from the Australian Imaging, Biomarkers and Lifestyle study of ageing. We assessed microstructural differences in fibre density, and macrostructural differences in fibre bundle morphology using fixel-based analysis. Whole-brain analysis was performed to compare groups across all white matter fixels. Subsequently, we performed a tract of interest analysis comparing fibre density and cross-section across 11 selected white matter tracts, to investigate potentially subtle degeneration within fibre pathways in mild cognitive impairment, initially by clinical diagnosis alone, and then by including amyloid status (i.e. a positive or negative amyloid PET scan). Our whole-brain analysis revealed significant white matter loss manifesting both microstructurally and macrostructurally in Alzheimer's disease patients, evident in specific fibre pathways associated with default mode network nodes. Reductions in fibre density and cross-section in mild cognitive impairment patients were only exhibited within the posterior cingulum when statistical analyses were limited to tracts of interest. Interestingly, these degenerative changes did not appear to be associated with high amyloid accumulation, given that amyloid-negative, but not positive, mild cognitive impairment subjects exhibited subtle focal left posterior cingulum deficits. The findings of this study demonstrated a stereotypical distribution of white matter degeneration in patients with Alzheimer's disease, which was in line with canonical findings from other imaging modalities, and with a network-based conceptualization of the disease.awx355media15726254535001.

Tract-specific atrophy in focal epilepsy: Disease, genetics, or seizures?

OBJECTIVE: To investigate whether genetics, underlying pathology, or repeated seizures contribute to atrophy in specific white matter tracts. METHODS: Medically refractory unilateral temporal lobe epilepsy (TLE) with hippocampal sclerosis (HS-TLE, n = 26) was studied as an archetype of focal epilepsy, using fixel-based analysis of diffusion-weighted imaging. A genetic effect was assessed in first-degree relatives of HS-TLE subjects who did not have epilepsy themselves (HS-1°Rel; n = 26). The role of disease process was uncovered by comparing HS-TLE to unilateral TLE with normal clinical magnetic resonance imaging (MRI-neg TLE; n = 26, matched for seizure severity). The effect of focal seizures was inferred from lateralized atrophy common to both HS-TLE and MRI-neg TLE, in comparison to healthy controls (n = 76). RESULTS: HS-1 °Rel had bilaterally small hippocampi, but no focal white matter atrophy was detected, indicating a limited effect of genetics. HS-TLE subjects had lateralized atrophy of most temporal lobe tracts, and hippocampal volumes in HS-TLE correlated with parahippocampal cingulum and anterior commissure atrophy, indicating an effect of the underlying pathology. Ipsilateral atrophy of the tapetum, uncinate, and inferior fronto-occipital fasciculus was found in both HS-TLE and MRI-neg TLE, suggesting a common lateralized effect of focal seizures. Both epilepsy groups had bilateral atrophy of the dorsal cingulum and corpus callosum fibers, which we interpret as a consequence of bilateral insults (potentially generalized seizures and/or medications). INTERPRETATION: Underlying pathology, repeated focal seizures, and global insults each contribute to atrophy in specific tracts. Genetic factors make less of a contribution in this cohort. A multifactorial model of white matter atrophy in focal epilepsy is proposed. Ann Neurol 2017;81:240-250.

A Novel Group-Fused Sparse Partial Correlation Method for Simultaneous Estimation of Functional Networks in Group Comparison Studies.

The conventional way to estimate functional networks is primarily based on Pearson correlation along with classic Fisher Z test. In general, networks are usually calculated at the individual-level and subsequently aggregated to obtain group-level networks. However, such estimated networks are inevitably affected by the inherent large inter-subject variability. A joint graphical model with Stability Selection (JGMSS) method was recently shown to effectively reduce inter-subject variability, mainly caused by confounding variations, by simultaneously estimating individual-level networks from a group. However, its benefits might be compromised when two groups are being compared, given that JGMSS is blinded to other groups when it is applied to estimate networks from a given group. We propose a novel method for robustly estimating networks from two groups by using group-fused multiple graphical-lasso combined with stability selection, named GMGLASS. Specifically, by simultaneously estimating similar within-group networks and between-group difference, it is possible to address inter-subject variability of estimated individual networks inherently related with existing methods such as Fisher Z test, and issues related to JGMSS ignoring between-group information in group comparisons. To evaluate the performance of GMGLASS in terms of a few key network metrics, as well as to compare with JGMSS and Fisher Z test, they are applied to both simulated and in vivo data. As a method aiming for group comparison studies, our study involves two groups for each case, i.e., normal control and patient groups; for in vivo data, we focus on a group of patients with right mesial temporal lobe epilepsy.

Electrical stimulation of the piriform cortex for the treatment of epilepsy: A review of the supporting evidence.

In this review, we consider how the piriform cortex is engaged in both focal and generalized epilepsy networks and postulate the various neural pathways that can be effectively neuromodulated by stimulation at this site. This highlights the common involvement of the piriform cortex in epilepsy. We address both current and future preclinical studies of deep brain stimulation (DBS) of the piriform cortex, with attention to the critical features of these trials that will enable them to be of greatest utility in informing clinical translation. Although recent DBS trials have utilized thalamic targets, electrical stimulation of the piriform cortex may also be a useful intervention for people with epilepsy. However, more work is required to develop a solid foundation for this approach before considering human trials.

Investigating white matter fibre density and morphology using fixel-based analysis.

Voxel-based analysis of diffusion MRI data is increasingly popular. However, most white matter voxels contain contributions from multiple fibre populations (often referred to as crossing fibres), and therefore voxel-averaged quantitative measures (e.g. fractional anisotropy) are not fibre-specific and have poor interpretability. Using higher-order diffusion models, parameters related to fibre density can be extracted for individual fibre populations within each voxel ('fixels'), and recent advances in statistics enable the multi-subject analysis of such data. However, investigating within-voxel microscopic fibre density alone does not account for macroscopic differences in the white matter morphology (e.g. the calibre of a fibre bundle). In this work, we introduce a novel method to investigate the latter, which we call fixel-based morphometry (FBM). To obtain a more complete measure related to the total number of white matter axons, information from both within-voxel microscopic fibre density and macroscopic morphology must be combined. We therefore present the FBM method as an integral piece within a comprehensive fixel-based analysis framework to investigate measures of fibre density, fibre-bundle morphology (cross-section), and a combined measure of fibre density and cross-section. We performed simulations to demonstrate the proposed measures using various transformations of a numerical fibre bundle phantom. Finally, we provide an example of such an analysis by comparing a clinical patient group to a healthy control group, which demonstrates that all three measures provide distinct and complementary information. By capturing information from both sources, the combined fibre density and cross-section measure is likely to be more sensitive to certain pathologies and more directly interpretable.

Dynamic coupling between fMRI local connectivity and interictal EEG in focal epilepsy: A wavelet analysis approach.

Simultaneous scalp EEG-fMRI recording is a noninvasive neuroimaging technique for combining electrophysiological and hemodynamic aspects of brain function. Despite the time-varying nature of both measurements, their relationship is usually considered as time-invariant. The aim of this study was to detect direct associations between scalp-recorded EEG and regional changes of hemodynamic brain connectivity in focal epilepsy through a time-frequency paradigm. To do so, we developed a voxel-wise framework that analyses wavelet coherence between dynamic regional phase synchrony (DRePS, calculated from fMRI) and band amplitude fluctuation (BAF) of a target EEG electrode with dominant interictal epileptiform discharges (IEDs). As a proof of concept, we applied this framework to seven patients with focal epilepsy. The analysis produced patient-specific spatial maps of DRePS-BAF coupling, which highlight regions with a strong link between EEG power and local fMRI connectivity. Although we observed DRePS-BAF coupling proximate to the suspected seizure onset zone in some patients, our results suggest that DRePS-BAF is more likely to identify wider 'epileptic networks'. We also compared DRePS-BAF with standard EEG-fMRI analysis based on general linear modelling (GLM). There was, in general, little overlap between the DRePS-BAF maps and GLM maps. However, in some subjects the spatial clusters revealed by these two analyses appeared to be adjacent, particularly in medial posterior cortices. Our findings suggest that (1) there is a strong time-varying relationship between local fMRI connectivity and interictal EEG power in focal epilepsy, and (2) that DRePS-BAF reflect different aspects of epileptic network activity than standard EEG-fMRI analysis. These two techniques, therefore, appear to be complementary. Hum Brain Mapp 38:5356-5374, 2017. © 2017 Wiley Periodicals, Inc.

Dynamic regional phase synchrony (DRePS): An Instantaneous Measure of Local fMRI Connectivity Within Spatially Clustered Brain Areas.

Dynamic functional brain connectivity analysis is a fast expanding field in computational neuroscience research with the promise of elucidating brain network interactions. Sliding temporal window based approaches are commonly used in order to explore dynamic behavior of brain networks in task-free functional magnetic resonance imaging (fMRI) data. However, the low effective temporal resolution of sliding window methods fail to capture the full dynamics of brain activity at each time point. These also require subjective decisions regarding window size and window overlap. In this study, we introduce dynamic regional phase synchrony (DRePS), a novel analysis approach that measures mean local instantaneous phase coherence within adjacent fMRI voxels. We evaluate the DRePS framework on simulated data showing that the proposed measure is able to estimate synchrony at higher temporal resolution than sliding windows of local connectivity. We applied DRePS analysis to task-free fMRI data of 20 control subjects, revealing ultra-slow dynamics of local connectivity in different brain areas. Spatial clustering based on the DRePS feature time series reveals biologically congruent local phase synchrony networks (LPSNs). Taken together, our results demonstrate three main findings. Firstly, DRePS has increased temporal sensitivity compared to sliding window correlation analysis in capturing locally synchronous events. Secondly, DRePS of task-free fMRI reveals ultra-slow fluctuations of ∼0.002-0.02 Hz. Lastly, LPSNs provide plausible spatial information about time-varying brain local phase synchrony. With the DRePS method, we introduce a framework for interrogating brain local connectivity, which can potentially provide biomarkers of human brain function in health and disease. Hum Brain Mapp 37:1970-1985, 2016. © 2016 Wiley Periodicals, Inc.

Abnormal cognitive network interactions in Lennox-Gastaut syndrome: A potential mechanism of epileptic encephalopathy.

OBJECTIVE: In patients with Lennox-Gastaut syndrome (LGS), recurrent epileptic activity is thought to contribute to impaired cognition (epileptic encephalopathy). Using concurrent electroencephalography-functional magnetic resonance imaging (EEG-fMRI), we recently showed that epileptiform discharges in LGS recruit large-scale networks that normally support key cognitive processes. In LGS, given that epileptic activity engages cognitive networks, and cognition is pervasively impaired, we hypothesized that cognitive network interactions in LGS are persistently abnormal. METHODS: We studied 15 LGS patients (mean age ± 1 standard deviation [SD] = 28.7 ± 10.6 years) and 17 healthy controls (mean age ± 1 SD = 27.6 ± 6.6 years) using task-free EEG-fMRI. Four networks of interest (default-mode, dorsal attention, executive control, and anterior salience) were defined using group-level independent components analysis (ICA). Functional connectivity within and between networks was determined for each subject, and then LGS network interactions were compared to network behavior in the control group. To test whether group differences were present in periods without scalp-detectable epileptiform discharges (i.e., persistent), we separately assessed discharge-affected and discharge-unaffected epochs in six patients with sufficient data for this analysis. RESULTS: In LGS, cognitive networks showed (1) reduced within-network integration, including weaker connectivity within the default-mode network, and (2) impaired between-network segregation, including stronger connectivity between the default-mode and dorsal attention networks. Abnormal interactions were present during fMRI periods with and without discharges, indicating that impaired network behavior may endure during periods without scalp-detectable epileptic activity. SIGNIFICANCE: In LGS, cognitive network interactions are persistently abnormal. Given that cognition typically worsens with the onset of LGS, and may improve after seizure control, our findings are consistent with the hypothesis that the epileptic process in LGS may initiate and perhaps sustain abnormal network behavior. We propose that epileptic encephalopathy may be a consequence of persistently disrupted cognitive network interactions.

Hippocampal malrotation is an anatomic variant and has no clinical significance in MRI-negative temporal lobe epilepsy.

OBJECTIVE: There is considerable difficulty in diagnosing hippocampal malrotation (HIMAL), with different criteria of variable reliability. Here we assess qualitative and quantitative criteria in HIMAL diagnosis and explore the role of HIMAL in magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE). METHODS: We studied the MRI of 155 adult patients with MRI-negative TLE and 103 healthy volunteers, and we asked (1) what are the qualitative and quantitative features that allow a reliable diagnosis of HIMAL, (2) how common is HIMAL in a normal control population, and (3) is HIMAL congruent with the epileptogenic side in MRI-negative TLE. RESULTS: We found that the features that are most correlated with the expert diagnosis of HIMAL are hippocampal shape change with hippocampal diameter ratio > 0.8, lack of normal lateral convex margin, and a deep dominant inferior temporal sulcus (DITS) with DITS height ratio > 0.6. In a blinded analysis, a consensus diagnosis of unilateral or bilateral HIMAL was made in 25 of 103 controls (24.3% of people, 14.6% of hippocampi-14 left, six right, 10 bilateral) that did not differ from 155 lesion-negative TLE patients where 25 had HIMAL (16.1% of patients, 11.6% of hippocampi-12 left, two right, 11 bilateral). Of the 12 with left HIMAL only, 9 had seizures arising from the left temporal lobe, whereas 3 had right-sided seizures. Of the two with right HIMAL only, both had seizures arising from the left temporal lobe. SIGNIFICANCE: HIMAL is an anatomic variant commonly found in controls. HIMAL is also an incidental nonpathologic finding in adult MRI-negative TLE and should not influence surgical decision making.

Connectivity-based fixel enhancement: Whole-brain statistical analysis of diffusion MRI measures in the presence of crossing fibres.

In brain regions containing crossing fibre bundles, voxel-average diffusion MRI measures such as fractional anisotropy (FA) are difficult to interpret, and lack within-voxel single fibre population specificity. Recent work has focused on the development of more interpretable quantitative measures that can be associated with a specific fibre population within a voxel containing crossing fibres (herein we use fixel to refer to a specific fibre population within a single voxel). Unfortunately, traditional 3D methods for smoothing and cluster-based statistical inference cannot be used for voxel-based analysis of these measures, since the local neighbourhood for smoothing and cluster formation can be ambiguous when adjacent voxels may have different numbers of fixels, or ill-defined when they belong to different tracts. Here we introduce a novel statistical method to perform whole-brain fixel-based analysis called connectivity-based fixel enhancement (CFE). CFE uses probabilistic tractography to identify structurally connected fixels that are likely to share underlying anatomy and pathology. Probabilistic connectivity information is then used for tract-specific smoothing (prior to the statistical analysis) and enhancement of the statistical map (using a threshold-free cluster enhancement-like approach). To investigate the characteristics of the CFE method, we assessed sensitivity and specificity using a large number of combinations of CFE enhancement parameters and smoothing extents, using simulated pathology generated with a range of test-statistic signal-to-noise ratios in five different white matter regions (chosen to cover a broad range of fibre bundle features). The results suggest that CFE input parameters are relatively insensitive to the characteristics of the simulated pathology. We therefore recommend a single set of CFE parameters that should give near optimal results in future studies where the group effect is unknown. We then demonstrate the proposed method by comparing apparent fibre density between motor neurone disease (MND) patients with control subjects. The MND results illustrate the benefit of fixel-specific statistical inference in white matter regions that contain crossing fibres.

Memory compromise at extended delays in people with new-onset epilepsy.

OBJECTIVE: Memory is one of the most sensitive markers of cognitive compromise in people with new-onset epilepsy. Nonetheless, around half of these cases score within the normal range on standard memory testing. Here we explore whether memory retention at a 1-week delay reveals otherwise undetected memory compromise in such individuals, and how it relates to subjective memory complaints and mood. METHODS: Using a prospective design, 38 adults with new-onset epilepsy underwent baseline memory screening via telephone using an abbreviated Rey Auditory Verbal Learning Test (RAVLT). Psychological screening occurred via online questionnaires. One week later, without forewarning, participants completed three follow-up memory tasks. Of particular focus, we explored longer-term memory performances and forgetting trajectories in those individuals (n = 23) who demonstrated normal memory performances (scores >10th percentile) at baseline (30-min delay). Outcomes were compared to 32 healthy controls, matched for age, sex, and education. RESULTS: As a group, people with epilepsy performed worse than controls on all memory measures, with 44 percent impaired at baseline testing. Of those unimpaired at baseline, the rate and volume of information loss over 1 week was significantly greater than for controls. Contextual memory performance at 1 week was also significantly poorer for people with epilepsy. At the individual level, the prevalence of impaired forgetting was not significantly different between patients and controls. Subjective memory complaints were not related to any objective tests but were strongly related to self-reported mood and anxiety symptoms. SIGNIFICANCE: People with new-onset epilepsy show reduced memory at short and extended intervals. For those showing normal memory at baseline, information does appear to be forgotten more quickly than in healthy controls, though the effect is not large. The findings indicate that while extended delay memory testing is not essential in all new epilepsy cases, it could provide useful information for particular individuals. PLAIN LANGUAGE STATEMENT: Memory problems are common in people with epilepsy shortly after seizure onset, however, many individuals still show normal memory performances on standard neuropsychological testing. Through testing memory at an extended timepoint (1 week), our study found that on average, these individuals showed a slightly quicker rate of forgetting over a 1-week period than people without a brain condition. Self-reported memory complaints in people with new epilepsy were unrelated to their actual memory skills on testing at short and long timepoints but were rather linked to lower mood and quality of life.

Cognitive and psychological dysfunction is present after a first seizure, prior to epilepsy diagnosis and treatment at a First Seizure Clinic.

OBJECTIVE: Neuropsychological comorbidities found in chronic epilepsy have also been reported earlier in the disease course. However, recurrent seizures, antiseizure medication (ASM), and adjustment to a chronic diagnosis remain potential confounds of this literature. It thus remains unclear whether these comorbidities are primary or secondary attributes of epilepsy. To capture individuals as close to disease onset as possible, we studied the cognitive and psychological functioning in adults after their first seizure, yet prior to epilepsy diagnosis and treatment. METHODS: Using a telehealth-based prospective design, we screened cognition, mood, and anxiety symptoms in adult patients referred to a First Seizure Clinic (FSC), who were over 18 years, English-speaking and not taking ASM. We screened cognition via telephone, and psychological symptoms via online questionnaires, all prior to the patients' diagnostic evaluation. Data were collected on 32 individuals subsequently diagnosed with epilepsy at the FSC, and 30 healthy controls from the community, who were matched to the epilepsy group for age, gender, and education. RESULTS: A multivariate analysis of variance revealed that the groups differed significantly on combined cognitive measures with a large effect size (F[1,56] = 5.75, p < 0.001, η2 = 0.45). Post-hoc analyses showed that performances on measures of verbal memory, working memory, and executive functions were significantly worse for the newly diagnosed epilepsy group than controls. The epilepsy group also exhibited higher rates of clinically significant depressive and anxiety symptoms. SIGNIFICANCE: Cognitive and psychological dysfunction is prevalent in people with epilepsy as early as the first seizure event, before the influence of diagnosis, ASM and recurrent seizures. Their neuropsychological profile parallels that seen in chronic epilepsy, showing that this dysfunction is already present at the very onset of the disease. The current study demonstrates the viability of telehealth neuropsychological screening for all new epilepsy cases. PLAIN LANGUAGE STATEMENT: The results of this study show, using telephone-based cognitive assessment and online questionnaires, that people with newly diagnosed epilepsy can experience problems with their thinking and memory skills, and low mood and anxiety, as early as after their first seizure. These issues are apparent at the very beginning of the disease, before an epilepsy diagnosis is made and before antiseizure medication is commenced, which suggests that they are due to the underlying brain disturbance, rather than the secondary effects of seizures, treatment, or lifestyle changes. Telehealth-screening of thinking skills and mental health for all new epilepsy cases is recommended to promote early management of such problems.

Exploring individual fixel-based white matter abnormalities in epilepsy.

Diffusion MRI has provided insight into the widespread structural connectivity changes that characterize epilepsies. Although syndrome-specific white matter abnormalities have been demonstrated, studies to date have predominantly relied on statistical comparisons between patient and control groups. For diffusion MRI techniques to be of clinical value, they should be able to detect white matter microstructural changes in individual patients. In this study, we apply an individualized approach to a technique known as fixel-based analysis, to examine fibre-tract-specific abnormalities in individuals with epilepsy. We explore the potential clinical value of this individualized fixel-based approach in epilepsy patients with differing syndromic diagnoses. Diffusion MRI data from 90 neurologically healthy control participants and 10 patients with epilepsy (temporal lobe epilepsy, progressive myoclonus epilepsy, and Dravet Syndrome, malformations of cortical development) were included in this study. Measures of fibre density and cross-section were extracted for all participants across brain white matter fixels, and mean values were computed within select tracts-of-interest. Scanner harmonized and normalized data were then used to compute Z-scores for individual patients with epilepsy. White matter abnormalities were observed in distinct patterns in individual patients with epilepsy, both at the tract and fixel level. For patients with specific epilepsy syndromes, the detected white matter abnormalities were in line with expected syndrome-specific clinical phenotypes. In patients with lesional epilepsies (e.g. hippocampal sclerosis, periventricular nodular heterotopia, and bottom-of-sulcus dysplasia), white matter abnormalities were spatially concordant with lesion location. This proof-of-principle study demonstrates the clinical potential of translating advanced diffusion MRI methodology to individual-patient-level use in epilepsy. This technique could be useful both in aiding diagnosis of specific epilepsy syndromes, and in localizing structural abnormalities, and is readily amenable to other neurological disorders. We have included code and data for this study so that individualized white matter changes can be explored robustly in larger cohorts in future work.

Work productivity, quality of life, and care needs: An unfolding epilepsy burden revealed in the Australian Epilepsy Project pilot study.

OBJECTIVE: Epilepsy is a common and serious neurological disorder. This cross-sectional analysis addresses the burden of epilepsy at different stages of the disease. METHODS: This pilot study is embedded within the Australian Epilepsy Project (AEP), aiming to provide epilepsy support through a national network of dedicated sites. For this analysis, adults aged 18-65 years with first unprovoked seizure (FUS), newly diagnosed epilepsy (NDE), or drug-resistant epilepsy (DRE) were recruited between February-August 2022. Baseline clinicodemographic data were collected from the participants who completed questionnaires to assess their quality of life (QOLIE-31, EQ-5D-5L), work productivity (Work Productivity and Activity Impairment [WPAI]), and care needs. Univariate analysis and multivariate regression was performed. RESULTS: 172 participants formed the study cohort (median age 34, interquartile range [IQR]: 26-45), comprising FUS (n = 44), NDE (n = 53), and DRE (n = 75). Mean QOLIE-31 score was 56 (standard deviation [SD] ± 18) and median EQ-5D-5L score was 0.77 (IQR: 0.56-0.92). QOLIE-31 but not EQ-5D-5L scores were significantly lower in the DRE group compared to FUS and NDE groups (p < 0.001). Overall, 64.5% of participants participated in paid work, with fewer DRE (52.0%) compared with FUS (76.7%) and NDE (72.5%) (p < 0.001). Compared to those not in paid employment, those in paid employment had significantly higher quality of life scores (p < 0.001). Almost 5.8% of participants required formal care (median 20 h/week, IQR: 12-55) and 17.7% required informal care (median 16 h/week, IQR: 7-101). SIGNIFICANCE: Epilepsy is associated with a large burden in terms of quality of life, productivity and care needs. PLAIN LANGUAGE SUMMARY: This is a pilot study from the Australian Epilepsy Project (AEP). It reports health economic data for adults of working age who live with epilepsy. It found that people with focal drug-resistant epilepsy had lower quality of life scores and were less likely to participate in paid employment compared to people with new diagnosis epilepsy. This study provides important local data regarding the burden of epilepsy and will help researchers in the future to measure the impact of the AEP on important personal and societal health economic outcomes.

Neuropsychological function in psychosis of epilepsy.

OBJECTIVE: The neuropsychological profile of patients with psychosis of epilepsy (POE) has received limited research attention. Recent neuroimaging work in POE has identified structural network pathology in the default mode network and the cognitive control network. This study examined the neuropsychological profile of POE focusing on cognitive domains subserved by these networks. METHODS: Twelve consecutive patients with a diagnosis of POE were prospectively recruited from the Comprehensive Epilepsy Programmes at The Royal Melbourne, Austin and St Vincent's Hospitals, Melbourne, Australia between January 2015 and February 2017. They were compared to 12 matched patients with epilepsy but no psychosis and 42 healthy controls on standardised neuropsychological tests of memory and executive functioning in a case-control design. RESULTS: Mean scores across all cognitive tasks showed a graded pattern of impairment, with the POE group showing the poorest performance, followed by the epilepsy without psychosis and the healthy control groups. This was associated with significant group-level differences on measures of working memory (p = < 0.01); immediate (p = < 0.01) and delayed verbal recall (p = < 0.01); visual memory (p < 0.001); and verbal fluency (p = 0.02). In particular, patients with POE performed significantly worse than the healthy control group on measures of both cognitive control (p = .005) and memory (p < .001), whereas the epilepsy without psychosis group showed only memory difficulties (delayed verbal recall) compared to healthy controls (p = .001). CONCLUSION: People with POE show reduced performance in neuropsychological functions supported by the default mode and cognitive control networks, when compared to both healthy participants and people with epilepsy without psychosis.

Bilateral Structural Network Abnormalities in Epilepsy Associated With Bottom-of-Sulcus Dysplasia.

BACKGROUND AND OBJECTIVES: To identify white matter fiber tracts that exhibit structural abnormality in patients with bottom-of-sulcus dysplasia (BOSD) and investigate their association with seizure activity. METHODS: Whole-brain fixel-based analysis of diffusion MRI data was performed to identify white matter fiber tracts with significant reductions in fiber density and cross-section in patients with BOSD (n = 20) when compared to healthy control participants (n = 40). Results from whole-brain analysis were used to investigate the association of fiber tract abnormality with seizure frequency and epilepsy duration. RESULTS: Despite the focal nature of the dysplasia, patients with BOSD showed widespread abnormality in white matter fiber tracts, including the bilateral corticospinal, corticothalamic, and cerebellothalamic tracts, superior longitudinal fasciculi, corpus callosum (body), and the forceps major. This pattern of bilateral connectivity reduction was not related to the laterality of the lesion. Exploratory post hoc analyses showed that high seizure frequency was associated with greater reduction in fiber density at the forceps major, bilateral corticospinal, and cerebellothalamic tracts. DISCUSSION: We demonstrate evidence of a bilaterally distributed, specific white matter network that is vulnerable to disruption in BOSD. The degree of tract abnormality is partly related to seizure activity, but additional contributors such as the genetic background and effects of treatment or environment have not been excluded.