Clinical prediction models for treatment outcomes in newly diagnosed epilepsy: A systematic review.

Up to 35% of individuals diagnosed with epilepsy continue to have seizures despite treatment, commonly referred to as drug-resistant epilepsy. Uncontrolled seizures can directly, or indirectly, negatively impact an individual's quality of life. To inform clinical management and life decisions, it is important to be able to predict the likelihood of seizure control. Those likely to achieve seizure control will be able to return sooner to their usual work and leisure activities and require less follow-up, whereas those with a poor prognosis will need more frequent clinical attendance and earlier consideration of epilepsy surgery. This is a systematic review aimed at identifying demographic, clinical, physiological (e.g., electroencephalographic), and imaging (e.g., magnetic resonance imaging) factors that may be predictive of treatment outcomes in patients with newly diagnosed epilepsy (NDE). MEDLINE and Embase were searched for prediction models of treatment outcomes in patients with NDE. Study characteristics were extracted and subjected to assessment of risk of bias (and applicability concerns) using the PROBAST (Prediction Model Risk of Bias Assessment Tool) tool. Baseline variables associated with treatment outcomes are reported as prognostic factors. After screening, 48 models were identified in 32 studies, which generally scored low for concerns of applicability, but universally scored high for susceptibility to bias. Outcomes reported fit broadly into four categories: drug resistance, short-term treatment response, seizure remission, and mortality. Prognostic factors were also heterogenous, but the predictors that were commonly significantly associated with outcomes were those related to seizure characteristics/types, epilepsy history, and age at onset. Antiseizure medication response was often included as a baseline variable, potentially obscuring other factor relationships at baseline. Currently, outcome prediction models for NDE demonstrate a high risk of bias. Model development could be improved with a stronger adherence to recommended TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) practices. Furthermore, we outline actionable changes to common practices that are intended to improve the overall quality of prediction model development in NDE.

Contextual determinants of guideline-based family support during end-of-life cancer care and subsequent bereavement care: A cross-sectional survey of registered nurses.

PURPOSE: In end-of-life cancer care, 10-20% of bereaved family members experience adverse mental health effects, including prolonged grief disorder. Despite great efforts, evidence-based recommendations to support their grieving process and well-being are often not successfully adopted into routine clinical care. This study identified facilitators and barriers using implementation science methodology. METHODS: 81 registered nurses working in cancer care from four hospitals and three home care services in Switzerland assessed their current family support practices in end-of-life care and bereavement care. They then assessed organisational attributes of their institution and their own individual characteristics and skills regarding literature-based factors of potential relevance. Facilitators and barriers to guideline-based family support were determined using fractional logistic regression. RESULTS: Service specialisation in palliative care, a culture that supports change, the availability of family support guidelines, billing/reimbursement of bereavement support services, and individual knowledge of family support and skill were systematically associated with higher adoption of guideline-based family support practices. Lack of privacy with families and insufficient training acted as significant barriers. CONCLUSIONS: While several potentially relevant factors have emerged in the literature, certain organisational and individual determinants actually empirically predict guideline-based family support according to nurses in end-of-life cancer care, with some determinants having much stronger implications than others. This provides crucial guidance for focussing quality improvement and implementation efforts through tailored strategies, especially with scarce resources. Furthermore, adoption is lower in bereavement care than in end-of-life care, suggesting a particular need for supportive organisational cultures including specific training and billing/reimbursement options.

A WORLDWIDE ENIGMA STUDY ON EPILEPSY-RELATED GRAY AND WHITE MATTER COMPROMISE ACROSS THE ADULT LIFESPAN.

Objectives: Temporal lobe epilepsy (TLE) is commonly associated with mesiotemporal pathology and widespread alterations of grey and white matter structures. Evidence supports a progressive condition although the temporal evolution of TLE is poorly defined. This ENIGMA-Epilepsy study utilized multimodal magnetic resonance imaging (MRI) data to investigate structural alterations in TLE patients across the adult lifespan. We charted both grey and white matter changes and explored the covariance of age-related alterations in both compartments. Methods: We studied 769 TLE patients and 885 healthy controls across an age range of 17-73 years, from multiple international sites. To assess potentially non-linear lifespan changes in TLE, we harmonized data and combined median split assessments with cross-sectional sliding window analyses of grey and white matter age-related changes. Covariance analyses examined the coupling of grey and white matter lifespan curves. Results: In TLE, age was associated with a robust grey matter thickness/volume decline across a broad cortico-subcortical territory, extending beyond the mesiotemporal disease epicentre. White matter changes were also widespread across multiple tracts with peak effects in temporo-limbic fibers. While changes spanned the adult time window, changes accelerated in cortical thickness, subcortical volume, and fractional anisotropy (all decreased), and mean diffusivity (increased) after age 55 years. Covariance analyses revealed strong limbic associations between white matter tracts and subcortical structures with cortical regions. Conclusions: This study highlights the profound impact of TLE on lifespan changes in grey and white matter structures, with an acceleration of aging-related processes in later decades of life. Our findings motivate future longitudinal studies across the lifespan and emphasize the importance of prompt diagnosis as well as intervention in patients.

End-of-life and bereavement support to families in cancer care: a cross-sectional survey with bereaved family members.

BACKGROUND: Losing a close other to cancer is an incisive experience that occurs after a long course of illness and intense family caregiving. Despite an evident need for family engagement and support and guidance on this, patients and family members may not receive the attention and support they need when a family unit is experiencing a disruption by death. A clear understanding of the quality of care that is currently provided and its ability to address family needs is necessary to improve end-of-life and bereavement support to families affected by cancer. The purpose of this study is to investigate the quality of support of end-of-life and bereavement care to families, their (un)met needs, grief experiences, and self-perceived health outcomes. METHODS: A multi-center, cross-sectional observational survey study with family members (n = 35) whose close other died of cancer in a health institution or their own home in German-speaking Switzerland. RESULTS: Bereaved family members were mostly satisfied with end-of-life care. Information on the grief process and services, and acknowledgment of their grief was experienced as helpful. Most coped with their grief drawing on family resources and exhibited resilience, but they reported unmet needs in relation to family togetherness and caregiving. CONCLUSION: This study with a small number of family members indicates that support provided to families across settings and illness trajectories is perceived as helpful, with specific needs related to family support. The findings suggest that improvements should focus on ensuring care that addresses the family as a unit and enables togetherness, mutual reflection, meaningful relationships, preparedness for death, resilience, and benefit-finding. PROTOCOL REGISTRATION: https://osf.io/j4kfh .

Brain alterations in regions associated with end-organ diabetic microvascular disease in diabetes mellitus: A UK Biobank study.

BACKGROUND: Diabetes mellitus (DM) is associated with structural grey matter alterations in the brain, including changes in the somatosensory and pain processing regions seen in association with diabetic peripheral neuropathy. In this case-controlled biobank study, we aimed to ascertain differences in grey and white matter anatomy in people with DM compared with non-diabetic controls (NDC). METHODS: This study utilises the UK Biobank prospective, population-based, multicentre study of UK residents. Participants with diabetes and age/gender-matched controls without diabetes were selected in a three-to-one ratio. We excluded people with underlying neurological/neurodegenerative disease. Whole brain, cortical, and subcortical volumes (188 regions) were compared between participants with diabetes against NDC corrected for age, sex, and intracranial volume using univariate regression models, with adjustment for multiple comparisons. Diffusion tensor imaging analysis of fractional anisotropy (FA) was performed along the length of 50 white matter tracts. RESULTS: We included 2404 eligible participants who underwent brain magnetic resonance imaging (NDC, n = 1803 and DM, n = 601). Participants with DM had a mean (±standard deviation) diagnostic duration of 18 ± 11 years, with adequate glycaemic control (HbA1C 52 ± 13 mmol/mol), low prevalence of microvascular complications (diabetic retinopathy prevalence, 5.8%), comparable cognitive function to controls but greater self-reported pain. Univariate volumetric analyses revealed significant reductions in grey matter volume (whole brain, total, and subcortical grey matter), with mean percentage differences ranging from 2.2% to 7% in people with DM relative to NDC (all p < 0.0002). The subcortical (bilateral cerebellar cortex, brainstem, thalamus, central corpus callosum, putamen, and pallidum) and cortical regions linked to sensorimotor (bilateral superior frontal, middle frontal, precentral, and postcentral gyri) and visual functions (bilateral middle and superior occipital gyri), all had lower grey matter volumes in people with DM relative to NDC. People with DM had significantly reduced FA along the length of the thalamocortical radiations, thalamostriatal projections, and commissural fibres of the corpus callosum (all; p < 0·001). INTERPRETATION: This analysis suggests that anatomic differences in brain regions are present in a cohort with adequately controlled glycaemia without prevalent microvascular disease when compared with volunteers without diabetes. We hypothesise that these differences may predate overt end-organ damage and complications such as diabetic neuropathy and retinopathy. Central nervous system alterations/neuroplasticity may occur early in the natural history of microvascular complications; therefore, brain imaging should be considered in future mechanistic and interventional studies of DM.

Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA-Epilepsy study.

OBJECTIVE: The intricate neuroanatomical structure of the cerebellum is of longstanding interest in epilepsy, but has been poorly characterized within the current corticocentric models of this disease. We quantified cross-sectional regional cerebellar lobule volumes using structural magnetic resonance imaging in 1602 adults with epilepsy and 1022 healthy controls across 22 sites from the global ENIGMA-Epilepsy working group. METHODS: A state-of-the-art deep learning-based approach was employed that parcellates the cerebellum into 28 neuroanatomical subregions. Linear mixed models compared total and regional cerebellar volume in (1) all epilepsies, (2) temporal lobe epilepsy with hippocampal sclerosis (TLE-HS), (3) nonlesional temporal lobe epilepsy, (4) genetic generalized epilepsy, and (5) extratemporal focal epilepsy (ETLE). Relationships were examined for cerebellar volume versus age at seizure onset, duration of epilepsy, phenytoin treatment, and cerebral cortical thickness. RESULTS: Across all epilepsies, reduced total cerebellar volume was observed (d = .42). Maximum volume loss was observed in the corpus medullare (dmax = .49) and posterior lobe gray matter regions, including bilateral lobules VIIB (dmax = .47), crus I/II (dmax = .39), VIIIA (dmax = .45), and VIIIB (dmax = .40). Earlier age at seizure onset ( η ρ max 2 = .05) and longer epilepsy duration ( η ρ max 2 = .06) correlated with reduced volume in these regions. Findings were most pronounced in TLE-HS and ETLE, with distinct neuroanatomical profiles observed in the posterior lobe. Phenytoin treatment was associated with reduced posterior lobe volume. Cerebellum volume correlated with cerebral cortical thinning more strongly in the epilepsy cohort than in controls. SIGNIFICANCE: We provide robust evidence of deep cerebellar and posterior lobe subregional gray matter volume loss in patients with chronic epilepsy. Volume loss was maximal for posterior subregions implicated in nonmotor functions, relative to motor regions of both the anterior and posterior lobe. Associations between cerebral and cerebellar changes, and variability of neuroanatomical profiles across epilepsy syndromes argue for more precise incorporation of cerebellar subregional damage into neurobiological models of epilepsy.

Adoption of evidence-based end-of-life and bereavement support to families in cancer care: A contextual analysis study with health professionals.

AIMS: To investigate the level of adoption of evidence-based family engagement and support during end-of-life cancer care and subsequent bereavement and its contextual facilitators and barriers from health professionals' perspectives, and to explore differences between professional groups. DESIGN: Contextual analysis using an online cross-sectional survey. METHODS: This study was conducted in four Swiss hospitals and three home care oncology and palliative care services. Non-parametric testing was used to investigate the level of adoption and differences between nurses, physicians, occupational- and physiotherapists and psychosocial professionals (chaplains, onco-psychologists and social workers). The STROBE checklist for cross-sectional studies was followed. RESULTS: The majority of the 111 participating health professionals were nurses. Adoption was statistically significantly higher during end-of-life care than bereavement, with nurses and physicians reporting higher levels than the other professional groups. Guidance on end-of-life family care was available in about half of the cases, in contrast to a quarter for bereavement care. Self-perceived knowledge, skills and attitudes were moderate to high, with nurses and physicians reporting higher levels than others, except for general skills in working with families. Organisational structures were experienced as rather supportive, with the psychosocial group appraising the organisational context as significantly less conducive to fully implementing end-of-life and bereavement care than others, particularly during the end-of-life phase. CONCLUSION: Evidence-based family engagement and support were better adopted during end-of-life care than bereavement. Overall, nurses and physicians felt better enabled to care for families compared to other professional groups. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. PROTOCOL REGISTRATION: https://osf.io/j4kfh. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Implementation and quality improvement efforts should focus particularly on the bereavement phase and be tailored to professional groups. IMPACT: The findings show that evidence-based family engagement and support practices during end-of-life were rather well adopted in contrast to subsequent bereavement care, with nurses and physicians better enabled than other professionals to provide care. A better understanding of health professionals' contributions and roles in family care is important to build interprofessional capacity for evidence-based end-of-life and bereavement support. REPORTING METHOD: The STROBE checklist for reports of cross-sectional studies was followed (von Elm et al., 2007).

Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA-Epilepsy study.

Objective: The intricate neuroanatomical structure of the cerebellum is of longstanding interest in epilepsy, but has been poorly characterized within the current cortico-centric models of this disease. We quantified cross-sectional regional cerebellar lobule volumes using structural MRI in 1,602 adults with epilepsy and 1,022 healthy controls across twenty-two sites from the global ENIGMA-Epilepsy working group. Methods: A state-of-the-art deep learning-based approach was employed that parcellates the cerebellum into 28 neuroanatomical subregions. Linear mixed models compared total and regional cerebellar volume in i) all epilepsies; ii) temporal lobe epilepsy with hippocampal sclerosis (TLE-HS); iii) non-lesional temporal lobe epilepsy (TLE-NL); iv) genetic generalised epilepsy; and (v) extra-temporal focal epilepsy (ETLE). Relationships were examined for cerebellar volume versus age at seizure onset, duration of epilepsy, phenytoin treatment, and cerebral cortical thickness. Results: Across all epilepsies, reduced total cerebellar volume was observed (d=0.42). Maximum volume loss was observed in the corpus medullare (dmax=0.49) and posterior lobe grey matter regions, including bilateral lobules VIIB (dmax= 0.47), Crus I/II (dmax= 0.39), VIIIA (dmax=0.45) and VIIIB (dmax=0.40). Earlier age at seizure onset (ηρ2max=0.05) and longer epilepsy duration (ηρ2max=0.06) correlated with reduced volume in these regions. Findings were most pronounced in TLE-HS and ETLE with distinct neuroanatomical profiles observed in the posterior lobe. Phenytoin treatment was associated with reduced posterior lobe volume. Cerebellum volume correlated with cerebral cortical thinning more strongly in the epilepsy cohort than in controls. Significance: We provide robust evidence of deep cerebellar and posterior lobe subregional grey matter volume loss in patients with chronic epilepsy. Volume loss was maximal for posterior subregions implicated in non-motor functions, relative to motor regions of both the anterior and posterior lobe. Associations between cerebral and cerebellar changes, and variability of neuroanatomical profiles across epilepsy syndromes argue for more precise incorporation of cerebellum subregions into neurobiological models of epilepsy.

Effects of Specific Bioactive Collagen Peptides in Combination with Concurrent Training on Running Performance and Indicators of Endurance Capacity in Men: A Randomized Controlled Trial.

BACKGROUND: First evidence indicates that the supplementation of specific collagen peptides (SCP) is associated with a significant improvement in running performance in physically active women; however, it is unclear if the same is true in males. The purpose of the present study was to investigate the effects of a concurrent training program including 60 min of continuous moderate intensity running training and 15 min of dynamic resistance training combined with supplementation of SCP on parameters of running performance in moderately trained males. METHODS: In a double-blind, placebo-controlled, randomized trial, participants performed a 12 weeks concurrent training and ingested 15 g of SCP [treatment group (TG)] or placebo [control group (CG)] daily. Before and after the intervention, running endurance performance was measured by a 1-h time trial on a running track. Velocity at the lactate threshold (VLT) and at the individual anaerobic threshold (VIAT) were assessed on a treadmill ergometer. Body composition was evaluated by bioelectrical impedance analysis. RESULTS: Thirty-two men (28.4 ± 5.2 years) completed the study and were included in the analysis. After 12 weeks, TG had a statistically significant (p ≤ 0.05) higher increase in running distance (1727 ± 705 m) compared to the CG (1018 ± 976 m) in the time trial. VLT increased in the TG by 0.680 ± 1.27 km h-1 and slightly decreased by - 0.135 ± 0.978 km h-1 in the CG, resulting in statistically significant group differences (p ≤ 0.05). A significantly higher improvement in VIAT (p ≤ 0.05) was shown in the TG compared with the CG only (1.660 ± 1.022 km h-1 vs 0.606 ± 0.974 km h-1; p ≤ 0.01). Fat mass decreased (TG - 1.7 ± 1.6 kg; CG - 1.2 ± 2.0 kg) and fat free mass increased (TG 0.2 ± 1.2 kg; CG 0.5 ± 1.3 kg) in both groups with no significant group differences. CONCLUSION: In summary, supplementation with 15 g of SCP improved running performance in a 1-h time trial and enhanced indicators of endurance capacity at submaximal exercise intensities such as an increased velocity at the lactate as well as the anaerobic threshold more effectively than CT alone. TRIAL REGISTRATION: ETK: 123/17; DRKS-ID: DRKS00015529 (Registered 07 November 2018-Retrospectively registered); https://drks.de/search/de/trial/DRKS00015529.

At the heart of the matter: how mental stress and negative emotions affect atrial fibrillation.

Atrial fibrillation (AF) is the most common form of cardiac arrhythmia, affecting 2%-3% of the world's population. Mental and emotional stress, as well as some mental health conditions (e.g., depression) have been shown to significantly impact the heart and have been suggested to act both as independent risk factors and triggers in the onset of AF. In this paper, we review the current literature to examine the role that mental and emotional stress have in the onset of AF and summarise the current knowledge on the interaction between the brain and heart, and the cortical and subcortical pathways involved in the response to stress. Review of the evidence suggests that mental and emotional stress negatively affect the cardiac system, potentially increasing the risk for developing and/or triggering AF. Further studies are required to further understand the cortical and sub-cortical structures involved in the mental stress response and how these interact with the cardiac system, which may help in defining new strategies and interventions to prevent the development of, and improve the management of AF.

A structural magnetic resonance imaging review of clinical motor outcomes from deep brain stimulation in movement disorders.

Patients with movement disorders treated by deep brain stimulation do not always achieve successful therapeutic alleviation of motor symptoms, even in cases where surgery is without complications. Magnetic resonance imaging (MRI) offers methods to investigate structural brain-related factors that may be predictive of clinical motor outcomes. This review aimed to identify features which have been associated with variability in clinical post-operative motor outcomes in patients with Parkinson's disease, dystonia, and essential tremor from structural MRI modalities. We performed a literature search for articles published between 1 January 2000 and 1 April 2022 and identified 5197 articles. Following screening through our inclusion criteria, we identified 60 total studies (39 = Parkinson's disease, 11 = dystonia syndromes and 10 = essential tremor). The review captured a range of structural MRI methods and analysis techniques used to identify factors related to clinical post-operative motor outcomes from deep brain stimulation. Morphometric markers, including volume and cortical thickness were commonly identified in studies focused on patients with Parkinson's disease and dystonia syndromes. Reduced metrics in basal ganglia, sensorimotor and frontal regions showed frequent associations with reduced motor outcomes. Increased structural connectivity to subcortical nuclei, sensorimotor and frontal regions was also associated with greater motor outcomes. In patients with tremor, increased structural connectivity to the cerebellum and cortical motor regions showed high prevalence across studies for greater clinical motor outcomes. In addition, we highlight conceptual issues for studies assessing clinical response with structural MRI and discuss future approaches towards optimizing individualized therapeutic benefits. Although quantitative MRI markers are in their infancy for clinical purposes in movement disorder treatments, structural features obtained from MRI offer the powerful potential to identify candidates who are more likely to benefit from deep brain stimulation and provide insight into the complexity of disorder pathophysiology.

Convolutional Neural Network Algorithm to Determine Lateralization of Seizure Onset in Patients With Epilepsy: A Proof-of-Principle Study.

BACKGROUND AND OBJECTIVES: A new frontier in diagnostic radiology is the inclusion of machine-assisted support tools that facilitate the identification of subtle lesions often not visible to the human eye. Structural neuroimaging plays an essential role in the identification of lesions in patients with epilepsy, which often coincide with the seizure focus. In this study, we explored the potential for a convolutional neural network (CNN) to determine lateralization of seizure onset in patients with epilepsy using T1-weighted structural MRI scans as input. METHODS: Using a dataset of 359 patients with temporal lobe epilepsy (TLE) from 7 surgical centers, we tested whether a CNN based on T1-weighted images could classify seizure laterality concordant with clinical team consensus. This CNN was compared with a randomized model (comparison with chance) and a hippocampal volume logistic regression (comparison with current clinically available measures). Furthermore, we leveraged a CNN feature visualization technique to identify regions used to classify patients. RESULTS: Across 100 runs, the CNN model was concordant with clinician lateralization on average 78% (SD = 5.1%) of runs with the best-performing model achieving 89% concordance. The CNN outperformed the randomized model (average concordance of 51.7%) on 100% of runs with an average improvement of 26.2% and outperformed the hippocampal volume model (average concordance of 71.7%) on 85% of runs with an average improvement of 6.25%. Feature visualization maps revealed that in addition to the medial temporal lobe, regions in the lateral temporal lobe, cingulate, and precentral gyrus aided in classification. DISCUSSION: These extratemporal lobe features underscore the importance of whole-brain models to highlight areas worthy of clinician scrutiny during temporal lobe epilepsy lateralization. This proof-of-concept study illustrates that a CNN applied to structural MRI data can visually aid clinician-led localization of epileptogenic zone and identify extrahippocampal regions that may require additional radiologic attention. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in patients with drug-resistant unilateral temporal lobe epilepsy, a convolutional neural network algorithm derived from T1-weighted MRI can correctly classify seizure laterality.

Automatic and manual segmentation of the piriform cortex: Method development and validation in patients with temporal lobe epilepsy and Alzheimer's disease.

The piriform cortex (PC) is located at the junction of the temporal and frontal lobes. It is involved physiologically in olfaction as well as memory and plays an important role in epilepsy. Its study at scale is held back by the absence of automatic segmentation methods on MRI. We devised a manual segmentation protocol for PC volumes, integrated those manually derived images into the Hammers Atlas Database (n = 30) and used an extensively validated method (multi-atlas propagation with enhanced registration, MAPER) for automatic PC segmentation. We applied automated PC volumetry to patients with unilateral temporal lobe epilepsy with hippocampal sclerosis (TLE; n = 174 including n = 58 controls) and to the Alzheimer's Disease Neuroimaging Initiative cohort (ADNI; n = 151, of whom with mild cognitive impairment (MCI), n = 71; Alzheimer's disease (AD), n = 33; controls, n = 47). In controls, mean PC volume was 485 mm3 on the right and 461 mm3 on the left. Automatic and manual segmentations overlapped with a Jaccard coefficient (intersection/union) of ~0.5 and a mean absolute volume difference of ~22 mm3 in healthy controls, ~0.40/ ~28 mm3 in patients with TLE, and ~ 0.34/~29 mm3 in patients with AD. In patients with TLE, PC atrophy lateralised to the side of hippocampal sclerosis (p < .001). In patients with MCI and AD, PC volumes were lower than those of controls bilaterally (p < .001). Overall, we have validated automatic PC volumetry in healthy controls and two types of pathology. The novel finding of early atrophy of PC at the stage of MCI possibly adds a novel biomarker. PC volumetry can now be applied at scale.

[End-of-Life Dreams and Visions]. / Traum- und Wachvisionen am Lebensende.

End-of-Life Dreams and Visions Abstract: End-of life dreams and visions (ELDVs) or so-called death bed phenomena are transcendent experiences at the end of life that can be visual, auditory and/or kinesthetic, and often include visions of (deceased) loved ones, close friends or perceptions of places, travels, bright lights, or music. ELDVs typically occur weeks to hours prior to death and may comfort the dying and prepare spiritually for the end of life. Such experiences are frequently reported by dying individuals, the prevalence varying between 30 and 80%, but in the clinical context ELDVs are usually neglected, but interpreted and treated as pathological changes in the brain that result in, and from, delirium. This article tries to enlighten the occurrence, the contents and meanings of ELDVs in dying persons as opposed to delirium and night dreams using findings from the literature and from clinical observations. Implications of these conclusions for palliative care and the therapeutic relevance of ELDVs when taking care of dying individuals and their loved ones will also be discussed.

Neurocysticercosis-related seizures: Imaging biomarkers.

Neurocysticercosis (NCC)-a parasitic CNS infection endemic to developing nations-has been called the leading global cause of acquired epilepsy yet remains understudied. It is currently unknown why a large proportion of patients develop recurrent seizures, often following the presentation of acute seizures. Furthermore, the presentation of NCC is heterogenous and the features that predispose to the development of an epileptogenic state remain uncertain. Perilesional factors (such as oedema and gliosis) have been implicated in NCC-related ictogenesis, but the effects of cystic factors, including lesion load and location, seem not to play a role in the development of habitual epilepsy. In addition, the cytotoxic consequences of the cyst's degenerative stages are varied and the majority of research, relying on retrospective data, lacks the necessary specificity to distinguish between acute symptomatic and unprovoked seizures. Previous research has established that epileptogenesis can be the consequence of abnormal network connectivity, and some imaging studies have suggested that a causative link may exist between NCC and aberrant network organisation. In wider epilepsy research, network approaches have been widely adopted; studies benefiting predominantly from the rich, multimodal data provided by advanced MRI methods are at the forefront of the field. Quantitative MRI approaches have the potential to elucidate the lesser-understood epileptogenic mechanisms of NCC. This review will summarise the current understanding of the relationship between NCC and epilepsy, with a focus on MRI methodologies. In addition, network neuroscience approaches with putative value will be highlighted, drawing from current imaging trends in epilepsy research.

Resting state functional connectivity demonstrates increased segregation in bilateral temporal lobe epilepsy.

OBJECTIVE: Temporal lobe epilepsy (TLE) is the most common type of focal epilepsy. An increasingly identified subset of patients with TLE consists of those who show bilaterally independent temporal lobe seizures. The purpose of this study was to leverage network neuroscience to better understand the interictal whole brain network of bilateral TLE (BiTLE). METHODS: In this study, using a multicenter resting state functional magnetic resonance imaging (rs-fMRI) data set, we constructed whole-brain functional networks of 19 patients with BiTLE, and compared them to those of 75 patients with unilateral TLE (UTLE). We quantified resting-state, whole-brain topological properties using metrics derived from network theory, including clustering coefficient, global efficiency, participation coefficient, and modularity. For each metric, we computed an average across all brain regions, and iterated this process across network densities. Curves of network density vs each network metric were compared between groups. Finally, we derived a combined metric, which we term the "integration-segregation axis," by combining whole-brain average clustering coefficient and global efficiency curves, and applying principal component analysis (PCA)-based dimensionality reduction. RESULTS: Compared to UTLE, BiTLE had decreased global efficiency (p = .031), and decreased whole brain average participation coefficient across a range of network densities (p = .019). Modularity maximization yielded a larger number of smaller communities in BiTLE than in UTLE (p = .020). Differences in network properties separate BiTLE and UTLE along the integration-segregation axis, with regions within the axis having a specificity of up to 0.87 for BiTLE. Along the integration-segregation axis, UTLE patients with poor surgical outcomes were distributed in the same regions as BiTLE, and network metrics confirmed similar patterns of increased segregation in both BiTLE and poor outcome UTLE. SIGNIFICANCE: Increased interictal whole-brain network segregation, as measured by rs-fMRI, is specific to BiTLE, as well as poor surgical outcome UTLE, and may assist in non-invasively identifying this patient population prior to intracranial electroencephalography or device implantation.

From basic sciences and engineering to epileptology: A translational approach.

Collaborative efforts between basic scientists, engineers, and clinicians are enabling translational epileptology. In this article, we summarize the recent advances presented at the International Conference for Technology and Analysis of Seizures (ICTALS 2022): (1) novel developments of structural magnetic resonance imaging; (2) latest electroencephalography signal-processing applications; (3) big data for the development of clinical tools; (4) the emerging field of hyperdimensional computing; (5) the new generation of artificial intelligence (AI)-enabled neuroprostheses; and (6) the use of collaborative platforms to facilitate epilepsy research translation. We highlight the promise of AI reported in recent investigations and the need for multicenter data-sharing initiatives.

MRI-based deep learning can discriminate between temporal lobe epilepsy, Alzheimer's disease, and healthy controls.

BACKGROUND: Radiological identification of temporal lobe epilepsy (TLE) is crucial for diagnosis and treatment planning. TLE neuroimaging abnormalities are pervasive at the group level, but they can be subtle and difficult to identify by visual inspection of individual scans, prompting applications of artificial intelligence (AI) assisted technologies. METHOD: We assessed the ability of a convolutional neural network (CNN) algorithm to classify TLE vs. patients with AD vs. healthy controls using T1-weighted magnetic resonance imaging (MRI) scans. We used feature visualization techniques to identify regions the CNN employed to differentiate disease types. RESULTS: We show the following classification results: healthy control accuracy = 81.54% (SD = 1.77%), precision = 0.81 (SD = 0.02), recall = 0.85 (SD = 0.03), and F1-score = 0.83 (SD = 0.02); TLE accuracy = 90.45% (SD = 1.59%), precision = 0.86 (SD = 0.03), recall = 0.86 (SD = 0.04), and F1-score = 0.85 (SD = 0.04); and AD accuracy = 88.52% (SD = 1.27%), precision = 0.64 (SD = 0.05), recall = 0.53 (SD = 0.07), and F1 score = 0.58 (0.05). The high accuracy in identification of TLE was remarkable, considering that only 47% of the cohort had deemed to be lesional based on MRI alone. Model predictions were also considerably better than random permutation classifications (p < 0.01) and were independent of age effects. CONCLUSIONS: AI (CNN deep learning) can classify and distinguish TLE, underscoring its potential utility for future computer-aided radiological assessments of epilepsy, especially for patients who do not exhibit easily identifiable TLE associated MRI features (e.g., hippocampal sclerosis).

In people with temporal lobe epilepsy, seizures start in a particular part of the brain positioned behind the ears called the temporal lobe. It is difficult for a doctor to detect that a person has temporal lobe epilepsy using brain scans. In this study, we developed a computer model that was able to identify people with temporal lobe epilepsy from scans of their brain. This computer model could be used to help doctors identify temporal lobe epilepsy from brain scans in the future.

Midbrain structure volume, estimated myelin and functional connectivity in idiopathic generalised epilepsy.

BACKGROUND: Structural and functional neuroimaging studies often overlook lower basal ganglia structures located in and adjacent to the midbrain due to poor contrast on clinically acquired T1-weighted scans. Here, we acquired T1-weighted, T2-weighted, and resting-state fMRI scans to investigate differences in volume, estimated myelin content and functional connectivity of the substantia nigra (SN), subthalamic nuclei (SubTN) and red nuclei (RN) of the midbrain in IGE. METHODS: Thirty-three patients with IGE (23 refractory, 10 non-refractory) and 39 age and sex-matched healthy controls underwent MR imaging. Midbrain structures were automatically segmented from T2-weighted images and structural volumes were calculated. The estimated myelin content for each structure was determined using a T1-weighted/T2-weighted ratio method. Resting-state functional connectivity analysis of midbrain structures (seed-based) was performed using the CONN toolbox. RESULTS: An increased volume of the right RN was found in IGE and structural volumes of the right SubTN differed between patients with non-refractory and refractory IGE. However, no volume findings survived corrections for multiple comparisons. No myelin alterations of midbrain structures were found for any subject groups. We found functional connectivity alterations including significantly decreased connectivity between the left SN and the thalamus and significantly increased connectivity between the right SubTN and the superior frontal gyrus in IGE. CONCLUSIONS: We report volumetric and functional connectivity alterations of the midbrain in patients with IGE. We postulate that potential increases in structural volumes are due to increased iron deposition that impacts T2-weighted contrast. These findings are consistent with previous studies demonstrating pathophysiological abnormalities of the lower basal ganglia in animal models of generalised epilepsy.

The impact of transcatheter aortic valve implantation planning and procedure on acute and chronic renal failure.

BACKGROUND: Severe aortic valve stenosis inhibits renal perfusion, thereby potentially worsening renal function, in particular in elderly patients most often assigned to transcatheter aortic valve implantation (TAVI). Pre-TAVI diagnostics and the procedure itself may adversely impact renal function, however renal perfusion and function may also improve post-procedure. This study aimed to clarify the impact of TAVI planning and procedure on kidney function METHODS: In this retrospective study, kidney function of patients who underwent transfemoral TAVI at a tertiary university hospital between 2016 and 2019 was analyzed. The present study investigated kidney function at baseline, after computed tomography (CT) was performed for evaluation of TAVI, after TAVI, at discharge and at follow-up. RESULTS: Among 366 patients, the prevalence of acute kidney injury (AKI) was 14.5% after TAVI. Independent predictors of AKI were arterial hypertension, baseline creatinine, AKI post CT and coronary intervention during pre-procedural diagnostics. At discharge and follow-up, 2.1% and 3.4%, respectively had sustained relevant impairment of kidney function (defined as creatinine/baseline creatinine > 1.5 or renal replacement therapy). Patients with known chronic kidney disease showed no higher rates of short- and long-term impairment, but higher rates of improvement of renal function after TAVI. CONCLUSIONS: In most cases TAVI does not worsen renal function. A sustained impairment after TAVI was found in only a few cases. This was independent of reduced baseline kidney function. Transfemoral TAVI can thus be planned and performed even in patients with higher stages of chronic kidney disease.