Analytic Tools for Post-traumatic Epileptogenesis Biomarker Search in Multimodal Dataset of an Animal Model and Human Patients

ENLARGED PERIVASCULAR SPACES IN FRONTAL AND TEMPORAL CORTICAL REGIONS CHARACTERIZE SEIZURE OUTCOME AFTER TRAUMATIC BRAIN INJURY

Post-traumatic epilepsy (PTE) is characterized by seizures that occur at least one week after traumatic brain injury (TBI). Although PTE remains one of the most life-altering outcomes of TBI, there are no preventative treatments. The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) is an international project designed to identify multimodal biomarkers of PTE; early EpiBioS4Rx research suggests that features of perivascular spaces (PVS) are a potential biomarker. This study evaluates the association between volume fraction (VF), the volume of PVS relative to total brain volume, and seizure activity. Structural magnetic resonance (MR) imaging from a subset of 62 EpiBioS4Rx subjects was used to create Enhanced PVS Contrast (EPC) imaging to segment and quantify PVS metrics. A multiple logistic regression model that controlled for demographic and clinical factors revealed a significant difference between the late seizure-positive and seizure-negative groups in the paracentral lobule, precentral gyrus, and temporal pole of the right hemisphere. These findings are supported by prior literature that identify a relationship between PVS function in these regions and seizure activity after TBI.

Role of the glymphatic system and perivascular spaces as a potential biomarker for post-stroke epilepsy

Stroke is one of the most common causes of acquired epilepsy, which can also result in disability and increased mortality rates particularly in elderly patients. No preventive treatment for post-stroke epilepsy is currently available. Development of such treatments has been greatly limited by the lack of biomarkers to reliably identify high-risk patients. The glymphatic system, including perivascular spaces (PVS), is the brain's waste clearance system, and enlargement or asymmetry of PVS (ePVS) is hypothesized to play a significant role in the pathogenesis of several neurological conditions. In this article, we discuss potential mechanisms for the role of perivascular spaces in the development of post-stroke epilepsy. Using advanced MR-imaging techniques, it has been shown that there is asymmetry and impairment of glymphatic function in the setting of ischemic stroke. Furthermore, studies have described a dysfunction of PVS in patients with different focal and generalized epilepsy syndromes. It is thought that inflammatory processes involving PVS and the blood-brain barrier, impairment of waste clearance, and sustained hypertension affecting the glymphatic system during a seizure may play a crucial role in epileptogenesis post-stroke. We hypothesize that impairment of the glymphatic system and asymmetry and dynamics of ePVS in the course of a stroke contribute to the development of PSE. Automated ePVS detection in stroke patients might thus assist in the identification of high-risk patients for post-stroke epilepsy trials. PLAIN LANGUAGE SUMMARY: Stroke often leads to epilepsy and is one of the main causes of epilepsy in elderly patients, with no preventative treatment available. The brain's waste removal system, called the glymphatic system which consists of perivascular spaces, may be involved. Enlargement or asymmetry of perivascular spaces could play a role in this and can be visualised with advanced brain imaging after a stroke. Detecting enlarged perivascular spaces in stroke patients could help identify those at risk for post-stroke epilepsy.

Reduced total number of enlarged perivascular spaces in post-traumatic epilepsy patients with unilateral lesions - a feasibility study

BACKGROUND

We investigated the value of automated enlarged perivascular spaces (ePVS) quantification to distinguish chronic traumatic brain injury (TBI) patients with post-traumatic epilepsy (PTE+) from chronic TBI patients without PTE (PTE-) in a feasibility study.

METHODS

Patients with and without PTE were recruited and underwent an MRI post-TBI. Multimodal auto identification of ePVS algorithm was applied to T1-weighted MRIs to segment ePVS. The total number of ePVS was calculated and corrected for white matter volume, and an asymmetry index (AI) derived.

RESULTS

PTE was diagnosed in 7 out of the 99 participants (male=69) after a median time of less than one year since injury (range 10-22). Brain lesions were observed in all 7 PTE+ cases (unilateral=4, 57%; bilateral=3, 43%) as compared to 40 PTE- cases (total 44%; unilateral=17, 42%; bilateral=23, 58%). There was a significant difference between PTE+ (M=1.21e-4, IQR [8.89e-5]) and PTE- cases (M=2.79e-4, IQR [6.25e-5]) in total corrected numbers of ePVS in patients with unilateral lesions (p=0.024). No differences in AI, trauma severity and lesion volume were seen between groups.

CONCLUSION

This study has shown that automated quantification of ePVS is feasible and provided initial evidence that individuals with PTE with unilateral lesions may have fewer ePVS compared to TBI patients without epilepsy. Further studies with larger sample sizes should be conducted to determine the value of ePVS quantification as a PTE-biomarker.

The asymmetry of glymphatic system dysfunction in patients with temporal lobe epilepsy: A DTI-ALPS study

BACKGROUND AND PURPOSE

While the occurrence of glymphatic system dysfunction has been observed in temporal lobe epilepsy (TLE), the potential asymmetry of this system has yet to be investigated in the TLE context. We aimed to investigate the glymphatic system function in both hemispheres and to analyze asymmetric features of the glymphatic system in TLE patients using diffusion tensor image analysis along the perivascular space (DTI-ALPS) method.

MATERIALS AND METHODS

43 patients (left TLE (LTLE), n = 20; right TLE (RTLE), n = 23) and 39 healthy controls (HC) were enrolled in this study. The DTI-ALPS index was calculated for the left (left ALPS index) and right (right ALPS index) hemispheres respectively. An asymmetry index (AI) was calculated by AI = (Right - Left)/ [(Right + Left)/2] to represent the asymmetric pattern. Independent two sample t-test, two-sample paired t-test or one-way ANOVA with Bonferroni correction were conducted to compare the differences in ALPS indices and AI among the groups.

RESULTS

Both left ALPS index (p = 0.040) and right ALPS index (p = 0.001) of RTLE patients were significantly decreased, while only left ALPS index of LTLE patients (p = 0.005) was reduced. Compared to contralateral ALPS index, the ipsilateral ALPS index was significantly decreased in TLE (p = 0.008) and RTLE (p = 0.009) patients. Leftward asymmetry of the glymphatic system was found in HC (p = 0.045) and RTLE (p = 0.009) patients. The LTLE patients presented reduced asymmetric traits when compared to RTLE patients (p = 0.029).

CONCLUSION

The TLE patients exhibited altered ALPS indices, which could be triggered by glymphatic system dysfunction. Altered ALPS indices were more severe in ipsilateral than in the contralateral hemisphere. Moreover, LTLE and RTLE patients exhibited different change patterns of the glymphatic system. In addition, glymphatic system function presented asymmetric patterns in both normal adult brain and RTLE patients.

Associations of Enlarged Perivascular Spaces With Brain Lesions, Brain Age, and Clinical Outcomes in Chronic Traumatic Brain Injury

BACKGROUND AND OBJECTIVES

Enlarged perivascular spaces (ePVS) have been identified as a key signature of glymphatic system dysfunction in neurologic conditions. The incidence and clinical implications of ePVS after traumatic brain injury (TBI) are not yet understood. We investigated whether individuals with chronic moderate-to-severe TBI had an increased burden of ePVS and whether ePVS burden is modulated by the presence of focal lesions, older brain age, and poorer sleep quality. We examined whether an increased burden of ePVS was associated with poorer cognitive and emotional outcomes.

METHODS

Using a cross-sectional design, participants with a single moderate-to-severe chronic TBI (sustained ≥10 years ago) were recruited from an inpatient rehabilitation program. Control participants were recruited from the community. Participants underwent 3T brain MRI, neuropsychological assessment, and clinical evaluations. ePVS burden in white matter was quantified using automated segmentation. The relationship between the number of ePVS, group membership, focal lesions, brain age, current sleep quality, and outcome was modeled using negative binomial and linear regressions.

RESULTS

This study included 100 participants with TBI (70% male; mean age = 56.8 years) and 75 control participants (54.3% male; mean age = 59.8 years). The TBI group had a significantly greater burden of ePVS (prevalence ratio rate [PRR] = 1.29, p = 0.013, 95% CI 1.05-1.57). The presence of bilateral lesions was associated with greater ePVS burden (PRR = 1.41, p = 0.021, 95% CI 1.05-1.90). There was no association between ePVS burden, sleep quality (PRR = 1.01, p = 0.491, 95% CI 0.98-1.048), and sleep duration (PRR = 1.03, p = 0.556, 95% CI 0.92-1.16). ePVS was associated with verbal memory (β = -0.42, p = 0.006, 95% CI -0.72 to -0.12), but not with other cognitive domains. The burden of ePVS was not associated with emotional distress (β = -0.70, p = 0.461, 95% CI -2.57 to 1.17) or brain age (PRR = 1.00, p = 0.665, 95% CI 0.99-1.02).

DISCUSSION

TBI is associated with a greater burden of ePVS, especially when there have been bilateral brain lesions. ePVS was associated with reduced verbal memory performance. ePVS may indicate ongoing impairments in glymphatic system function in the chronic postinjury period.

Brain perivascular spaces and autism: clinical and pathogenic implications from an innovative volumetric MRI study

Introduction

Our single-center case-control study aimed to evaluate the unclear glymphatic system alteration in autism spectrum disorder (ASD) through an innovative neuroimaging tool which allows to segment and quantify perivascular spaces in the white matter (WM-PVS) with filtering of non-structured noise and increase of the contrast-ratio between perivascular spaces and the surrounding parenchyma.

Methods

Briefly, files of 65 ASD and 71 control patients were studied. We considered: ASD type, diagnosis and severity level and comorbidities (i.e., intellectual disability, attention-deficit hyperactivity disorder, epilepsy, sleep disturbances). We also examined diagnoses other than ASD and their associated comorbidities in the control group.

Results

When males and females with ASD are included together, WM-PVS grade and WM-PVS volume do not significantly differ between the ASD group and the control group overall. We found, instead, that WM-PVS volume is significantly associated with male sex: males had higher WM-PVS volume compared to females (p = 0.01). WM-PVS dilation is also non-significantly associated with ASD severity and younger age (< 4 years). In ASD patients, higher WM-PVS volume was related with insomnia whereas no relation was found with epilepsy or IQ.

Discussion

We concluded that WM-PVS dilation can be a neuroimaging feature of male ASD patients, particularly the youngest and most severe ones, which may rely on male-specific risk factors acting early during neurodevelopment, such as a transient excess of extra-axial CSF volume. Our findings can corroborate the well-known strong male epidemiological preponderance of autism worldwide.

A critical guide to the automated quantification of perivascular spaces in magnetic resonance imaging

The glymphatic system is responsible for waste clearance in the brain. It is comprised of perivascular spaces (PVS) that surround penetrating blood vessels. These spaces are filled with cerebrospinal fluid and interstitial fluid, and can be seen with magnetic resonance imaging. Various algorithms have been developed to automatically label these spaces in MRI. This has enabled volumetric and morphological analyses of PVS in healthy and disease cohorts. However, there remain inconsistencies between PVS measures reported by different methods of automated segmentation. The present review emphasizes that importance of voxel-wise evaluation of model performance, mainly with the Sørensen Dice similarity coefficient. Conventional count correlations for model validation are inadequate if the goal is to assess volumetric or morphological measures of PVS. The downside of voxel-wise evaluation is that it requires manual segmentations that require large amounts of time to produce. One possible solution is to derive these semi-automatically. Additionally, recommendations are made to facilitate rigorous development and validation of automated PVS segmentation models. In the application of automated PVS segmentation tools, publication of image quality metrics, such as the contrast-to-noise ratio, alongside descriptive statistics of PVS volumes and counts will facilitate comparability between studies. Lastly, a head-to-head comparison between two algorithms, applied to two cohorts of astronauts reveals how results can differ substantially between techniques.

Imaging perivascular space structure and function using brain MRI

In this article, we provide an overview of current neuroimaging methods for studying perivascular spaces (PVS) in humans using brain MRI. In recent years, an increasing number of studies highlighted the role of PVS in cerebrospinal/interstial fluid circulation and clearance of cerebral waste products and their association with neurological diseases. Novel strategies and techniques have been introduced to improve the quantification of PVS and to investigate their function and morphological features in physiological and pathological conditions. After a brief introduction on the anatomy and physiology of PVS, we examine the latest technological developments to quantitatively analyze the structure and function of PVS in humans with MRI. We describe the applications, advantages, and limitations of these methods, providing guidance and suggestions on the acquisition protocols and analysis techniques that can be applied to study PVS in vivo. Finally, we review the human neuroimaging studies on PVS across the normative lifespan and in the context of neurological disorders.

Sub-scalp electroencephalography: A next-generation technique to study human neurophysiology

Sub-scalp electroencephalography (ssEEG) is emerging as a promising technology in ultra-long-term electroencephalography (EEG) recordings. Given the diversity of devices available in this nascent field, uncertainty persists about its utility in epilepsy evaluation. This review critically dissects the many proposed utilities of ssEEG devices including (1) seizure quantification, (2) seizure characterization, (3) seizure lateralization, (4) seizure localization, (5) seizure alarms, (6) seizure forecasting, (7) biomarker discovery, (8) sleep medicine, and (9) responsive stimulation. The different ssEEG devices in development have individual design philosophies with unique strengths and limitations. There are devices offering primarily unilateral recordings (24/7 EEG^TM SubQ, Neuroview^TM, Soenia® UltimateEEG™), bilateral recordings (Minder™, Epios™), and even those with responsive stimulation capability (EASEE®). We synthesize the current knowledge of these ssEEG systems. We review the (1) ssEEG devices, (2) use case scenarios, (3) challenges and (4) suggest a roadmap for ideal ssEEG designs.

MRI-Visible Perivascular Spaces Associated With Cognitive Impairment in Military Veterans With Traumatic Brain Injury Mediated by CSF P-Tau

Objective

To investigate the association of MRI-visible perivascular spaces (PVS) with cognitive impairment in military veterans with traumatic brain injury (TBI), and whether cerebrospinal fluid (CSF) p-tau and Aβ mediate this effect.

Materials and Methods

We included 55 Vietnam War veterans with a history of TBI and 52 non-TBI Vietnam War veterans from the Department of Defense Alzheimer's Disease Neuroimaging Initiative (ADNI) database. All the subjects had brain MRI, CSF p-tau, Aβ, and neuropsychological examinations. MRI-visible PVS number and grade were rated on MRI in the centrum semiovale (CSO-PVS) and basal ganglia (BG-PVS). Multiple linear regression was performed to assess the association between MRI-visible PVS and cognitive impairment and the interaction effect of TBI. Additionally, mediation effect of CSF biomarkers on the relationship between MRI-visible PVS and cognitive impairment was explored in TBI group.

Results

Compared with military control, TBI group had higher CSO-PVS number (p = 0.001), CSF p-tau (p = 0.022) and poorer performance in verbal memory (p = 0.022). High CSO-PVS number was associated with poor verbal memory in TBI group (β = -0.039, 95% CI -0.062, -0.016), but not in military control group (β = 0.019, 95% CI -0.004, 0.043) (p-interaction = 0.003). Further mediation analysis revealed that CSF p-tau had a significant indirect effect (β = -0.009, 95% CI: -0.022 -0.001, p = 0.001) and mediated 18.75% effect for the relationship between CSO-PVS and verbal memory in TBI group.

Conclusion

MRI-visible CSO-PVS was more common in Vietnam War veterans with a history of TBI and was associated with poor verbal memory, mediated partially by CSF p-tau.

Neuroanatomic Markers of Posttraumatic Epilepsy Based on MR Imaging and Machine Learning

BACKGROUND AND PURPOSE

Although posttraumatic epilepsy is a common complication of traumatic brain injury, the relationship between these conditions is unclear and early posttraumatic epilepsy detection and prevention remain major unmet clinical challenges. This study aimed to identify imaging biomarkers that predict posttraumatic epilepsy among survivors of traumatic brain injury on the basis of an MR imaging data set.

MATERIALS AND METHODS

We performed tensor-based morphometry to analyze brain-shape changes associated with traumatic brain injury and to derive imaging features for statistical group comparison. Additionally, machine learning was used to identify structural anomalies associated with brain lesions. Automatically generated brain lesion maps were used to identify brain regions where lesion load may indicate an increased incidence of posttraumatic epilepsy. We used 138 non-posttraumatic epilepsy subjects for training the machine learning method. Validation of lesion delineation was performed on 15 subjects. Group analysis of the relationship between traumatic brain injury and posttraumatic epilepsy was performed on an independent set of 74 subjects (37 subjects with and 37 randomly selected subjects without epilepsy).

RESULTS

We observed significant F-statistics related to tensor-based morphometry analysis at voxels close to the pial surface, which may indicate group differences in the locations of edema, hematoma, or hemorrhage. The results of the F-test on lesion data showed significant differences between groups in both the left and right temporal lobes. We also saw significant differences in the right occipital lobe and cerebellum.

CONCLUSIONS

Statistical analysis suggests that lesions in the temporal lobes, cerebellum, and the right occipital lobe are associated with an increased posttraumatic epilepsy incidence.

Asymmetric distribution of enlarged perivascular spaces in centrum semiovale may be associated with epilepsy after acute ischemic stroke

Objective

To investigate the factors influencing enlarged perivascular space (EPVS) characteristics at the onset of acute ischemic stroke (AIS), and whether the PVS characteristics can predict later post‐stroke epilepsy (PSE).

Methods

A total of 312 patients with AIS were identified, of whom 58/312 (18.6%) developed PSE. Twenty healthy participants were included as the control group. The number of PVS in the basal ganglia (BG), centrum semiovale (CS), and midbrain (MB) was manually calculated on T₂‐weighted MRI. The scores and asymmetry index (AI) of EPVS in each region were compared among the enrolled participants. Other potential risk factors for PSE were also analyzed, including NIHSS at admission and stroke etiologies.

Results

The EPVS scores were significantly higher in the bilateral BG and CS of AIS patients compared to those of the control group (both p < 0.01). No statistical differences in EPVS scores in BG, CS, and MB were obtained between the PSE group and the nonepilepsy AIS group (all p > 0.01). However, markedly different AI scores in CS were found between the PSE group and the nonepilepsy AIS group (p = 0.004). Multivariable analysis showed that high asymmetry index of EPVS (AI≥0.2) in CS was an independent predictor for PSE (OR = 3.7, 95% confidence interval 1.5–9.1, p = 0.004).

Conclusions

Asymmetric distribution of EPVS in CS may be an independent risk factor and a novel imaging biomarker for the development of PSE. Further studies to understand the mechanisms of this association and confirmation with larger patient populations are warranted.

Automatic Detection of EEG Epileptiform Abnormalities in Traumatic Brain Injury using Deep Learning

Traumatic brain injury (TBI) is a sudden injury that causes damage to the brain. TBI can have wide-ranging physical, psychological, and cognitive effects. TBI outcomes include acute injuries, such as contusion or hematoma, as well as chronic sequelae that emerge days to years later, including cognitive decline and seizures. Some TBI patients develop posttraumatic epilepsy (PTE), or recurrent and unprovoked seizures following TBI. In recent years, significant efforts have been made to identify biomarkers of epileptogenesis, the process by which a normal brain becomes capable of generating seizures. These biomarkers would allow for a higher standard of care by identifying patients at risk of developing PTE as candidates for antiepileptogenic interventions. In this paper, we use deep neural network architectures to automatically detect potential biomarkers of PTE from electroencephalogram (EEG) data collected between post-injury day 1-7 from patients with moderate-to-severe TBI. Continuous EEG is often part of multimodal monitoring for TBI patients in intensive care units. Clinicians review EEG to identify the presence of epileptiform abnormalities (EAs), such as seizures, periodic discharges, and abnormal rhythmic delta activity, which are potential biomarkers of epileptogenesis. We show that a recurrent neural network trained with continuous EEG data can be used to identify EAs with the highest accuracy of 80.78%, paving the way for robust, automated detection of epileptiform activity in TBI patients.

Predictors and prognoses of epilepsy after anti-neuronal antibody-positive autoimmune encephalitis

PURPOSE

This study aimed to investigate the incidence and predictors of epilepsy after anti-neuronal antibody-positive autoimmune encephalitis (AIE). The clinical outcomes of patients with epilepsy after AIE were also explored.

METHODS

A total of 111 AIE patients were retrospectively evaluated. Post-AIE epilepsy (PAEE) was defined as at least one unprovoked seizure occurring six or more months after discharge from hospital.

RESULTS

The incidence of acute symptomatic seizures was 80.2% (89/111) in our AIE patients. Furthermore, of the 89 AIE patients with seizures, 29 (32.6%) presented with seizures as the initial symptom. Overall, 44 out of 111 AIE patients (39.6%) had unprovoked seizures after six months, meeting our definition of PAEE. The independent risk factors for PAEE incidence included an initial presentation with new-onset refractory status epilepticus (NORSE), delayed immunotherapy treatment, the complication of a lung infection during admission, the requirement for mechanical ventilation during hospitalization, parietal lesions observed in magnetic resonance imaging (MRI), and focal slow waves on electroencephalographic (EEG) monitoring.

CONCLUSIONS

Early initiation of immunotherapy and lung infection treatment may reduce the risk of conversion of symptomatic seizures to chronic epilepsy in the acute phase of AIE. In general, PAEE patients could have a good prognosis if treated properly and in a timely fashion.

Update on the Neuroimaging and Electroencephalographic Biomarkers of Epileptogenesis: A Literature Review

Epilepsy is one of the most common debilitating neurological disorders that lead to severe socio-cognitive dysfunction. While there are currently more than 30 antiseizure medications available for the treatment and prevention of seizures, none address the prevention of epileptogenesis that leading to the development of epilepsy following a potential brain insult. Hence, there is a growing need for the identification of accurate biomarkers of epileptogenesis that enable the prediction of epilepsy following a known brain insult. Although recent studies using various neuroimages and electroencephalography have found promising biomarkers of epileptogenesis, their utility needs to be further validated in larger clinical trials. In this literature review, we searched the Medline, Pubmed, and Embase databases using the following search algorithm: "epileptogenesis" and "biomarker" and "EEG" or "electroencephalography" or "neuroimaging" limited to publications in English. We presented a comprehensive overview of recent innovations in the role of neuroimaging and EEG in identifying reliable biomarkers of epileptogenesis.

Body mass index, time of day and genetics affect perivascular spaces in the white matter

The analysis of cerebral perivascular spaces (PVS) using magnetic resonance imaging (MRI) allows to explore in vivo their contributions to neurological disorders. To date the normal amount and distribution of PVS in healthy human brains are not known, thus hampering our ability to define with confidence pathogenic alterations. Furthermore, it is unclear which biological factors can influence the presence and size of PVS on MRI. We performed exploratory data analysis of PVS volume and distribution in a large population of healthy individuals (n = 897, age = 28.8 ± 3.7). Here we describe the global and regional amount of PVS in the white matter, which can be used as a reference for clinicians and researchers investigating PVS and may help the interpretation of the structural changes affecting PVS in pathological states. We found a relatively high inter-subject variability in the PVS amount in this population of healthy adults (range: 1.31-14.49 cm3). The PVS volume was higher in older and male individuals. Moreover, we identified body mass index, time of day, and genetics as new elements significantly affecting PVS in vivo under physiological conditions, offering a valuable foundation to future studies aimed at understanding the physiology of perivascular flow.

The ENIGMA Brain Injury working group: approach, challenges, and potential benefits

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium brings together researchers from around the world to try to identify the genetic underpinnings of brain structure and function, along with robust, generalizable effects of neurological and psychiatric disorders. The recently-formed ENIGMA Brain Injury working group includes 10 subgroups, based largely on injury mechanism and patient population. This introduction to the special issue summarizes the history, organization, and objectives of ENIGMA Brain Injury, and includes a discussion of strategies, challenges, opportunities and goals common across 6 of the subgroups under the umbrella of ENIGMA Brain Injury. The following articles in this special issue, including 6 articles from different subgroups, will detail the challenges and opportunities specific to each subgroup.

Artificial Intelligence Technologies in Neurosurgery: a Systematic Literature Review Using Topic Modeling. Part II: Research Objectives and Perspectives

The current increase in the number of publications on the use of artificial intelligence (AI) technologies in neurosurgery indicates a new trend in clinical neuroscience. The aim of the study was to conduct a systematic literature review to highlight the main directions and trends in the use of AI in neurosurgery.

METHODS

Using the PubMed search engine, 327 original journal articles published from 1996 to July 2019 and related to the use of AI technologies in neurosurgery, were selected. The typical issues addressed by using AI were identified for each area of neurosurgery.

RESULTS

The typical AI applications within each of the five main areas of neurosurgery (neuro-oncology, functional, vascular, spinal neurosurgery, and traumatic brain injury) were defined.

CONCLUSION

The article highlights the main areas and trends in the up-to-date AI research in neurosurgery, which might be helpful in planning new scientific projects.

Perivascular Space Imaging at Ultrahigh Field MR Imaging

The recent Food and Drug Administration approval of 7 T MR imaging scanners for clinical use has introduced the possibility to study the brain not only in physiologic but also in pathologic conditions at ultrahigh field (UHF). Because UHF MR imaging offers higher signal-to-noise ratio and spatial resolution compared with lower field clinical scanners, the benefits of UHF MR imaging are particularly evident for imaging small anatomic structures, such as the cerebral perivascular spaces (PVS). In this article, the authors describe the application of UHF MR imaging for the investigation of PVS.

Imaging biomarkers of posttraumatic epileptogenesis

Traumatic brain injury (TBI) affects 2.5 million people annually within the United States alone, with over 300 000 severe injuries resulting in emergency room visits and hospital admissions. Severe TBI can result in long-term disability. Posttraumatic epilepsy (PTE) is one of the most debilitating consequences of TBI, with an estimated incidence that ranges from 2% to 50% based on severity of injury. Conducting studies of PTE poses many challenges, because many subjects with TBI never develop epilepsy, and it can be more than 10 years after TBI before seizures begin. One of the unmet needs in the study of PTE is an accurate biomarker of epileptogenesis, or a panel of biomarkers, which could provide early insights into which TBI patients are most susceptible to PTE, providing an opportunity for prophylactic anticonvulsant therapy and enabling more efficient large-scale PTE studies. Several recent reviews have provided a comprehensive overview of this subject (Neurobiol Dis, 123, 2019, 3; Neurotherapeutics, 11, 2014, 231). In this review, we describe acute and chronic imaging methods that detect biomarkers for PTE and potential mechanisms of epileptogenesis. We also describe shortcomings in current acquisition methods, analysis, and interpretation that limit ongoing investigations that may be mitigated with advancements in imaging techniques and analysis.

The holy grail of epilepsy prevention: Preclinical approaches to antiepileptogenic treatments

A variety of acute brain insults can induce epileptogenesis, a complex process that results in acquired epilepsy. Despite advances in understanding mechanisms of epileptogenesis, there is currently no approved treatment that prevents the development or progression of epilepsy in patients at risk. The current concept of epileptogenesis assumes a window of opportunity following acute brain insults that allows intervention with preventive treatment. Recent results suggest that injury-induced epileptogenesis can be a much more rapid process than previously thought, suggesting that the 'therapeutic window' may only be open for a brief period, as in stroke therapy. However, experimental data also suggest a second, possibly delayed process ("secondary epileptogenesis") that influences the progression and refractoriness of the epileptic state over time, allowing interfering with this process even after onset of epilepsy. In this review, both methodological issues in preclinical drug development and novel targets for antiepileptogenesis will be discussed. Several promising drugs that either prevent epilepsy (antiepileptogenesis) or slow epilepsy progression and alleviate cognitive or behavioral comorbidities of epilepsy (disease modification) have been described in recent years, using diverse animal models of acquired epilepsy. Promising agents include TrkB inhibitors, losartan, statins, isoflurane, anti-inflammatory and anti-oxidative drugs, the SV2A modulator levetiracetam, and epigenetic interventions. Research on translational target validity and on prognostic biomarkers that can be used to stratify patients (or experimental animals) at high risk of developing epilepsy will hopefully soon lead to proof-of-concept clinical trials with the most promising drugs, which will be essential to make prevention of epilepsy a reality. This article is part of the special issue entitled 'New Epilepsy Therapies for the 21st Century - From Antiseizure Drugs to Prevention, Modification and Cure of Epilepsy'.