Harmonization of pipeline for preclinical multicenter MRI biomarker discovery in a rat model of post-traumatic epileptogenesis

ComBating inter-site differences in field strength: harmonizing preclinical traumatic brain injury MRI data

Integrating datasets from multiple sites and scanners can increase statistical power for neuroimaging studies but can also introduce significant inter-site confounds. We evaluated the effectiveness of ComBat, an empirical Bayes approach, to combine longitudinal preclinical MRI data acquired at 4.7 or 9.4 T at two different sites in Australia. Male Sprague Dawley rats underwent MRI on Days 2, 9, 28, and 150 following moderate/severe traumatic brain injury (TBI) or sham injury as part of Project 1 of the NIH/NINDS-funded Centre Without Walls EpiBioS4Rx project. Diffusion-weighted and multiple-gradient-echo images were acquired, and outcomes included QSM, FA, and ADC. Acute injury measures including apnea and self-righting reflex were consistent between sites. Mixed-effect analysis of ipsilateral and contralateral corpus callosum (CC) summary values revealed a significant effect of site on FA and ADC values, which was removed following ComBat harmonization. Bland-Altman plots for each metric showed reduced variability across sites following ComBat harmonization, including for QSM, despite appearing to be largely unaffected by inter-site differences and no effect of site observed. Following harmonization, the combined inter-site data revealed significant differences in the imaging metrics consistent with previously reported outcomes. TBI resulted in significantly reduced FA and increased susceptibility in the ipsilateral CC, and significantly reduced FA in the contralateral CC compared with sham-injured rats. Additionally, TBI rats also exhibited a reversal in ipsilateral CC ADC values over time with significantly reduced ADC at Day 9, followed by increased ADC 150 days after injury. Our findings demonstrate the need for harmonizing multi-site preclinical MRI data and show that this can be successfully achieved using ComBat while preserving phenotypical changes due to TBI.

Brain abscess - A rare confounding factor for diagnosis of post-traumatic epilepsy after lateral fluid-percussion injury

OBJECTIVE

To assess the prevalence of brain abscesses as a confounding factor for the diagnosis of post-traumatic epilepsy (PTE) in a rat model of lateral fluid-percussion-induced (FPI) traumatic brain injury (TBI).

METHODS

This retrospective study included 583 rats from 3 study cohorts collected over 2009-2022 in a single laboratory. The rats had undergone sham-operation or TBI using lateral FPI. Rats were implanted with epidural and/or intracerebral electrodes for electroencephalogram recordings. Brains were processed for histology to screen for abscess(es). In abscess cases, (a) unfolded cortical maps were constructed to assess the cortical location and area of the abscess, (b) the abscess tissue was Gram stained to determine the presence of gram-positive and gram-negative bacteria, and (c) immunostaining was performed to detect infiltrating neutrophils, T-lymphocytes, and glial cells as tissue biomarkers of inflammation. In vivo and/or ex vivo magnetic resonance images available from a subcohort of animals were reviewed to evaluate the presence of abscesses. Plasma samples available from a subcohort of rats were used for enzyme-linked immunosorbent assays to determine the levels of lipopolysaccharide (LPS) as a circulating biomarker for gram-negative bacteria.

RESULTS

Brain abscesses were detected in 2.6% (15/583) of the rats (6 sham, 9 TBI). In histology, brain abscesses were characterized as vascularized encapsulated lesions filled with neutrophils and surrounded by microglia/macrophages and astrocytes. The abscesses were mainly located under the screw electrodes, support screws, or craniectomy. Epilepsy was diagnosed in 60% (9/15) of rats with an abscess (4 sham, 5 TBI). Of these, 67% (6/9) had seizure clusters. The average seizure frequency in abscess cases was 0.436 ± 0.281 seizures/d. Plasma LPS levels were comparable between rats with and without abscesses (p > 0.05).

SIGNIFICANCE

Although rare, a brain abscess is a potential confounding factor for epilepsy diagnosis in animal models of structural epilepsies following brain surgery and electrode implantation, particularly if seizures occur in sham-operated experimental controls and/or in clusters.

Epilepsy phenotype and its reproducibility after lateral fluid percussion-induced traumatic brain injury in rats: Multicenter EpiBioS4Rx study project 1

OBJECTIVE

This study was undertaken to assess reproducibility of the epilepsy outcome and phenotype in a lateral fluid percussion model of posttraumatic epilepsy (PTE) across three study sites.

METHODS

A total of 525 adult male Sprague Dawley rats were randomized to lateral fluid percussion-induced brain injury (FPI) or sham operation. Of these, 264 were assigned to magnetic resonance imaging (MRI cohort, 43 sham, 221 traumatic brain injury [TBI]) and 261 to electrophysiological follow-up (EEG cohort, 41 sham, 220 TBI). A major effort was made to harmonize the rats, materials, equipment, procedures, and monitoring systems. On the 7th post-TBI month, rats were video-EEG monitored for epilepsy diagnosis.

RESULTS

A total of 245 rats were video-EEG phenotyped for epilepsy on the 7th postinjury month (121 in MRI cohort, 124 in EEG cohort). In the whole cohort (n = 245), the prevalence of PTE in rats with TBI was 22%, being 27% in the MRI and 18% in the EEG cohort (p > .05). Prevalence of PTE did not differ between the three study sites (p > .05). The average seizure frequency was .317 ± .725 seizures/day at University of Eastern Finland (UEF; Finland), .085 ± .067 at Monash University (Monash; Australia), and .299 ± .266 at University of California, Los Angeles (UCLA; USA; p < .01 as compared to Monash). The average seizure duration did not differ between UEF (104 ± 48 s), Monash (90 ± 33 s), and UCLA (105 ± 473 s; p > .05). Of the 219 seizures, 53% occurred as part of a seizure cluster (≥3 seizures/24 h; p >.05 between the study sites). Of the 209 seizures, 56% occurred during lights-on period and 44% during lights-off period (p > .05 between the study sites).

SIGNIFICANCE

The PTE phenotype induced by lateral FPI is reproducible in a multicenter design. Our study supports the feasibility of performing preclinical multicenter trials in PTE to increase statistical power and experimental rigor to produce clinically translatable data to combat epileptogenesis after TBI.

Successful harmonization in EpiBioS4Rx biomarker study on post-traumatic epilepsy paves the way towards powered preclinical multicenter studies

OBJECTIVE

Project 1 of the Preclinical Multicenter Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) consortium aims to identify preclinical biomarkers for antiepileptogenic therapies following traumatic brain injury (TBI). The international participating centers in Finland, Australia, and the United States have made a concerted effort to ensure protocol harmonization. Here, we evaluate the success of harmonization process by assessing the timing, coverage, and performance between the study sites.

METHOD

We collected data on animal housing conditions, lateral fluid-percussion injury model production, postoperative care, mortality, post-TBI physiological monitoring, timing of blood sampling and quality, MR imaging timing and protocols, and duration of video-electroencephalography (EEG) follow-up using common data elements. Learning effect in harmonization was assessed by comparing procedural accuracy between the early and late stages of the project.

RESULTS

The animal housing conditions were comparable between the study sites but the postoperative care procedures varied. Impact pressure, duration of apnea, righting reflex, and acute mortality differed between the study sites (p < 0.001). The severity of TBI on D2 post TBI assessed using the composite neuroscore test was similar between the sites, but recovery of acute somato-motor deficits varied (p < 0.001). A total of 99% of rats included in the final cohort in UEF, 100% in Monash, and 79% in UCLA had blood samples taken at all time points. The timing of sampling differed on day (D)2 (p < 0.05) but not D9 (p > 0.05). Plasma quality was poor in 4% of the samples in UEF, 1% in Monash and 14% in UCLA. More than 97% of the final cohort were MR imaged at all timepoints in all study sites. The timing of imaging did not differ on D2 and D9 (p > 0.05), but varied at D30, 5 months, and ex vivo timepoints (p < 0.001). The percentage of rats that completed the monthly high-density video-EEG follow-up and the duration of video-EEG recording on the 7th post-injury month used for seizure detection for diagnosis of post-traumatic epilepsy differed between the sites (p < 0.001), yet the prevalence of PTE (UEF 21%, Monash 22%, UCLA 23%) was comparable between the sites (p > 0.05). A decrease in acute mortality and increase in plasma quality across time reflected a learning effect in the TBI production and blood sampling protocols.

SIGNIFICANCE

Our study is the first demonstration of the feasibility of protocol harmonization for performing powered preclinical multi-center trials for biomarker and therapy discovery of post-traumatic epilepsy.

Image data harmonization tools for the analysis of post-traumatic epilepsy development in preclinical multisite MRI studies

Preclinical MRI studies have been utilized for the discovery of biomarkers that predict post-traumatic epilepsy (PTE). However, these single site studies often lack statistical power due to limited and homogeneous datasets. Therefore, multisite studies, such as the Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx), are developed to create large, heterogeneous datasets that can lead to more statistically significant results. EpiBioS4Rx collects preclinical data internationally across sites, including the United States, Finland, and Australia. However, in doing so, there are robust normalization and harmonization processes that are required to obtain statistically significant and generalizable results. This work describes the tools and procedures used to harmonize multisite, multimodal preclinical imaging data acquired by EpiBioS4Rx. There were four main harmonization processes that were utilized, including file format harmonization, naming convention harmonization, image coordinate system harmonization, and diffusion tensor imaging (DTI) metrics harmonization. By using Python tools and bash scripts, the file formats, file names, and image coordinate systems are harmonized across all the sites. To harmonize DTI metrics, values are estimated for each voxel in an image to generate a histogram representing the whole image. Then, the Quantitative Imaging Toolkit (QIT) modules are utilized to scale the mode to a value of one and depict the subsequent harmonized histogram. The standardization of file formats, naming conventions, coordinate systems, and DTI metrics are qualitatively assessed. The histograms of the DTI metrics were generated for all the individual rodents per site. For inter-site analysis, an average of the individual scans was calculated to create a histogram that represents each site. In order to ensure the analysis can be run at the level of individual animals, the sham and TBI cohort were analyzed separately, which depicted the same harmonization factor. The results demonstrate that these processes qualitatively standardize the file formats, naming conventions, coordinate systems, and DTI metrics of the data. This assists in the ability to share data across the study, as well as disseminate tools that can help other researchers to strengthen the statistical power of their studies and analyze data more cohesively.

MRI-Guided Electrode Implantation for Chronic Intracerebral Recordings in a Rat Model of Post-Traumatic Epilepsy-Challenges and Gains

Brain atrophy induced by traumatic brain injury (TBI) progresses in parallel with epileptogenesis over time, and thus accurate placement of intracerebral electrodes to monitor seizure initiation and spread at the chronic postinjury phase is challenging. We evaluated in adult male Sprague Dawley rats whether adjusting atlas-based electrode coordinates on the basis of magnetic resonance imaging (MRI) increases electrode placement accuracy and the effect of chronic electrode implantations on TBI-induced brain atrophy. One group of rats (EEG cohort) was implanted with two intracortical (anterior and posterior) and a hippocampal electrode right after TBI to target coordinates calculated using a rat brain atlas. Another group (MRI cohort) was implanted with the same electrodes, but using T2-weighted MRI to adjust the planned atlas-based 3D coordinates of each electrode. Histological analysis revealed that the anterior cortical electrode was in the cortex in 83% (25% in targeted layer V) of the EEG cohort and 76% (31%) of the MRI cohort. The posterior cortical electrode was in the cortex in 40% of the EEG cohort and 60% of the MRI cohort. Without MRI-guided adjustment of electrode tip coordinates, 58% of the posterior cortical electrodes in the MRI cohort will be in the lesion cavity, as revealed by simulated electrode placement on histological images. The hippocampal electrode was accurately placed in 82% of the EEG cohort and 86% of the MRI cohort. Misplacement of intracortical electrodes related to their rostral shift due to TBI-induced cortical and hippocampal atrophy and caudal retraction of the brain, and was more severe ipsilaterally than contralaterally (p < 0.001). Total lesion area in cortical subfields targeted by the electrodes (primary somatosensory cortex, visual cortex) was similar between cohorts (p > 0.05). MRI-guided adjustment of coordinates for electrodes improved the success rate of intracortical electrode tip placement nearly to that at the acute postinjury phase (68% vs. 62%), particularly in the posterior brain, which exhibited the most severe postinjury atrophy. Overall, MRI-guided electrode implantation improved the quality and interpretation of the origin of EEG-recorded signals.

A companion to the preclinical common data elements and case report forms for in vivo rodent neuroimaging: A report of the TASK3-WG3 Neuroimaging Working Group of the ILAE/AES Joint Translational Task Force

The International League Against Epilepsy/American Epilepsy Society (ILAE/AES) Joint Translational Task Force established the TASK3 working groups to create common data elements (CDEs) for various aspects of preclinical epilepsy research studies, which could help improve the standardization of experimental designs. In this article, we discuss CDEs for neuroimaging data that are collected in rodent models of epilepsy, with a focus on adult rats and mice. We provide detailed CDE tables and case report forms (CRFs), and with this companion manuscript, we discuss the methodologies for several imaging modalities and the parameters that can be collected.

Quantitative MRI Harmonization to Maximize Clinical Impact: The RIN-Neuroimaging Network

Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures.

Convolutional Neural Networks Enable Robust Automatic Segmentation of the Rat Hippocampus in MRI After Traumatic Brain Injury

Registration-based methods are commonly used in the automatic segmentation of magnetic resonance (MR) brain images. However, these methods are not robust to the presence of gross pathologies that can alter the brain anatomy and affect the alignment of the atlas image with the target image. In this work, we develop a robust algorithm, MU-Net-R, for automatic segmentation of the normal and injured rat hippocampus based on an ensemble of U-net-like Convolutional Neural Networks (CNNs). MU-Net-R was trained on manually segmented MR images of sham-operated rats and rats with traumatic brain injury (TBI) by lateral fluid percussion. The performance of MU-Net-R was quantitatively compared with methods based on single and multi-atlas registration using MR images from two large preclinical cohorts. Automatic segmentations using MU-Net-R and multi-atlas registration were of excellent quality, achieving cross-validated Dice scores above 0.90 despite the presence of brain lesions, atrophy, and ventricular enlargement. In contrast, the performance of single-atlas segmentation was unsatisfactory (cross-validated Dice scores below 0.85). Interestingly, the registration-based methods were better at segmenting the contralateral than the ipsilateral hippocampus, whereas MU-Net-R segmented the contralateral and ipsilateral hippocampus equally well. We assessed the progression of hippocampal damage after TBI by using our automatic segmentation tool. Our data show that the presence of TBI, time after TBI, and whether the hippocampus was ipsilateral or contralateral to the injury were the parameters that explained hippocampal volume.

Deterministic Tractography Analysis of Rat Brain Using SIGMA Atlas in 9.4T MRI

Preclinical studies using rodents have been the choice for many neuroscience researchers due totheir close reflection of human biology. In particular, research involving rodents has utilized MRI to accurately identify brain regions and characteristics by acquiring high resolution cavity images with different contrasts non-invasively, and this has resulted in high reproducibility and throughput. In addition, tractographic analysis using diffusion tensor imaging to obtain information on the neural structure of white matter has emerged as a major methodology in the field of neuroscience due to its contribution in discovering significant correlations between altered neural connections and various neurological and psychiatric diseases. However, unlike image analysis studies with human subjects where a myriad of human image analysis programs and procedures have been thoroughly developed and validated, methods for analyzing rat image data using MRI in preclinical research settings have seen significantly less developed. Therefore, in this study, we present a deterministic tractographic analysis pipeline using the SIGMA atlas for a detailed structural segmentation and structural connectivity analysis of the rat brain’s structural connectivity. In addition, the structural connectivity analysis pipeline presented in this study was preliminarily tested on normal and stroke rat models for initial observation.

Diffusion Tensor Orientation as a Microstructural MRI Marker of Mossy Fiber Sprouting After TBI in Rats

Diffusion tensor imaging (DTI) metrics are highly sensitive to microstructural brain alterations and are potentially useful imaging biomarkers for underlying neuropathologic changes after experimental and human traumatic brain injury (TBI). As potential imaging biomarkers require direct correlation with neuropathologic alterations for validation and interpretation, this study systematically examined neuropathologic abnormalities underlying alterations in DTI metrics in the hippocampus and cortex following controlled cortical impact (CCI) in rats. Ex vivo DTI metrics were directly compared with a comprehensive histologic battery for neurodegeneration, microgliosis, astrocytosis, and mossy fiber sprouting by Timm histochemistry at carefully matched locations immediately, 48 hours, and 4 weeks after injury. DTI abnormalities corresponded to spatially overlapping but temporally distinct neuropathologic alterations representing an aggregate measure of dynamic tissue damage and reorganization. Prominent DTI alterations of were observed for both the immediate and acute intervals after injury and associated with neurodegeneration and inflammation. In the chronic period, diffusion tensor orientation in the hilus of the dentate gyrus became prominently abnormal and was identified as a reliable structural biomarker for mossy fiber sprouting after CCI in rats, suggesting potential application as a biomarker to follow secondary progression in experimental and human TBI.

Minimal specifications for non-human primate MRI: Challenges in standardizing and harmonizing data collection

Recent methodological advances in MRI have enabled substantial growth in neuroimaging studies of non-human primates (NHPs), while open data-sharing through the PRIME-DE initiative has increased the availability of NHP MRI data and the need for robust multi-subject multi-center analyses. Streamlined acquisition and analysis protocols would accelerate and improve these efforts. However, consensus on minimal standards for data acquisition protocols and analysis pipelines for NHP imaging remains to be established, particularly for multi-center studies. Here, we draw parallels between NHP and human neuroimaging and provide minimal guidelines for harmonizing and standardizing data acquisition. We advocate robust translation of widely used open-access toolkits that are well established for analyzing human data. We also encourage the use of validated, automated pre-processing tools for analyzing NHP data sets. These guidelines aim to refine methodological and analytical strategies for small and large-scale NHP neuroimaging data. This will improve reproducibility of results, and accelerate the convergence between NHP and human neuroimaging strategies which will ultimately benefit fundamental and translational brain science.

Biomarkers for posttraumatic epilepsy

A biomarker is a characteristic that can be objectively measured as an indicator of normal biologic processes, pathogenic processes, or responses to an exposure or intervention, including therapeutic interventions. Biomarker modalities include molecular, histologic, radiographic, or physiologic characteristics. To improve the understanding and use of biomarker terminology in biomedical research, clinical practice, and medical product development, the Food and Drug Administration (FDA)-National Institutes of Health (NIH) Joint Leadership Council developed the BEST Resource (Biomarkers, EndpointS, and other Tools). The seven BEST biomarker categories include the following: (a) susceptibility/risk biomarkers, (b) diagnostic biomarkers, (c) monitoring biomarkers, (d) prognostic biomarkers, (e) predictive biomarkers, (f) pharmacodynamic/response biomarkers, and (g) safety biomarkers. We hypothesize some potential overlap between the reported biomarkers of traumatic brain injury (TBI), epilepsy, and posttraumatic epilepsy (PTE). Here, we tested this hypothesis by reviewing studies focusing on biomarker discovery for posttraumatic epileptogenesis and epilepsy. The biomarker modalities reviewed here include plasma/serum and cerebrospinal fluid molecular biomarkers, imaging biomarkers, and electrophysiologic biomarkers. Most of the reported biomarkers have an area under the receiver operating characteristic curve greater than 0.800, suggesting both high sensitivity and high specificity. Our results revealed little overlap in the biomarker candidates between TBI, epilepsy, and PTE. In addition to using single parameters as biomarkers, machine learning approaches have highlighted the potential for utilizing patterns of markers as biomarkers. Although published data suggest the possibility of identifying biomarkers for PTE, we are still in the early phase of the development curve. Many of the seven biomarker categories lack PTE-related biomarkers. Thus, further exploration using proper, statistically powered, and standardized study designs with validation cohorts, and by developing and applying novel analytical methods, is needed for PTE biomarker discovery.

What value can TSPO PET bring for epilepsy treatment?

Epilepsy is one of the most common neurological disorders and affects both the young and adult populations. The question we asked for this review was how positron emission tomography (PET) imaging with translocator protein (TSPO) radioligands can help inform the epilepsy clinic and the development of future treatments targeting neuroinflammatory processes.Even though the first TSPO PET scans in epilepsy patients were performed over 20 years ago, this imaging modality has not seen wide adoption in the clinic. There is vast scientific evidence from preclinical studies in rodent models of temporal lobe epilepsy which have shown increased levels of TSPO corresponding to neuroinflammatory processes in the brain. These increases peaked sub-acutely (1-2 weeks) after the epileptogenic insult (e.g. status epilepticus) and remained chronically increased, albeit at lower levels. In addition, these studies have shown a correlation between TSPO levels and seizure outcome, pharmacoresistance and behavioural morbidities. Histological assessment points to a complex interplay between different cellular components such as microglial activation, astrogliosis and cell death changing dynamically over time.In epilepsy patients, a highly sensitive biomarker of neuroinflammation would provide value for the optimization of surgical assessment (particularly for extratemporal lobe epilepsy) and support the clinical development path of anti-inflammatory treatments. Clinical studies have shown a systematic increase in asymmetry indices of TSPO PET binding. However, region-based analysis typically does not yield statistical differences and changes are often not restricted to the epileptogenic zone, limiting the ability of this imaging modality to localise pathology for surgery. In this manuscript, we discuss the biological underpinnings of these findings and review for which applications in epilepsy TSPO PET could bring added value.

Identification of clinically relevant biomarkers of epileptogenesis - a strategic roadmap

Onset of many forms of epilepsy occurs after an initial epileptogenic insult or as a result of an identified genetic defect. Given that the precipitating insult is known, these epilepsies are, in principle, amenable to secondary prevention. However, development of preventive treatments is difficult because only a subset of individuals will develop epilepsy and we cannot currently predict which individuals are at the highest risk. Biomarkers that enable identification of these individuals would facilitate clinical trials of potential anti-epileptogenic treatments, but no such prognostic biomarkers currently exist. Several putative molecular, imaging, electroencephalographic and behavioural biomarkers of epileptogenesis have been identified, but clinical translation has been hampered by fragmented and poorly coordinated efforts, issues with inter-model reproducibility, study design and statistical approaches, and difficulties with validation in patients. These challenges demand a strategic roadmap to facilitate the identification, characterization and clinical validation of biomarkers for epileptogenesis. In this Review, we summarize the state of the art with respect to biomarker research in epileptogenesis and propose a five-phase roadmap, adapted from those developed for cancer and Alzheimer disease, that provides a conceptual structure for biomarker research.

Topographical reorganization of brain functional connectivity during an early period of epileptogenesis

OBJECTIVE

The current study aims to investigate functional brain network representations during the early period of epileptogenesis.

METHODS

Eighteen rats with the intrahippocampal kainate model of mesial temporal lobe epilepsy were used for this experiment. Functional magnetic resonance imaging (fMRI) measurements were made 1 week after status epilepticus, followed by 2-4-month electrophysiological and video monitoring. Animals were identified as having (1) developed epilepsy (E+, n = 9) or (2) not developed epilepsy (E-, n = 6). Nine additional animals served as controls. Graph theory analysis was performed on the fMRI data to quantify the functional brain networks in all animals prior to the development of epilepsy. Spectrum clustering with the network features was performed to estimate their predictability in epileptogenesis.

RESULTS

Our data indicated that E+ animals showed an overall increase in functional connectivity strength compared to E- and control animals. Global network features and small-worldness of E- rats were similar to controls, whereas E+ rats demonstrated increased small-worldness, including increased reorganization degree, clustering coefficient, and global efficiency, with reduced shortest pathlength. A notable classification of the combined brain network parameters was found in E+ and E- animals. For the local network parameters, the E- rats showed increased hubs in sensorimotor cortex, and decreased hubness in hippocampus. The E+ rats showed a complete loss of hippocampal hubs, and the appearance of new hubs in the prefrontal cortex. We also observed that lesion severity was not related to epileptogenesis.

SIGNIFICANCE

Our data provide a view of the reorganization of topographical functional brain networks in the early period of epileptogenesis and how it can significantly predict the development of epilepsy. The differences from E- animals offer a potential means for applying noninvasive neuroimaging tools for the early prediction of epilepsy.

Experimental traumatic brain injury does not lead to lung infection

Traumatic brain injury (TBI) patients often experience post-traumatic infections, especially in the lung. Pulmonary infection is associated with unfavorable outcomes and increased mortality rates in TBI patients; however, our understanding of the underlying mechanisms is poor. Here we used a lateral fluid percussion injury (LFPI) model in rats to investigate whether TBI could lead to spontaneous lung infection. Analysis of bacterial load in lung tissue indicated no occurrence of spontaneous lung infection at 24 h, 48 h, and 7 d following LFPI. This may suggest that exogenous infectious agents play a crucial role in post-TBI infection in patients.

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.

Preface - Practical and theoretical considerations for performing a multi-center preclinical biomarker discovery study of post-traumatic epileptogenesis: lessons learned from the EpiBioS4Rx consortium

The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) is a NINDS funded Center-Without-Walls international study aimed at preventing epileptogenesis after traumatic brain injury (TBI). One objective of EpiBioS4Rx relates to preclinical biomarker discovery for post-traumatic epilepsy. In order to perform a statistically appropriately powered biomarker discovery study, EpiBioS4Rx has made a rigorous attempt to harmonize the preclinical procedures performed at the three EpiBioS4Rx centers, located in Finland, Australia, and the USA. Moreover, we have also performed a rigorous interim analysis of the success of procedural harmonization, which is reported in this virtual special issue. The analysis included harmonization of the production of animal model, blood sampling, electroencephalogram analyses (seizures, high-frequency oscillations) and magnetic resonance imaging analysis. Based on lessons learned, we propose a 3-stage protocol to facilitate the success of preclinical multicenter studies: preparation ⇨ testing ⇨ multicenter study. The need of funding for preparation and testing phases, which precede the actual multicenter study and are necessary for its success, should be taken into account in the design of funding schemes.

Informatics tools to assess the success of procedural harmonization in preclinical multicenter biomarker discovery study on post-traumatic epileptogenesis

The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) is a National Institutes for Neurological Diseases and Stoke funded Centers-Without-Walls international multidisciplinary study aimed at preventing epileptogenesis. The preclinical biomarker discovery in EpiBios4Rx applies a multicenter study design to allow the number of animals that are required for adequate statistical power for the analysis to be studied in an efficient manner. Further, the use of multiple centers mimics the clinical trial situation, and therefore potentially the chance of successful clinical translation of the outcomes of the study. Its successful implementation requires harmonization of procedures and data analyses between the three contributing centers in Finland, Australia, and USA. The objective of the present analysis was to develop metrics for analysis of the success of harmonization of procedures to guide further data analyses and plan the future multicenter preclinical studies. The interim analysis of data is based on the analysis of data from 212 rats with lateral fluid-percussion injury or sham-operation included in the biomarker discovery by April 30, 2018. The details of protocols, including production of injury, post-injury follow-up, blood sampling, electroencephalogram recording, and magnetic resonance imaging have been presented in the accompanying manuscripts in this Supplement. Implementation of protocols in EpiBios4Rx project participant centers was visualized in 2D using t-distributed stochastic neighborhood embedding (t-SNE). The protocols applied to each rat were presented as feature vectors of procedure related variables (e.g., impact pressure, anesthesia time). The total number of protocol features linked to each rat was 112. The missing data was accounted in visualization by utilizing imputation and adding the number of missing values as a third dimension to 2D t-SNE plot, resulting in a 3D overview of protocol data. Intraclass correlation coefficient (ICC) using Euclidean distances and area under receiver operating characteristic curve (AUC) of k-nearest neighbor classifier (KNN) were utilized to quantify the degree of clustering by center. Both subsets of data with incomplete protocol vectors omitted and missing protocol data imputed were assessed. Our data show that a visible clustering by center was observed in all t-SNE plots, except for day 7 neuroscores. Both ICC and AUC indicated clustering by center in all protocol variable subsets, excluding unimputed day 7 neuroscores (ICC 0.04 and AUC 0.6). ICC for imputed set of all protocol related variables was 0.1 and KNN AUC 0.92. In conclusion, both ICC and AUC indicated differences in protocol between EpiBios4Rx participating centers, which needs to be taken into account in data analysis. Importantly, the majority of observed differences are recoverable as they relate to insufficient updates in record keeping. While AUC score of KNN is a more sensitive measure for protocol harmonization than ICC for data that displays complex splintered clustering, ICC and AUC provide complementary measures to assess the degree of procedural harmonization. This experience should be helpful for other groups planning such multicenter post-traumatic epileptogenesis studies in the future.