Development and Evaluation of a Method for Automated Detection of Spreading Depolarizations in the Injured Human Brain.

BACKGROUND: Spreading depolarizations (SDs) occur in some 60% of patients receiving intensive care following severe traumatic brain injury and often occur at a higher incidence following serious subarachnoid hemorrhage and malignant hemisphere stroke (MHS); they are independently associated with worse clinical outcome. Detection of SDs to guide clinical management, as is now being advocated, currently requires continuous and skilled monitoring of the electrocorticogram (ECoG), frequently extending over many days. METHODS: We developed and evaluated in two clinical intensive care units (ICU) a software routine capable of detecting SDs both in real time at the bedside and retrospectively and also capable of displaying patterns of their occurrence with time. We tested this prototype software in 91 data files, each of approximately 24 h, from 18 patients, and the results were compared with those of manual assessment ("ground truth") by an experienced assessor blind to the software outputs. RESULTS: The software successfully detected SDs in real time at the bedside, including in patients with clusters of SDs. Counts of SDs by software (dependent variable) were compared with ground truth by the investigator (independent) using linear regression. The slope of the regression was 0.7855 (95% confidence interval 0.7149-0.8561); a slope value of 1.0 lies outside the 95% confidence interval of the slope, representing significant undersensitivity of 79%. R2 was 0.8415. CONCLUSIONS: Despite significant undersensitivity, there was no additional loss of sensitivity at high SD counts, thus ensuring that dense clusters of depolarizations of particular pathogenic potential can be detected by software and depicted to clinicians in real time and also be archived.

Which Spreading Depolarizations Are Deleterious To Brain Tissue?

Spreading depolarizations (SDs) are profound disruptions of cellular homeostasis that slowly propagate through gray matter and present an extraordinary metabolic challenge to brain tissue. Recent work has shown that SDs occur commonly in human patients in the neurointensive care setting and have established a compelling case for their importance in the pathophysiology of acute brain injury. The International Conference on Spreading Depolarizations (iCSD) held in Boca Raton, Florida, in September of 2018 included a discussion session focused on the question of "Which SDs are deleterious to brain tissue?" iCSD is attended by investigators studying various animal species including invertebrates, in vivo and in vitro preparations, diseases of acute brain injury and migraine, computational modeling, and clinical brain injury, among other topics. The discussion included general agreement on many key issues, but also revealed divergent views on some topics that are relevant to the design of clinical interventions targeting SDs. A draft summary of viewpoints offered was then written by a multidisciplinary writing group of iCSD members, based on a transcript of the session. Feedback of all discussants was then formally collated, reviewed and incorporated into the final document. It is hoped that this report will stimulate collection of data that are needed to develop a more nuanced understanding of SD in different pathophysiological states, as the field continues to move toward effective clinical interventions.

A computational biomarker of idiopathic generalized epilepsy from resting state EEG.

Epilepsy is one of the most common serious neurologic conditions. It is characterized by the tendency to have recurrent seizures, which arise against a backdrop of apparently normal brain activity. At present, clinical diagnosis relies on the following: (1) case history, which can be unreliable; (2) observation of transient abnormal activity during electroencephalography (EEG), which may not be present during clinical evaluation; and (3) if diagnostic uncertainty occurs, undertaking prolonged monitoring in an attempt to observe EEG abnormalities, which is costly. Herein, we describe the discovery and validation of an epilepsy biomarker based on computational analysis of a short segment of resting-state (interictal) EEG. Our method utilizes a computer model of dynamic networks, where the network is inferred from the extent of synchrony between EEG channels (functional networks) and the normalized power spectrum of the clinical data. We optimize model parameters using a leave-one-out classification on a dataset comprising 30 people with idiopathic generalized epilepsy (IGE) and 38 normal controls. Applying this scheme to all 68 subjects we find 100% specificity at 56.7% sensitivity, and 100% sensitivity at 65.8% specificity. We believe this biomarker could readily provide additional support to the diagnostic process.

Detection of spreading depolarization with intraparenchymal electrodes in the injured human brain.

BACKGROUND: Spreading depolarization events following ischemic and traumatic brain injury are associated with poor patient outcome. Currently, monitoring these events is limited to patients in whom subdural electrodes can be placed at open craniotomy. This study examined whether these events can be detected using intra-cortical electrodes, opening the way for electrode insertion via burr hole. METHODS: Animal work was carried out on adult Sprague-Dawley rats in a laboratory setting to investigate the feasibility of recording depolarization events. Subsequently, 8 human patients requiring craniotomy for traumatic brain injury or aneurysmal subarachnoid hemorrhage were monitored for depolarization events in an intensive care setting with concurrent strip (subdural) and depth (intra-parenchymal) electrode recordings. RESULTS: (1) Depolarization events can be reliably detected from intra-cortically placed electrodes. (2) A reproducible slow potential change (SPC) waveform morphology was identified from intra-cortical electrodes on the depth array. (3) The depression of cortical activity known to follow depolarization events was identified consistently from both intra-cortical and sub-cortical electrodes on the depth array. CONCLUSIONS: Intra-parenchymally sited electrodes can be used to consistently identify depolarization events in humans. This technique greatly extends the capability of monitoring for spreading depolarization events in injured patients, as electrodes can be sited without the need for craniotomy. The method provides a new investigative tool for the evaluation of the contribution of these events to secondary brain injury in human patients.

Real-Time Non-Invasive Imaging and Detection of Spreading Depolarizations through EEG: An Ultra-Light Explainable Deep Learning Approach.

A core aim of neurocritical care is to prevent secondary brain injury. Spreading depolarizations (SDs) have been identified as an important independent cause of secondary brain injury. SDs are usually detected using invasive electrocorticography recorded at high sampling frequency. Recent pilot studies suggest a possible utility of scalp electrodes generated electroencephalogram (EEG) for non-invasive SD detection. However, noise and attenuation of EEG signals makes this detection task extremely challenging. Previous methods focus on detecting temporal power change of EEG over a fixed high-density map of scalp electrodes, which is not always clinically feasible. Having a specialized spectrogram as an input to the automatic SD detection model, this study is the first to transform SD identification problem from a detection task on a 1-D time-series wave to a task on a sequential 2-D rendered imaging. This study presented a novel ultra-light-weight multi-modal deep-learning network to fuse EEG spectrogram imaging and temporal power vectors to enhance SD identification accuracy over each single electrode, allowing flexible EEG map and paving the way for SD detection on ultra-low-density EEG with variable electrode positioning. Our proposed model has an ultra-fast processing speed (<0.3 sec). Compared to the conventional methods (2 hours), this is a huge advancement towards early SD detection and to facilitate instant brain injury prognosis. Seeing SDs with a new dimension - frequency on spectrograms, we demonstrated that such additional dimension could improve SD detection accuracy, providing preliminary evidence to support the hypothesis that SDs may show implicit features over the frequency profile.

Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised.

Current explanatory concepts suggest seizures emerge from ongoing dynamics of brain networks. It is unclear how brain network properties determine focal or generalised seizure onset, or how network properties can be described in a clinically-useful manner. Understanding network properties would cast light on seizure-generating mechanisms and allow to quantify to which extent a seizure is focal or generalised. Functional brain networks were estimated in segments of scalp-EEG without interictal discharges (68 people with epilepsy, 38 controls). Simplified brain dynamics were simulated using a computer model. We introduce: Critical Coupling (Cc), the ability of a network to generate seizures; Onset Index (OI), the tendency of a region to generate seizures; and Participation Index (PI), the tendency of a region to become involved in seizures. Cc was lower in both patient groups compared with controls. OI and PI were more variable in focal-onset than generalised-onset cases. In focal cases, the regions with highest OI and PI corresponded to the side of seizure onset. Properties of interictal functional networks from scalp EEG can be estimated using a computer model and used to predict seizure likelihood and onset patterns. This may offer potential to enhance diagnosis through quantification of seizure type using inter-ictal recordings.

Clinical translation of microfluidic sensor devices: focus on calibration and analytical robustness.

We present approaches to facilitate the use of microfluidics outside of the laboratory, in our case within a clinical setting and monitoring from human subjects, where the complexity of microfluidic devices requires high skill and expertise and would otherwise limit translation. Microfluidic devices show great potential for converting complex laboratory protocols into on-chip processes. We demonstrate a flexible microfluidic platform can be coupled to microfluidic biosensors and used in conjunction with clinical microdialysis. The versatility is demonstrated through a series of examples of increasing complexity including analytical processes relevant to a clinical environment such as automatic calibration, standard addition, and more general processes including system optimisation, reagent addition and homogenous enzyme reactions. The precision and control offered by this set-up enables the use of microfluidics by non-experts in clinical settings, increasing uptake and usage in real-world scenarios. We demonstrate how this type of system is helpful in guiding physicians in real-time clinical decision-making.

3D printed microfluidic device for online detection of neurochemical changes with high temporal resolution in human brain microdialysate.

This paper presents the design, optimisation and fabrication of a mechanically robust 3D printed microfluidic device for the high time resolution online analysis of biomarkers in a microdialysate stream at microlitre per minute flow rates. The device consists of a microfluidic channel with secure low volume connections that easily integrates electrochemical biosensors for biomarkers such as glutamate, glucose and lactate. The optimisation process of the microfluidic channel fabrication, including for different types of 3D printer, is explained and the resulting improvement in sensor response time is quantified. The time resolution of the device is characterised by recording short lactate concentration pulses. The device is employed to record simultaneous glutamate, glucose and lactate concentration changes simulating the physiological response to spreading depolarisation events in cerebrospinal fluid dialysate. As a proof-of-concept study, the device is then used in the intensive care unit for online monitoring of a brain injury patient, demonstrating its capabilities for clinical monitoring.

Simultaneous monitoring of potassium, glucose and lactate during spreading depolarization in the injured human brain - Proof of principle of a novel real-time neurochemical analysis system, continuous online microdialysis.

Spreading depolarizations occur spontaneously and frequently in injured human brain. They propagate slowly through injured tissue often cycling around a local area of damage. Tissue recovery after an spreading depolarization requires greatly augmented energy utilisation to normalise ionic gradients from a virtually complete loss of membrane potential. In the injured brain, this is difficult because local blood flow is often low and unreactive. In this study, we use a new variant of microdialysis, continuous on-line microdialysis, to observe the effects of spreading depolarizations on brain metabolism. The neurochemical changes are dynamic and take place on the timescale of the passage of an spreading depolarization past the microdialysis probe. Dialysate potassium levels provide an ionic correlate of cellular depolarization and show a clear transient increase. Dialysate glucose levels reflect a balance between local tissue glucose supply and utilisation. These show a clear transient decrease of variable magnitude and duration. Dialysate lactate levels indicate non-oxidative metabolism of glucose and show a transient increase. Preliminary data suggest that the transient changes recover more slowly after the passage of a sequence of multiple spreading depolarizations giving rise to a decrease in basal dialysate glucose and an increase in basal dialysate potassium and lactate levels.

Recording, analysis, and interpretation of spreading depolarizations in neurointensive care: Review and recommendations of the COSBID research group.

Spreading depolarizations (SD) are waves of abrupt, near-complete breakdown of neuronal transmembrane ion gradients, are the largest possible pathophysiologic disruption of viable cerebral gray matter, and are a crucial mechanism of lesion development. Spreading depolarizations are increasingly recorded during multimodal neuromonitoring in neurocritical care as a causal biomarker providing a diagnostic summary measure of metabolic failure and excitotoxic injury. Focal ischemia causes spreading depolarization within minutes. Further spreading depolarizations arise for hours to days due to energy supply-demand mismatch in viable tissue. Spreading depolarizations exacerbate neuronal injury through prolonged ionic breakdown and spreading depolarization-related hypoperfusion (spreading ischemia). Local duration of the depolarization indicates local tissue energy status and risk of injury. Regional electrocorticographic monitoring affords even remote detection of injury because spreading depolarizations propagate widely from ischemic or metabolically stressed zones; characteristic patterns, including temporal clusters of spreading depolarizations and persistent depression of spontaneous cortical activity, can be recognized and quantified. Here, we describe the experimental basis for interpreting these patterns and illustrate their translation to human disease. We further provide consensus recommendations for electrocorticographic methods to record, classify, and score spreading depolarizations and associated spreading depressions. These methods offer distinct advantages over other neuromonitoring modalities and allow for future refinement through less invasive and more automated approaches.

Centromedian thalamic nuclei deep brain stimulation in refractory status epilepticus.

BACKGROUND: Refractory status epilepticus (RSE) is associated with high mortality. We report a potential treatment alternative. HYPOTHESIS: Deep brain stimulation (DBS) of the centromedian thalamic nuclei (CMN) can be effective in the treatment of RSE. METHODS: Report of the evolution of RSE after DBS of the CMN in a 27-year-old man. RESULTS: In the course of an encephalopathy of unknown origin, and after a cardiac arrest, the patient developed RSE with myoclonic jerks and generalized tonic-clonic seizures. The EEG showed continuous generalized periodic epileptiform discharges (GPEDS). Five weeks after RSE onset, bilateral DBS of the CMN was started. This treatment was immediately followed by disappearance of tonic-clonic seizures and GPEDS, suggesting a resolution of RSE. The patient continued having multifocal myoclonic jerks, probably subcortical in origin, which resolved after 4 weeks. The patient remained clinically stable for 2 months in a persistent vegetative state. CONCLUSIONS: The remission of RSE, the abolition of GPEDS, and the patient survival suggest that DBS of the CMN may be efficacious in the treatment of refractory, generalized status epilepticus.

Unwinding of the uniform lying helix structure in cholesteric liquid crystals next to a spatially uniform aligning surface.

The symmetry of the cholesteric uniform lying helix (ULH) structure, where the helix axis is aligned in a single direction parallel to the device substrates, is not compatible with a uniform surface alignment and an unwinding of the helical structure is expected at the interface. Fluorescence confocal polarizing microscopy experiments are performed on the interface between a bulk ULH and a uniform aligning surface (for both planar and homeotropic alignments). The results are analyzed in the framework of a finite difference numerical simulation based on the Frank elastic distortion, to determine relevant director structures. An optical model is introduced to predict three-dimensional fluorescence profiles for the structures. Comparison of experimental and theoretical results shows that the equilibrium structure of the system involves a continuous unwinding of the helix close to the surface.