Applications of near-infrared spectroscopy in neurocritical care.

Significance: Acute brain injuries are commonly encountered in the intensive care unit. Alterations in cerebrovascular physiology triggered by the initial insult can lead to neurological worsening, further brain injury, and poor outcomes. Robust methods for assessing cerebrovascular physiology continuously at the bedside are limited. Aim: In this review, we aim to assess the potential of near-infrared spectroscopy (NIRS) as a bedside tool to monitor cerebrovascular physiology in critically ill patients with acute brain injury as well as those who are at high risk for developing brain injury. Approach: We first review basic principles of cerebral blood flow regulation and how these are altered after brain injury. We then discuss the potential role for NIRS in different acute brain injuries. We pay specific attention to the potential for NIRS to (1) identify new brain injuries and clinical worsening, (2) non-invasively measure intracranial pressure (ICP) and cerebral autoregulation, and (3) identify optimal blood pressure (BP) targets that may improve patient outcomes. Results: A growing body of work supports the use of NIRS in the care of brain injured patients. NIRS is routinely used during cardiac surgeries to identify acute neurologic events, and there is some evidence that treatment algorithms using cerebral oximetry may result in improved outcomes. In acute brain injury, NIRS can be used to measure autoregulation to identify an "optimum" BP where autoregulation status is best preserved. Finally, NIRS has been utilized to identify oximetry thresholds that correlate with poor outcome as well as identify new focal intracranial hemorrhages. Conclusions: NIRS is emerging as a tool that can non-invasively measure brain function in critically ill patients. Future work will be aimed at technical refinements to improve diagnostic accuracy, as well as larger scale clinical trials that can establish a definitive impact on patient outcomes.

Improving Neurotrauma by Depolarization Inhibition With Combination Therapy: A Phase 2 Randomized Feasibility Trial.

BACKGROUND AND OBJECTIVES: Spreading depolarizations (SDs) are a pathological mechanism that mediates lesion development in cerebral gray matter. They occur in ∼60% of patients with severe traumatic brain injury (TBI), often in recurring and progressive patterns from days 0 to 10 after injury, and are associated with worse outcomes. However, there are no protocols or trials suggesting how SD monitoring might be incorporated into clinical management. The objective of this protocol is to determine the feasibility and efficacy of implementing a treatment protocol for intensive care of patients with severe TBI that is guided by electrocorticographic monitoring of SDs. METHODS: Patients who undergo surgery for severe TBI with placement of a subdural electrode strip will be eligible for enrollment. Those who exhibit SDs on electrocorticography during intensive care will be randomized 1:1 to either (1) standard care that is blinded to the further course of SDs or (2) a tiered intervention protocol based on efficacy to suppress further SDs. Interventions aim to block the triggering and propagation of SDs and include adjusted targets for management of blood pressure, CO 2 , temperature, and glucose, as well as ketamine pharmacotherapy up to 4 mg/kg/ hour. Interventions will be escalated and de-escalated depending on the course of SD pathology. EXPECTED OUTCOMES: We expect to demonstrate that electrocorticographic monitoring of SDs can be used as a real- time diagnostic in intensive care that leads to meaningful changes in patient management and a reduction in secondary injury, as compared with standard care, without increasing medical complications or adverse events. DISCUSSION: This trial holds potential for personalization of intensive care management by tailoring therapies based on monitoring and confirmation of the targeted neuronal mechanism of SD. Results are expected to validate the concept of this approach, inform refinement of the treatment protocol, and lead to larger-scale trials.

Prediction of intracranial pressure crises after severe traumatic brain injury using machine learning algorithms.

OBJECTIVE: Avoiding intracranial hypertension after traumatic brain injury (TBI) is a foundation of neurocritical care, to minimize secondary brain injury related to elevated intracranial pressure (ICP). However, this approach at best is reactive to episodes of intracranial hypertension, allowing for periods of elevated ICP before therapies can be initiated. Accurate prediction of ICP crises before they occur would permit clinicians to implement preventive strategies, minimize total time with ICP above threshold, and potentially avoid secondary injury. The objective of this study was to develop an algorithm capable of predicting the onset of ICP crises with sufficient lead time to enable application of preventative therapies. METHODS: Thirty-six patients admitted to a level I trauma center with severe TBI (Glasgow Coma Scale score < 8) between April 2015 and January 2019 who underwent continuous intraparenchymal ICP monitor placement were retrospectively identified. Continuous ICP data were extracted from each monitoring period (range 4-96 hours of monitoring). An ICP crisis was treated as a binary outcome, defined as ICP > 22 mm Hg for at least 75% of the data within a 5-minute interval. ICP data preceding each ICP crisis were grouped into four total data sets of 1- and 2-hour epochs, each with 10- to 20-minute lead-time intervals before an ICP crisis. Crisis and noncrisis events were identified from continuous time-series data and randomly split into 70% for training and 30% for testing, from a subset of 30 patients. Machine learning algorithms were trained to predict ICP crises, including light gradient boosting, extreme gradient boosting, and random forest. Accuracy and area under the receiver operating characteristic curve (AUC) were measured to compare performance. The most predictive algorithm was optimized using feature selection and hyperparameter tuning to avoid overfitting, and then tested on a validation subset of 5 patients. Precision, recall, F1 score, and accuracy were measured. RESULTS: The random forest model demonstrated the highest accuracy (range 0.82-0.88) and AUC (range 0.86-0.88) across all four data sets. Further validation testing revealed high precision (0.76), relatively low recall (0.46), and overall strong predictive performance (F1 score 0.57, accuracy 0.86) for ICP crises. Decision curve analysis showed that the model provided net benefit at probability thresholds above 0.1 and below 0.9. CONCLUSIONS: The presented model can provide accurate and timely forecasts of ICP crises in patients with severe TBI 10-20 minutes prior to their occurrence. If validated and implemented in clinical workflows, this algorithm can enable earlier intervention for ICP crises, more effective treatment of intracranial hypertension, and potentially improved outcomes following severe TBI.

Cardiac arrest: An interdisciplinary scoping review of clinical literature from 2020.

Objectives: The Interdisciplinary Cardiac Arrest Research Review (ICARE) group was formed in 2018 to conduct an annual search of peer-reviewed literature relevant to cardiac arrest. Now in its third year, the goals of the review are to highlight annual updates in the interdisciplinary world of clinical cardiac arrest research with a focus on clinically relevant and impactful clinical and population-level studies from 2020. Methods: A search of PubMed using keywords related to clinical research in cardiac arrest was conducted. Titles and abstracts were screened for relevance and sorted into 7 categories: Epidemiology & Public Health Initiatives; Prehospital Resuscitation, Technology & Care; In-Hospital Resuscitation & Post-Arrest Care; Prognostication & Outcomes; Pediatrics; Interdisciplinary Guidelines & Reviews; and a new section dedicated to the coronavirus disease 2019 (COVID-19) pandemic. Screened manuscripts underwent standardized scoring of methodological quality and impact on the respective fields by reviewer teams lead by a subject matter expert editor. Articles scoring higher than 99 percentiles by category were selected for full critique. Systematic differences between editors' and reviewers' scores were assessed using Wilcoxon signed-rank test. Results: A total of 3594 articles were identified on initial search; of these, 1026 were scored after screening for relevance and deduplication, and 51 underwent full critique. The leading category was Prehospital Resuscitation, Technology & Care representing 35% (18/51) of fully reviewed articles. Four COVID-19 related articles were included for formal review that was attributed to a relative lack of high-quality data concerning cardiac arrest and COVID-19 specifically by the end of the 2020 calendar year. No significant differences between editor and reviewer scoring were found among review articles (P = 0.697). Among original research articles, section editors scored a median 1 point (interquartile range, 0-3; P < 0.01) less than reviewers. Conclusions: Several clinically relevant studies have added to the evidence base for the management of cardiac arrest patients including methods for prognostication of neurologic outcome following arrest, airway management strategy, timing of coronary intervention, and methods to improve expeditious performance of key components of resuscitation such as chest compressions in adults and children.

Deviations from PRx-derived optimal blood pressure are associated with mortality after cardiac arrest.

AIM: Pressure reactivity index (PRx) provides a surrogate measurement of cerebrovascular autoregulation (CAR). We determined whether deviations from PRx-derived optimal mean arterial pressure (MAPopt) were associated with in-hospital mortality after adult cardiac arrest. METHODS: Retrospective analysis of post-cardiac arrest patients who had continuously recorded intracranial pressure (ICP) and MAP. PRx was calculated as a moving, linear correlation between ICP and MAP. Impaired CAR was defined as PRx ≥ 0.3. MAPopt was calculated using a multi-window weighted algorithm. The burdens of MAP < 5 mmHg below MAPopt (MAPopt-5) and > 5 mmHg above MAPopt (MAPopt + 5) were calculated by integrating the area between MAP and MAPopt-5 or MAPopt + 5 curves, respectively. Univariate logistic regression tested the association between burden of MAP < MAPopt-5 and outcome. RESULTS: Twenty-two patients were analyzed. Thirteen (59%) patients died before hospital discharge. Time (median [IQR]) between ROSC and monitoring initiation was 16 [14, 21] hours and duration of monitoring was 35 [22, 48] hours; neither differed between survivors and non-survivors. Median MAPopt was 89 [85, 97] mmHg and did not differ between survivors and non-survivors (89 [83, 94] vs. 91 [85, 105] mmHg, p = 0.64). Burden of MAP < MAPopt-5 was greater for non-survivors compared to survivors (OR 3.6 [95% CI 1.2-15.6]). Range of intact CAR (upper-lower limit) was narrower for non-survivors when compared to survivors (5 [0, 22] vs. 24 [7, 36] mmHg, p = 0.03). CONCLUSION: A greater burden of MAP below PRx-derived MAPopt-5 was associated with mortality after cardiac arrest. Non-survivors had a narrower range of intact CAR than survivors.

Hierarchical Cluster Analysis Identifies Distinct Physiological States After Acute Brain Injury.

BACKGROUND: Analysis of intracranial multimodality monitoring data is challenging, and quantitative methods may help identify unique physiological signatures that inform therapeutic strategies and outcome prediction. The aim of this study was to test the hypothesis that data-driven approaches can identify distinct physiological states from intracranial multimodality monitoring data. METHODS: This was a single-center retrospective observational study of patients with either severe traumatic brain injury or high-grade subarachnoid hemorrhage who underwent invasive multimodality neuromonitoring. We used hierarchical cluster analysis to group hourly values for heart rate, mean arterial pressure, intracranial pressure, brain tissue oxygen, and cerebral microdialysis across all included patients into distinct groups. Average values for measured physiological variables were compared across the identified clusters, and physiological profiles from identified clusters were mapped onto physiological states known to occur after acute brain injury. The distribution of clusters was compared between patients with favorable outcome (discharged to home or acute rehab) and unfavorable outcome (in-hospital death or discharged to chronic nursing facility). RESULTS: A total of 1704 observations from 20 patients were included. Even though the difference in mean values for measured variables between patients with favorable and unfavorable outcome were small, we identified four distinct clusters within our data: (1) events with low brain tissue oxygen and high lactate-to-pyruvate ratio-values (consistent with cerebral ischemia), (2) events with higher intracranial pressure values without evidence for ischemia (3) events which appeared to be physiologically "normal," and (4) events with high cerebral lactate without brain hypoxia (consistent with cerebral hyperglycolysis). Patients with a favorable outcome had a greater proportion of cluster 3 (normal) events, whereas patients with an unfavorable outcome had a greater proportion of cluster 1 (ischemia) and cluster 4 (hyperglycolysis) events (p < 0.0001, Fisher-Freeman-Halton test). CONCLUSIONS: A data-driven approach can identify distinct groupings from invasive multimodality neuromonitoring data that may have implications for therapeutic strategies and outcome predictions. These groupings could be used as classifiers to train machine learning models that can aid in the treatment of patients with acute brain injury. Further work is needed to replicate the findings of this exploratory study in larger data sets.

Deviations from NIRS-derived optimal blood pressure are associated with worse outcomes after pediatric cardiac arrest.

AIM: Evaluate cerebrovascular autoregulation (CAR) using near-infrared spectroscopy (NIRS) after pediatric cardiac arrest and determine if deviations from CAR-derived optimal mean arterial pressure (MAPopt) are associated with outcomes. METHODS: CAR was quantified by a moving, linear correlation between time-synchronized mean arterial pressure (MAP) and regional cerebral oxygenation, called cerebral oximetry index (COx). MAPopt was calculated using a multi-window weighted algorithm. We calculated burden (magnitude and duration) of MAP less than 5 mmHg below MAPopt (MAPopt - 5), as the area between MAP and MAPopt - 5 curves using numerical integration and normalized as percentage of monitoring duration. Unfavorable outcome was defined as death or pediatric cerebral performance category (PCPC) at hospital discharge ≥3 with ≥1 change from baseline. Univariate logistic regression tested association between burden of MAP less than MAPopt - 5 and outcome. RESULTS: Thirty-four children (median age 2.9 [IQR 1.5,13.4] years) were evaluated. Median COx in the first 24 h post-cardiac arrest was 0.06 [0,0.20]; patients spent 27% [19,43] of monitored time with COx ≥ 0.3. Patients with an unfavorable outcome (n = 24) had a greater difference between MAP and MAPopt - 5 (13 [11,19] vs. 9 [8,10] mmHg, p = 0.01) and spent more time with MAP below MAPopt - 5 (38% [26,61] vs. 24% [14,28], p = 0.03). Patients with unfavorable outcome had a higher burden of MAP less than MAPopt - 5 than patients with favorable outcome in the first 24 h post-arrest (187 [107,316] vs. 62 [43,102] mmHg × Min/Hr; OR 4.93 [95% CI 1.16-51.78]). CONCLUSIONS: Greater burden of MAP below NIRS-derived MAPopt - 5 during the first 24 h after cardiac arrest was associated with unfavorable outcomes.

A Full-Stack Application for Detecting Seizures and Reducing Data During Continuous Electroencephalogram Monitoring.

Continuous electroencephalogram monitoring is associated with lower mortality in critically ill patients; however, it is underused due to the resource-intensive nature of manually interpreting prolonged streams of continuous electroencephalogram data. Here, we present a novel real-time, machine learning-based alerting and monitoring system for epilepsy and seizures that dramatically reduces the amount of manual electroencephalogram review. METHODS: We developed a custom data reduction algorithm using a random forest and deployed it within an online cloud-based platform, which streams data and communicates interactively with caregivers via a web interface to display algorithm results. We developed real-time, machine learning-based alerting and monitoring system for epilepsy and seizures on continuous electroencephalogram recordings from 77 patients undergoing routine scalp ICU electroencephalogram monitoring and tested it on an additional 20 patients. RESULTS: We achieved a mean seizure sensitivity of 84% in cross-validation and 85% in testing, as well as a mean specificity of 83% in cross-validation and 86% in testing, corresponding to a high level of data reduction. This study validates a platform for machine learning-assisted continuous electroencephalogram analysis and represents a meaningful step toward improving utility and decreasing cost of continuous electroencephalogram monitoring. We also make our high-quality annotated dataset of 97 ICU continuous electroencephalogram recordings public for others to validate and improve upon our methods.

Neuromonitoring After Cardiac Arrest: Can Twenty-First Century Medicine Personalize Post Cardiac Arrest Care?

Cardiac arrest survivors comprise a heterogeneous population, in which the etiology of arrest, systemic and neurologic comorbidities, and sequelae of post-cardiac arrest syndrome influence the severity of secondary brain injury. The degree of secondary neurologic injury can be modifiable and is influenced by factors that alter cerebral physiology. Neuromonitoring techniques provide tools for evaluating the evolution of physiologic variables over time. This article reviews the pathophysiology of hypoxic-ischemic brain injury, provides an overview of the neuromonitoring tools available to identify risk profiles for secondary brain injury, and highlights the importance of an individualized approach to post cardiac arrest care.

Cerebrovascular pressure reactivity and intracranial pressure are associated with neurologic outcome after hypoxic-ischemic brain injury.

AIM: We evaluated the association of physiological parameters measured by intracranial multimodality neuromonitoring with neurologic outcome in a consecutive series of patients with hypoxic-ischemic brain injury (HIBI). METHODS: We retrospectively identified all patients with HIBI who underwent combined invasive intracranial pressure (ICP) and brain tissue oxygen (PbtO2) monitoring over a 3 year period. Cerebrovascular pressure reactivity index (PRx) was calculated continuously as a surrogate of cerebral autoregulation. Favorable outcome was defined as recovery of consciousness (Glasgow Coma Scale motor score = 6). Differences in mean ICP, PRx and PbtO2 for the entire monitoring period across outcomes were measured. Logistic regression and area under receiver operating characteristic (AUROC) curve were used to assess the association of each monitoring parameter with neurologic outcome. RESULTS: We analyzed data from 36 patients. Most (89%) had an antecedent sudden cardiac arrest. Favorable outcome occurred in 8 (22%) patients. ICP and PRx were higher in patients with unfavorable outcome (ICP: 26 ±â€¯4.1 mmHg vs 7.5 ±â€¯2 mmHg, p = 0.0002; PRx: 0.51 ±â€¯0.05 vs 0.11 ±â€¯0.05, p < 0.0001). There was no significant difference in PbtO2 between groups (unfavorable: 20 ±â€¯2.4 mmHg vs favorable: 25 ±â€¯1.5 mmHg, p = 0.12). Both ICP (AUROC 0.84, 95%CI 0.72-0.98, p = 0.003) and PRx (AUROC 0.94, 95%CI 0.85-1, p = 0.0002) discriminated between favorable and unfavorable outcome, in contrast to PbtO2, (AUROC 0.59, 95%CI 0.39-0.78, p = 0.52). ICP > 15 mmHg, PRx > 0.2, and PbtO2 < 18 mmHg had sensitivity/specificity of 68%/100%, 89%/88%, and 40%/100% respectively for discriminating outcomes. CONCLUSION: Cerebrovascular pressure reactivity and intracranial pressure appear to be associated with neurologic outcome in patients with HIBI.

Physiological Signatures of Brain Death Uncovered by Intracranial Multimodal Neuromonitoring.

BACKGROUND: The physiological and neurochemical changes that accompany brain death are not well described. MATERIALS AND METHODS: A retrospective observational study of patients with acute brain injury who underwent intracranial multimodality neuromonitoring between October 2015 and June 2018. Patients were included for analysis either if brain death was diagnosed or refractory intracranial hypertension with persistent equalization of intracranial pressure (ICP) and mean arterial pressure (MAP) developed. RESULTS: Of 114 patients who underwent invasive neuromonitoring, 11 cases with MAP/ICP equalization were identified. Of those, 9 were declared brain dead based on accepted national and institutional criteria. An additional 2 cases with MAP/ICP equalization who died after withdrawal of life-sustaining therapies were identified. Of the 11 identified patients, 10 had continuous monitoring data available for analysis. Cerebral microdialysis data were available for 4 patients.In the 10 cases with available continuous data, ICP/MAP equalization was associated with marked reduction of cerebral blood flow and brain tissue oxygen tension to near zero levels as well as a significant decrease in brain temperature compared with body temperature. In the 4 patients with microdialysis monitoring, ICP/MAP equalization resulted in a near complete depletion of cerebral glucose and pyruvate, as well as a marked rise in cerebral glycerol. Finally, ICP/MAP equalization was accompanied by complete loss of cerebrovascular pressure reactivity, decrease in intracranial pulse pressure, and a paradoxical improvement of ICP waveform morphology. CONCLUSIONS: A characteristic set of changes in cerebrovascular physiology and neurochemistry occurs during brain death. These changes can be identified by intracranial neuromonitoring.

Association of MRI Brain Injury With Outcome After Pediatric Out-of-Hospital Cardiac Arrest.

OBJECTIVE: To determine the association between the extent of diffusion restriction and T2/fluid-attenuated inversion recovery (FLAIR) injury on brain MRI and outcomes after pediatric out-of-hospital cardiac arrest (OHCA). METHODS: Diffusion restriction and T2/FLAIR injury were described according to the pediatric MRI modification of the Alberta Stroke Program Early Computed Tomography Score (modsASPECTS) for children from 2005 to 2013 who had an MRI within 14 days of OHCA. The primary outcome was unfavorable neurologic outcome defined as ≥1 change in Pediatric Cerebral Performance Category (PCPC) from baseline resulting in a hospital discharge PCPC score 3, 4, 5, or 6. Patients with unfavorable outcomes were further categorized into alive with PCPC 3-5, dead due to withdrawal of life-sustaining therapies for poor neurologic prognosis (WLST-neuro), or dead by neurologic criteria. RESULTS: We evaluated MRI scans from 77 patients (median age 2.21 [interquartile range 0.44, 13.07] years) performed 4 (2, 6) days postarrest. Patients with unfavorable outcomes had more extensive diffusion restriction (median 7 [4, 10.3] vs 0 [0, 0] regions, p < 0.001) and T2/FLAIR injury (5.5 [2.3, 8.2] vs 0 [0, 0.75] regions, p < 0.001) compared to patients with favorable outcomes. Area under the receiver operating characteristic curve for the extent of diffusion restriction and unfavorable outcome was 0.96 (95% confidence interval [CI] 0.91, 0.99) and 0.92 (95% CI 0.85, 0.97) for T2/FLAIR injury. There was no difference in extent of diffusion restriction between patients who were alive with an unfavorable outcome and patients who died from WLST-neuro (p = 0.11). CONCLUSIONS: More extensive diffusion restriction and T2/FLAIR injury on the modsASPECTS score within the first 14 days after pediatric cardiac arrest was associated with unfavorable outcomes at hospital discharge.

Cardiac arrest: An interdisciplinary review of the literature from 2018.

OBJECTIVES: The Interdisciplinary Cardiac Arrest Research Review (ICARE) group was formed in 2018 to conduct a systematic annual search of peer-reviewed literature relevant to cardiac arrest (CA). The goals of the review are to illustrate best practices and help reduce knowledge silos by disseminating clinically relevant advances in the field of CA across disciplines. METHODS: An electronic search of PubMed using keywords related to CA was conducted. Title and abstracts retrieved by these searches were screened for relevancy, separated by article type (original research or review), and sorted into 7 categories. Screened manuscripts underwent standardized scoring of overall methodological quality and importance. Articles scoring higher than 99 percentiles by category-type were selected for full critique. Systematic differences between editors and reviewer scores were assessed using Wilcoxon signed-rank test. RESULTS: A total of 9119 articles were identified on initial search; of these, 1214 were scored after screening for relevance and deduplication, and 80 underwent full critique. Prognostication & Outcomes category comprised 25% and Epidemiology & Public Health 17.5% of fully reviewed articles. There were no differences between editor and reviewer scoring. CONCLUSIONS: The total number of articles demonstrates the need for an accessible source summarizing high-quality research findings to serve as a high-yield reference for clinicians and scientists seeking to absorb the ever-growing body of CA-related literature. This may promote further development of the unique and interdisciplinary field of CA medicine.

IRIS: A Modular Platform for Continuous Monitoring and Caretaker Notification in the Intensive Care Unit.

OBJECTIVE: New approaches are needed to interpret large amounts of physiologic data continuously recorded in the ICU. We developed and prospectively validated a versatile platform (IRIS) for real-time ICU physiologic monitoring, clinical decision making, and caretaker notification. METHODS: IRIS was implemented in the neurointensive care unit to stream multimodal time series data, including EEG, intracranial pressure (ICP), and brain tissue oxygenation (PbtO2), from ICU monitors to an analysis server. IRIS was applied for 364 patients undergoing continuous EEG, 26 patients undergoing burst suppression monitoring, and four patients undergoing intracranial pressure and brain tissue oxygen monitoring. Custom algorithms were used to identify periods of elevated ICP, compute burst suppression ratios (BSRs), and detect faulty or disconnected EEG electrodes. Hospital staff were notified of clinically relevant events using our secure API to route alerts through a password-protected smartphone application. RESULTS: Sustained increases in ICP and concordant decreases in PbtO2 were reliably detected using user-defined thresholds and alert throttling. BSR trends computed by the platform correlated highly with manual neurologist markings (r2 0.633-0.781; p < 0.0001). The platform identified EEG electrodes with poor signal quality with 95% positive predictive value, and reduced latency of technician response by 93%. CONCLUSION: This study validates a flexible real-time platform for monitoring and interpreting ICU data and notifying caretakers of actionable results, with potential to reduce the manual burden of continuous monitoring services on care providers. SIGNIFICANCE: This work represents an important step toward facilitating translational medical data analytics to improve patient care and reduce health care costs.

Quantification of cerebral blood flow in adults by contrast-enhanced near-infrared spectroscopy: Validation against MRI.

The purpose of this study was to assess the accuracy of absolute cerebral blood flow (CBF) measurements obtained by dynamic contrast-enhanced (DCE) near-infrared spectroscopy (NIRS) using indocyanine green as a perfusion contrast agent. For validation, CBF was measured independently using the MRI perfusion method arterial spin labeling (ASL). Data were acquired at two sites and under two flow conditions (normocapnia and hypercapnia). Depth sensitivity was enhanced using time-resolved detection, which was demonstrated in a separate set of experiments using a tourniquet to temporally impede scalp blood flow. A strong correlation between CBF measurements from ASL and DCE-NIRS was observed (slope = 0.99 ± 0.08, y-intercept = -1.7 ± 7.4 mL/100 g/min, and R2 = 0.88). Mean difference between the two techniques was 1.9 mL/100 g/min (95% confidence interval ranged from -15 to 19 mL/100g/min and the mean ASL CBF was 75.4 mL/100 g/min). Error analysis showed that structural information and baseline absorption coefficient were needed for optimal CBF reconstruction with DCE-NIRS. This study demonstrated that DCE-NIRS is sensitive to blood flow in the adult brain and can provide accurate CBF measurements with the appropriate modeling techniques.

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.

Defining a Taxonomy of Intracranial Hypertension: Is ICP More Than Just a Number?

Intracranial pressure (ICP) monitoring and control is a cornerstone of neuroanesthesia and neurocritical care. However, because elevated ICP can be due to multiple pathophysiological processes, its interpretation is not straightforward. We propose a formal taxonomy of intracranial hypertension, which defines ICP elevations into 3 major pathophysiological subsets: increased cerebral blood volume, masses and edema, and hydrocephalus. (1) Increased cerebral blood volume increases ICP and arises secondary to arterial or venous hypervolemia. Arterial hypervolemia is produced by autoregulated or dysregulated vasodilation, both of which are importantly and disparately affected by systemic blood pressure. Dysregulated vasodilation tends to be worsened by arterial hypertension. In contrast, autoregulated vasodilation contributes to intracranial hypertension during decreases in cerebral perfusion pressure that occur within the normal range of cerebral autoregulation. Venous hypervolemia is produced by Starling resistor outflow obstruction, venous occlusion, and very high extracranial venous pressure. Starling resistor outflow obstruction tends to arise when cerebrospinal fluid pressure causes venous compression to thus increase tissue pressure and worsen tissue edema (and ICP elevation), producing a positive feedback ICP cycle. (2) Masses and edema are conditions that increase brain tissue volume and ICP, causing both vascular compression and decrease in cerebral perfusion pressure leading to oligemia. Brain edema is either vasogenic or cytotoxic, each with disparate causes and often linked to cerebral blood flow or blood volume abnormalities. Masses may arise from hematoma or neoplasia. (3) Hydrocephalus can also increase ICP, and is either communicating or noncommunicating. Further research is warranted to ascertain whether ICP therapy should be tailored to these physiological subsets of intracranial hypertension.

What Should a Clinician Do When Spreading Depolarizations are Observed in a Patient?

The International Conference on Spreading Depolarizations (iCSD) held in Boca Raton, Florida, in the September of 2018 devoted a section to address the question, "What should a clinician do when spreading depolarizations are observed in a patient?" Discussants represented a wide range of expertise, including neurologists, neurointensivists, neuroradiologists, neurosurgeons, and pre-clinical neuroscientists, to provide both clinical and basic pathophysiology perspectives. 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 formally collated, reviewed, and incorporated into the final document which was subsequently approved by all authors.