Next Article in Journal
Obatoclax, a Pan-BCL-2 Inhibitor, Targets Cyclin D1 for Degradation to Induce Antiproliferation in Human Colorectal Carcinoma Cells
Next Article in Special Issue
Pathophysiology and the Monitoring Methods for Cardiac Arrest Associated Brain Injury
Previous Article in Journal
Osteogenic Differentiation in Healthy and Pathological Conditions
Previous Article in Special Issue
Stem Cells and Labeling for Spinal Cord Injury
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJMS
Volume 18
Issue 1
10.3390/ijms18010043
ijms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Brain Monitoring in Critically Neurologically Impaired Patients

by
Salazar Jones
1,
Gary Schwartzbauer
1,2,3 and
Xiaofeng Jia
1,4,5,6,7,*
1
Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA
2
R Adams Cowley Shock Trauma Center, University of Maryland School of Medicine, Baltimore, MD 21201, USA
3
Institute for Global Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA
4
Department of Orthopaedics, University of Maryland School of Medicine, Baltimore, MD 21201, USA
5
Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
6
Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
7
Department of Anesthesiology and Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2017, 18(1), 43; https://doi.org/10.3390/ijms18010043
Submission received: 14 November 2016 / Revised: 10 December 2016 / Accepted: 21 December 2016 / Published: 27 December 2016
(This article belongs to the Special Issue Neurological Injuries’ Monitoring, Tracking and Treatment 2016)
Browse Figure
Versions Notes

Abstract

:
Assessment of neurologic injury and the evolution of severe neurologic injury is limited in comatose or critically ill patients that lack a reliable neurologic examination. For common yet severe pathologies such as the comatose state after cardiac arrest, aneurysmal subarachnoid hemorrhage (aSAH), and severe traumatic brain injury (TBI), critical medical decisions are made on the basis of the neurologic injury. Decisions regarding active intensive care management, need for neurosurgical intervention, and withdrawal of care, depend on a reliable, high-quality assessment of the true state of neurologic injury, and have traditionally relied on limited assessments such as intracranial pressure monitoring and electroencephalogram. However, even within TBI there exists a spectrum of disease that is likely not captured by such limited monitoring and thus a more directed effort towards obtaining a more robust biophysical signature of the individual patient must be undertaken. In this review, multimodal monitoring including the most promising serum markers of neuronal injury, cerebral microdialysis, brain tissue oxygenation, and pressure reactivity index to access brain microenvironment will be discussed with their utility among specific pathologies that may help determine a more complete picture of the neurologic injury state for active intensive care management and long-term outcomes. Goal-directed therapy guided by a multi-modality approach appears to be superior to standard intracranial pressure (ICP) guided therapy and should be explored further across multiple pathologies. Future directions including the application of optogenetics to evaluate brain injury and recovery and even as an adjunct monitoring modality will also be discussed.

1. Introduction

Brain monitoring is important in critical clinical scenarios where the extent or evolution of neurologic injury is unknown. Common situations include the comatose state after cardiac arrest, poor grade aneurysmal subarachnoid hemorrhage (aSAH), and severe traumatic brain injury (TBI) et al. The extent of neurologic injury and injury progression are crucial in determining prognosis and guiding intensive care strategies to ameliorate the neurologic injury [1,2].
By examining several clinical diagnoses, a glimpse of the scale of critically ill patients in whom brain monitoring is of importance can be seen. Each year, around 235,000 patients are hospitalized in the United States with traumatic brain injury with a significant portion having severe TBI (Glasgow Coma Scale score ≤ 8) [3]. Around 300,000 individuals have out-of-hospital cardiac arrests each year [1]. Of those comatose after cardiac arrest, half will not regain consciousness [4]. In the United States, about 30,000 persons each year have an aneurysmal subarachnoid hemorrhage with mortality close to 50% [5]. The impact of brain monitoring lies in the common thread among these pathologies. There is an initial inciting event that causes primary neurologic injury of unknown degree, followed by dynamic pathophysiological changes causing secondary neurologic injury. In the comatose or sedated patient, even the most attentive clinicians can often be in the dark about evolving secondary neurologic injury.

2. Objective of Brain Monitoring

Early determination of neurologic prognosis would decrease situations of prolonged medical resource utilization that does not provide any additional clinical benefit to the patient, but more importantly avoid withdraw of life support prematurely for those patients that may have a chance to recover later. As a supplement to the neurologic examination, other testing including electrophysiology markers such as electroencephalography (EEG) [6,7,8,9,10] and somatosensory evoked potentials [11,12] developed from preclinical studies with or without quantitative methods have been used in determining clinical prognosis after cardiac arrest patients treated with targeted temperature management [1,2]. In patients undergoing therapeutic hypothermia, sedation and neuromuscular blockade limit the ability of clinicians to obtain a reliable neurologic exam. For such patients, the main mechanisms of injury—ischemia and subsequent reperfusion injury to the brain—occur at the time of cardiac arrest and return of circulation [13]. As such, it is reasonable to seek methods to determine prognosis earlier in the care of comatose post-cardiac arrest patients. The information obtained would allow for more appropriate communication with patients’ families to aid in goals of care.
In other pathologies such as aSAH and TBI, there is both an initial primary injury and secondary injury that occurs over the ensuing weeks. The evolving secondary injury may often predominate as the most significant determinant of neurologic outcome [14]. This is especially the case when such evolution requires interventions such as decompressive craniectomy in severe TBI patients or endovascular therapy for vasospasm in aSAH patients. Critical patients in the intensive care unit (ICU) also are subject to additional systemic insults causing secondary neurologic injury including fever, respiratory failure, anemia, seizure, and infection [15]. Each insult can place patients on a lower recovery trajectory, hence, measures are taken to address any systemic insult. However, a more refined approach is needed to identify and address changes in the local brain environment that occur without a systemic correlate. Multiple techniques for brain monitoring are available (See Table 1).
In this review, we focus on techniques such as serum markers of neuronal injury, intracranial pressure monitoring, microdialysis, pressure reactivity index, and brain tissue oxygenation that are currently available at the bedside for clinical decision making. Optogenetics is also presented as the potential future of brain monitoring. Though the following techniques are discussed individually, the astute clinician will utilize multiple methods to generate a more complete clinical picture. Available multimodality monitors are capable of probes for microdialysis, brain tissue oxygenation, and intracranial pressure monitoring.

3. Serum Markers of Glial or Neuronal Injury

In the area of severe neurologic injury, serum markers of glial or neuronal injury are being investigated as measures of neurologic injury and prognosis.
Neuron specific enolase (NSE) is a glycolytic enzyme expressed in the cytosol of neuronal and glial cells. It is unique in that it has additional functions in the inflammatory response to injury after spinal cord injury, hypoxic-ischemic brain injury, and traumatic brain injury [17]. NSE goes to the cell surface and serves as a receptor to the serine protease plasminogen to stimulate degradation of the extracellular matrix [17]. Rech et al. [18] demonstrated in 45 post-cardiac arrest patients, that higher NSE levels within 48 h of arrest were associated with unfavorable outcomes at 6 months and suggested a cut-off of 60 ng/mL to have 100% specificity, albeit 35% sensitivity, in predicting unfavorable outcomes. In out-of-hospital cardiac arrest patients, Stammet et al. [19] demonstrated in 686 patients randomized to targeted therapeutic hypothermia at 33 or 36 °C that serial NSE levels were not affected by hypothermia and were higher at all measurements within 72 h in patients with unfavorable outcomes at 6 months. A cut-off of 45 ng/mL at the 72 h time point had a specificity of 99% and sensitivity of 54% to predict an unfavorable outcome. In aSAH, Tawk et al. [20] found patients with NSE levels >15 ng/mL had a moderate correlation with worse clinical severity and greater disability at discharge. In TBI, NSE has a less clear role. Higher levels of NSE are associated with unfavorable outcomes, but a specific laboratory cutoff value has not been determined and NSE has poor discrimination among the unfavorable outcomes [21]. Limitations of NSE testing are extracranial sources of NSE [22] and surgery can increase the levels of serum NSE [23].
Another serum marker of interest is S100B. S100B is a calcium-binding protein present in cytosol of astrocytes important for astrocyte activation in brain injury repair [24]. In the area of cardiac arrest, elevated S100B levels in patients correlate with severity of neurologic injury with persistently elevated levels >0.414 ng/mL at 72 h predicting mortality with 100% specificity [25,26]. In aSAH, elevated S100B levels aren’t able to predict delayed cerebral ischemia that can occur from vasospasm but are associated with worse Glasgow Outcome Score at 6 months [27,28]. In severe TBI, S100B levels 12 h from the time of trauma are predictive of Glasgow Outcome Score at 1 year [29]. S100B levels are subject to extracranial sources as well which presents limitations in multi-trauma patients and post cardiac arrest patients [22,30]. Of note for those with severe TBI, surgery or insertion of an external ventricular drain can affect serum levels of S100B [23,31].
Glial fibrillary acidic protein (GFAP), an astrocytic intermediate filament, has also been investigated serum marker of neuronal injury. In the area of cardiac arrest, GFAP levels are generally elevated in patients with poor outcomes, but there is inadequate discrimination among unfavorable outcomes to truly aid in predicting specific outcomes [32,33]. In aSAH patients, elevated levels of GFAP on admission correlate with severity of aSAH and represented a ten times more likelihood of poor outcome at the time of hospital discharge [34]. GFAP levels were elevated with secondary events such as aneurysm re-bleed and moderately correlated with poor outcome at 1 year (r = −0.48) [35]. Using a serum cutoff value of 0.15 µg/L to classify elevated GFAP levels was determined to be highly sensitive (92%) but not very specific (40%) in predicting unfavorable outcomes in aSAH [35]. In severe TBI, GFAP levels on admission moderately correlate with severity on trauma but is not as clinically useful in predicting outcome [36]. However, an elevated GFAP level (>11.14 ng/mL) at day 7 is an independent predictor of unfavorable outcome at 1 year (sensitivity 81.8%, specificity 88.9%) [37]. In patients with mild TBI, an elevated GFAP can predict those patients that are likely to have intracranial lesions on computed tomography (receiver-operator characteristics AUC 0.84) [38]. Papa et al. [39] showed that GFAP levels could predict which patients with mild to moderate TBI would need a neurosurgical intervention within the 7 days after trauma.

4. Cerebral Blood Flow Monitoring

Abnormalities in cerebral blood flow (CBF) are central to pathologies such as vasospasm in aSAH, traumatic brain injury, and in cardiac arrest. Direct clinical use in the intensive care unit are in optimizing a patient’s blood pressure, diagnosing vasospasm in aSAH, and for brain death examination. There are several methods for monitoring cerebral blood flow including: transcranial doppler, perfusion computed tomography (CT), diffusion correlation spectroscopy, and laser speckle imaging. Transcranial doppler is a well understood modality that assesses blood velocity in the major intracranial vessels and can be performed at the bedside. Intuitively, absence of velocity is seen in the absence of flow, however, relying on a negative finding can be problematic given operator dependence. In addition, only the major intracranial vessels are amenable to doppler investigation which may not be representative of the microvascular circulation [40]. The information obtained constitutes a single data point in time as opposed to a continuous monitoring tool. Moreover, in vasospasm for aSAH, the correct interpretation is to suspect decreased flow in the presence of elevated velocities. When compared to cerebral blood flow measured using continuous arterial spin labeling magnetic resonance imaging (MRI) in healthy patients, transcranial doppler velocities had no correlation [40].
Perfusion CT is a well-accepted and widely used method for measuring cerebral blood flow. Obtaining a perfusion CT requires the transport of critically injured patients to a CT scanner elsewhere in the hospital. The data obtained, although useful, still constitutes one data point in time, thus not suitable as a monitor. Near-infrared spectroscopy (NIS) takes advantage of differences in spectra of hemoglobin bound (HbO2) and unbound to oxygen to measure changes in HbO2 concentration, thus a surrogate of cerebral blood flow. NIS is a non-invasive method involving optical probes placed on the scalp with a maximum depth of tissue of approximately 2–3 cm [41]. NIS has been used as a research tool to study cerebral blood flow and cerebral metabolism in TBI [42]. As a measure of cerebral oxygenation, NIS is likely still inferior to invasive PbtO2 monitoring [43]. In the aSAH population, NIS has been used to monitor efficacy of vasospasm treatment [44]. Diffuse correlation spectroscopy (DCS) represents a non-invasive method of using optical probes to continuously measure changes in blood flow, thus measuring a relative CBF. DCS has been shown in pre-clinical models to identify cerebral blood flow changes in line with perfusion CT [45]. DCS combined with NIS has been validated in the neuro-intensive care unit with a good correlation of cerebral blood flow findings compared to xenon enhanced perfusion CT (r = 0.73) [46]. More clinical studies will be needed to determine if DCS or combined DCS/NIS can predict or identify early patients with vasospasm in aSAH.
Laser speckle imaging (LSI) is another non-invasive technique to image cerebral vasculature. LSI relies on the scattering of photons when photons strike particles in motion (e.g., red blood cells) [47,48]. LSI has been used in the pre-clinical research models to image the vasculature in response to hypothermia, peripheral electrical stimulation and for real-time monitoring of cerebral blood flow in rats after cardiac arrest [49,50,51]. LSI is still an emerging technology for clinical use, while translational researches are moving this technology from bench to bedside [52]. LSI is limited by the lack of depth resolution. Currently, LSI can be used after a window in the skull has been created. Intraoperative LSI during neurosurgical procedures have properly shown increase blood flow after bypass procedures and decrease in blood flow after coagulation of cortical vessels [53,54]. Further development is needed to advance incorporation of LSI when an intact human skull is in place to supplant LSI as a monitoring tool.

5. Intracranial Pressure Monitoring

Intracranial pressure (ICP) monitoring is a well-recognized method of monitoring for intracranial changes that can portend neurological worsening. The development of mass lesions including intracranial hemorrhage and cerebral edema are accompanied by a rise in intracranial pressure. If needed in severe TBI, decompressive craniectomy in cases of persistently elevated ICPs can be performed to increase overall survival [55]. As such, ICP monitoring has a well-defined role in TBI as recommended by the Brain Trauma Foundation [56]. Placement of an ICP monitor requires an invasive procedure for placement of a probe most commonly within the parenchyma or catheter within the ventricles. The use of an intraventricular catheter is advantageous for its ability to remove CSF as a therapy. It is not firmly established that the institution of ICP monitoring for severe TBI patients improves long-term outcomes [57]. Results from the Benchmark Evidence from South American Trials: Treatment of Intracranial Pressure (BEST TRIP) trial suggest that ICP monitoring in TBI is no better than clinical examination and CT imaging for outcomes 14-day and 6-month mortality [58]. Other reports have suggested the use of ICP monitoring helps to identify those TBI patients that need craniotomy/craniectomy and reduces in-hospital mortality [57,59]. In aSAH, elevated ICP is associated with worse outcomes, but strong data showing the prognostic value of ICP monitoring is lacking [60].
ICP monitoring has several limitations. Not all pathologies have the potential for the development of a mass lesion and, thus, a rise in ICP. The comatose state after cardiac arrest is an example where ICP monitoring does not have a clear role [61]. In addition, a rise in ICP is non-specific and may be secondary to dysfunctional autoregulation or hyperemia. Clinical suspicion of worrisome pathology based on a rise in ICP has to be confirmed by imaging. ICP monitoring, however, can be combined with other forms of cerebral monitoring for a more complete neurologic picture.

6. Cerebral Microdialysis—Assessment of Brain Microenvironment

Cerebral microdialysis is a form of invasive monitoring that requires insertion of a small catheter into the brain parenchyma. Invasive monitors often are inserted into the right frontal lobe. Endogenous molecules such as glucose, neurotransmitters, and products of metabolism are allowed to equilibrate within the dialysate. The concentration of endogenous molecules can then be measured from the dialysate. Common microdialysis analysis measures glutamate, glucose, lactate, and pyruvate.
Glutamate is an excitatory neurotransmitter that can increase brain activity and metabolic requirements. Increased cerebral glutamate has been seen in cardiac arrest and aSAH and implicated in ischemia and mediating apoptosis of neurons [62,63,64]. The excitatory neurotransmitter glutamate in high amounts can lead to excitotoxicity via spreading depolarizations that lead to increased energy substrate depletion and anaerobic metabolism. Hinzman et al. [65] demonstrated by placing a subdural electrode strip adjacent to a microdialysis catheter in 16 severe TBI patients that increasing glutamate was seen with increasing frequency of spreading depolarizations and metabolic crisis.
Lactate and pyruvate are two byproducts of metabolism. Pyruvate is the end product of glycoysis. In the setting of anaerobic respiration, pyruvate is converted to lactate. The ratio of lactate to pyruvate gives information about the overall state of oxygen delivery for cellular aerobic respiration. An elevated lactate to pyruvate ratio (>40) is worrisome for a metabolic crisis with possible causes including ischemia, hypoxia, low glucose availability and mitochondrial dysfunction. Elevated lactate to pyruvate ratios indicating ischemia have been observed after cardiac arrest [62]. Of note, lactate by itself may be elevated due to excessive glycolysis. Oddo et al. [66] showed that a state of cerebral hyperglycolysis was shown to be predictive of a good 6-month outcome in aSAH patients.
A decrease in cerebral blood flow can lead to ischemia and subsequently a metabolic crisis. Rostami et al. [67] also showed in aSAH patients that high lactate to pyruvate ratios were associated with decreased cerebral blood flow around the microdialysis catheter as seen on Xenon enhanced computed tomography.
An argument against the utility of microdialysis stems from the dialysate being taken from a single area of the brain. The brain microenvironment in one region may not be reflective of the global cerebral environment. This can be especially true in aSAH patients where vasospasm may be limited to individual vascular territories distant from the microdialysis monitor (See Figure 1). However, this assertion against microdialysis has been challenged in pathologies that involve diffuse injury such as in TBI. Bouzat et al. [68] used examined computed tomography perfusion studies of 27 severe traumatic brain injury patients with microdialysis monitoring. Regional blood flow around the catheter correlated with global cerebral blood flow [68]. In addition, low dialysate glucose and elevated lactate to pyruvate ratio >40 significantly predicted low regional cerebral blood flow (<35 mL/100 g brain tissue/min) on CT perfusion [68]. Moreover, the addition of cerebral microdialysis and PbtO2 monitoring to standard ICP monitoring was significantly more accurate in predicting low regional cerebral blood flow than ICP monitoring alone [68].
Using cerebral microenvironment metabolic profiles, the data has shown to be useful in predicting neurologic prognosis. In severe TBI patients, Timofeev et al. [69] showed that microdialysis markers were independently associated with outcome. In his prospective cohort of 223 patients, elevated levels of glutamate (>10 µmol/L) and high lactate to pyruvate ratios (>25) were associated with higher mortality. Conversely, favorable outcomes were more likely in patients with lower lactate/pyruvate ratios and total lactate levels [69]. Pyruvate was an independent negative predictor of mortality [69].
In addition to low glucose availability that can precipitate a metabolic crisis, fluctuations in glucose appear to be detrimental. Kurtz et al. [70] showed that patients with poor grade aSAH and high systemic glucose variability were more likely to show signs of metabolic distress defined as lactate to pyruvate ratio >40 on cerebral microdialysis analysis and had higher in-hospital mortality. Similarly, Gupta et al. [71] demonstrated in severe TBI patients that required a decompressive craniectomy, patients with more episodes of systemic hypoglycemia and hyperglycemia during the acute phase had a poor Glasgow Outcome Scale score at 3 months. The poor outcome group also had more episodes of cerebral hypoglycemia, although a temporal correlation of blood and cerebral glucose levels was not seen [71]. Rostami and Bellander showed with cerebral microdialysis that blood glucose levels and cerebral glucose levels may correlate in non-injured brain but not in injured brain [72]. To our knowledge, the role of cerebral glycemic variability using cerebral microdialysis in post cardiac arrest comatose patients is not known. Cerebral glucose metabolism as assessed by positron emission tomography (PET), though usually with limited image resolution and only when the patient’s condition is stable and allows for the exam, has shown decreased radiolabeled glucose uptake in patients in persistent vegetative state after cardiac arrest, although the utility in predicting prognosis is indeterminate [73,74]. However, in general, systemic glycemic variability is known to be a predictor of mortality in patients in the intensive care unit [75]. In addition, decreased brain to serum glucose ratios correlate with in-hospital mortality and poorer outcomes across multiple pathologies including aSAH, cardiac arrest, intracerebral hemorrhage, and TBI [76].
Additional markers have been investigated using microdialysis. Brain extracellular potassium concentration ([K+]) is a marker for metabolic distress on microdialysis and poor 3-month outcome in poor grade aSAH patients [77]. The brain extracellular [K+] does not necessarily correlate with serum [K+] signifying such useful information is only available through the use of microdialysis [77].
Newer techniques have allowed for the continuous real-time assessment of highly reactive oxygen species known to lead to cellular injury and necrosis in pre-clinical models [78]. Elevated cerebral dialysate levels of interleukin-6 on admission were associated with delayed cerebral ischemia in poor grade aneurysmal subarachnoid hemorrhage patients [79]. Levels of matrix-metalloproteinase-9 were significantly elevated in patients presenting with poor grade aSAH [79]. These markers of a pro-inflammatory state are uniquely available to microdialysis techniques and independent of traditional systemic markers of inflammation including white blood cell count, C-reactive protein, and body temperature [79]. Further work will allow for the quantification and eventual therapy for injurious oxidative stress.
Logistically, the use of microdialysis can be labor intensive. In our neurocritical care unit, the dialysate is analyzed hourly and requires a critical care nurse dedicated only to the single patient with a microdialysis catheter. In addition, the invasive nature introduces inherent risks including hemorrhage, infection, and hardware malfunction. Nevertheless, microdialysis offers a window into the individual’s pathophysiology underlying their cerebral injury and insults leading to secondary injury. The full transformative effect of microdialysis in the neurocritical care has yet to be seen.

7. Pressure Reactivity Index

Pressure reactivity index (PRx) is a measure of the correlation of blood pressure and intracranial pressure. In the normal range of intact autoregulation, blood pressure and ICP are negatively correlated. That is, an increase in cerebral blood flow is followed by cerebral vasoconstriction that decreases the volume of the intracranial blood compartment, thereby decreasing the ICP.
PRx requires an ICP monitor to correlate the ICP with the blood pressure. For severe TBI patients (GCS ≤ 8) with an abnormal CT scan, ICP monitoring is recommended by the Brain Trauma Foundation guidelines [56]. As such, for the severe TBI population, PRx provides critical autoregulation information without the need for additional invasive devices.
With PRx, clinicians can identify the individualized blood pressure range in which autoregulation is intact whereby cerebral perfusion pressure (CPP) is preserved. The individual patient’s optimal CPP (CPPopt) is the CPP at which the PRx is most negative, that is, when autoregulation is most appropriately responsive. Aries et al. [80] showed in a large retrospective cohort of severe TBI patients requiring neurocritical care that six-month Glasgow Outcome Scores were better in patients whose CPP was maintained within 5 mmHg of their CPPopt. Mortality was greatly increased in patients whose CPP was more than 5 mmHg below their CPPopt [80]. In a follow-up single center prospective pilot study, Dias et al. [81] demonstrated the feasibility of CPPopt guided care, and reconfirmed that patients with a median CPP 6.6 mmHg below CPPopt had poorer Glasgow Outcome Scores at 6 months. PRx has been investigated in the aSAH population. Despite case reports of PRx being useful for predicting delayed cerebral ischemia, its utility is not firmly established [82]. PRx may be able to identify patients with decreased cerebral blood flow, but it has not been shown to reliably predict delayed cerebral ischemia [83]. The Neurocritical Care Society guidelines acknowledge the multiple methods for monitoring cerebral autoregulation, but currently give a “weak recommendation” to their use [84]. Since no technique is clearly better than others, PRx is advantageous in patients already with ICP monitoring since no additional invasive procedure or blood draw is needed. To our knowledge, PRx has not been evaluated in the adult post-cardiac arrest patient. Limitations of PRx include the need for additional software that can compute CPPopt. In addition, the software may not be able to determine CPPopt for all patients [81].

8. PbtO2 Monitoring

PbtO2 monitoring is an invasive form of monitoring the brain tissue oxygenation via a catheter inserted into brain parenchyma. As for any form of invasive monitor, risks of hemorrhage, infection, and device malfunction are possible.
The level of brain tissue oxygenation is a crucial measure in the intensive care unit. A PbtO2 < 15 mmHg is associated with cerebral ischemia and poor neurological outcome. Normal PbtO2 is above 20 mmHg. ICU maneuvers to increase PbtO2 include pressors or volume expanders to increase mean arterial pressure (thereby, cerebral perfusion pressure), ICP reduction, blood transfusion to increase oxygen carrying capacity, and by increasing the fraction of inspired oxygen. Increasing the oxygen carrying capacity by blood transfusion increases the PbtO2 in as little as 2 h [85]. In poor grade aSAH patients that underwent intra-arterial spasmolysis, a rise in PbtO2 after treatment correlated with the angiographic response of improved blood flow [86]. The availability of measures to affect brain tissue oxygenation reinforces the clinical utility of real-time PbtO2 monitoring.
Spiotta et al. [87] noted that in a cohort of 70 patients with severe TBI that had goal directed PbtO2 therapy (PbtO2 > 20 mmHg) in addition to standard ICP/CPP management had significantly lower 3-month mortality—25.7% compared to 45.3% in standard ICP/CPP therapy group. At 3 months, the PbtO2 goal directed therapy group had significantly more favorable outcome rates (64.3% compared to 39.6%) [87]. Other groups have similarly showed a decrease in mortality and improved 6-month GOS outcomes with the addition of goal directed PbtO2 therapy over standard ICP/CPP therapy alone [88,89]. In aSAH, PbtO2 monitoring has less of a role in predicting vasospasm or outcome [90]. The utility of PbtO2 in comatose state after cardiac arrest is not known and currently not recommended [61].
Limitations of PbtO2 monitoring are inherent to the regional monitoring. The utility will depend on the pathology. Severe TBI as a global process lends itself as a clinical entity where PbtO2 monitoring would be of value.

9. Timing of Brain Monitoring

With the multitude of methods available for brain monitoring, timing of each has to be considered. In our view, the timing depends on the primary diagnosis. For the post-cardiac arrest comatose state, the serum markers of neuronal injury NSE and S100B within 48–72 h are useful for prognostication [18,19,25]. As the neurologic injury is predominantly subsequent to post cardiac arrest hypoxic state, invasive methods to detect secondary injury are less warranted. Electrophysiological testing and magnetic resonance imaging are additional methods for assessing prognosis 72 h after cardiac arrest [1].
In poor grade aSAH patients, the utility of serum markers of neuronal injury is best within the 24–72 h for predicting unfavorable outcomes [20,28,34]. S100B peaks early within 24 h and then decreases [27]. GFAP was shown to peak around day 2 [35]. For aSAH patients, preventing and treating delayed ischemic neurologic deficits from cerebral vasospasm is a primary objective in the intensive care setting. Delayed ischemia is very difficult to detect on the neurologic examination in the poor grade aSAH patient. Given the peak vasospasm window occurs between days 4 to 11 after aneurysm rupture [91], the use of microdialysis to detect regional ischemia may be targeted to this time period. Additional methods specifically for detecting vasospasm must be employed given not all cerebral vascular territories are affected equally.
In severe traumatic brain injury, S100B levels within 24 h of injury and an elevated GFAP level at day 7 are useful for outcome prediction [27,29,37]. ICP monitoring should be followed on admission as recommended by the Brain Trauma Foundation [56]. Beyond prognostic purposes, the use of other modalities such as microdialysis, PbtO2, and pressure reactivity index may improve outcomes (See Table 2) and can be considered where available.

10. Optogenetics—Possible Future Monitoring Tool?

Optogenetics is an interesting area of research relatively in its infancy but may have potential clinical applications in brain monitoring. In its simplest permutation, optogenetics involves optically recording changes in membrane potential. Regarding the central nervous system, changes in membrane potential is how action potentials spread down an axon, across a synapse, and activate second order neurons. The ability to see neuronal signal transmission in action implicates that functional circuitry can be characterized. The functional assessment possible through optogenetics is an advantage over current brain monitoring techniques.
The vehicle for gaining such information lies in the utilization of genetically encoded voltage indicators that fluoresce with changes in membrane potential. Since their introduction, voltage indicators have become much more sophisticated with voltage range specificities that allow for differentiating between axon depolarization, sub-threshold membrane potential changes, and synaptic activity as recently reviewed [92]. Optical recording of neural activity has been performed in in vitro cell models, whole brain explant models, and in vivo pre-clinical models [93,94]. Optogenetics can be combined with other therapies to monitor for improvement in neuronal functioning. Jayaprakash et al. [95] demonstrated the ability to optically monitor for synapse formation in an experimentally treated preclinical model of spinal cord injury. A current limitation of optogenetics is that the brain tissue of interest has to be genetically targeted for optogenetic monitoring. For the adult human brain, optogenetic monitoring is likely to be limited to specific regions or functional pathways rather than the entire brain.
Though seemingly a leap at this time, optogenetics may allow for in-depth real time brain monitoring of functional circuitry. Considerable work remains in the areas of voltage indicator optimization, integration and targeted gene expression, optical recording, and scaling to the human brain. Since optogenetic monitoring will be limited to the area of interest, it will complement current methods of brain monitoring to provide a better overall neurologic injury picture for monitoring, treatment, and prognosis.

11. Use of Multimodality Monitoring

There are multiple modalities of brain monitoring complement each other to provide a better picture of neurologic injury. With a better understanding of a patient’s individual cerebral pathophysiology, multimodality approach can lead to goal directed therapy to optimize the individual patient’s physiology. The use of goal-directed therapy guided by brain monitoring tools requires further clinical evaluation to identify improvements in outcomes. For severe TBI, several modalities have been combined with standard ICP monitoring with improvements in outcomes (See Table 2). Larger clinical series are needed to lead to widespread adoption of multimodality monitoring.

12. Conclusions

Tools for brain monitoring are becoming more sophisticated and continually improving to allow for real-time individualized brain monitoring. The role of microdialysis will only increase as markers of initial and ongoing neuronal injury are researched and applied to the clinical arena. It is conceivable that different pathologies may require different microdialysis markers on injury, thus further individualizing patient care. The availability and further development of multimodality monitors allow for concurrent brain tissue oxygenation, intracranial pressure monitoring, and cerebral microdialysis. The role of optogenetics in evaluating brain injury and recovery towards possible brain monitoring is seemingly far away, but may fundamentally change how we monitor the brain after injury. The importance of neurocritical care management is seen with improved functional outcomes for patients undergoing advanced brain monitoring.

Acknowledgments

The work was supported by R01HL118084 from National Institutes of Health (to Xiaofeng Jia).

Author Contributions

Salazar Jones searched and reviewed literature, drafted manuscript and revision; Gary Schwartzbauer provided critical comments and discussed the manuscript; Xiaofeng Jia designed and formulated the review theme, viewed the literature, revised and finalized the manuscript.

Conflicts of Interest

The authors declare no conflict of interest. The founding sponsors had no role in the in the writing of this review.

References

  1. Karapetkova, M.; Koenig, M.A.; Jia, X. Early prognostication markers in cardiac arrest patients treated with hypothermia. Eur. J. Neurol. 2016, 23, 476–488. [Google Scholar] [CrossRef] [PubMed]
  2. Deng, R.; Young, L.M.; Jia, X. Quantitative EEG markers in severe post-resuscitation brain injury with therapeutic hypothermia. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2015, 2015, 6598–6601. [Google Scholar] [PubMed]
  3. Corrigan, J.D.; Selassie, A.W.; Orman, J.A. The epidemiology of traumatic brain injury. J. Head Trauma Rehabil. 2010, 25, 72–80. [Google Scholar] [CrossRef] [PubMed]
  4. Hofmeijer, J.; Beernink, T.M.; Bosch, F.H.; Beishuizen, A.; Tjepkema-Cloostermans, M.C.; van Putten, M.J. Early EEG contributes to multimodal outcome prediction of postanoxic coma. Neurology 2015, 85, 137–143. [Google Scholar] [CrossRef] [PubMed]
  5. Zacharia, B.E.; Hickman, Z.L.; Grobelny, B.T.; DeRosa, P.; Kotchetkov, I.; Ducruet, A.F.; Connolly, E.S., Jr. Epidemiology of aneurysmal subarachnoid hemorrhage. Neurosurg. Clin. N. Am. 2010, 21, 221–233. [Google Scholar] [CrossRef] [PubMed]
  6. Jia, X.; Koenig, M.A.; Shin, H.C.; Zhen, G.; Pardo, C.A.; Hanley, D.F.; Thakor, N.V.; Geocadin, R.G. Improving neurological outcomes post-cardiac arrest in a rat model: Immediate hypothermia and quantitative EEG monitoring. Resuscitation 2008, 76, 431–442. [Google Scholar] [CrossRef] [PubMed]
  7. Jia, X.; Koenig, M.A.; Nickl, R.; Zhen, G.; Thakor, N.V.; Geocadin, R.G. Early electrophysiologic markers predict functional outcome associated with temperature manipulation after cardiac arrest in rats. Crit. Care Med. 2008, 36, 1909–1916. [Google Scholar] [CrossRef] [PubMed]
  8. Shin, H.C.; Tong, S.; Yamashita, S.; Jia, X.; Geocadin, R.G.; Thakor, N.V. Quantitative EEG and effect of hypothermia on brain recovery after cardiac arrest. IEEE Trans. Biomed. Eng. 2006, 53, 1016–1023. [Google Scholar] [CrossRef] [PubMed]
  9. Jia, X.; Koenig, M.A.; Shin, H.C.; Zhen, G.; Yamashita, S.; Thakor, N.V.; Geocadin, R.G. Quantitative EEG and neurological recovery with therapeutic hypothermia after asphyxial cardiac arrest in rats. Brain Res. 2006, 1111, 166–175. [Google Scholar] [CrossRef] [PubMed]
  10. Deng, R.; Koenig, M.A.; Young, L.M.; Jia, X. Early quantitative gamma-band EEG marker is associated with outcomes after cardiac arrest and targeted temperature management. Neurocrit. Care 2015, 23, 262–273. [Google Scholar] [CrossRef] [PubMed]
  11. Xiong, W.; Koenig, M.A.; Madhok, J.; Jia, X.; Puttgen, H.A.; Thakor, N.V.; Geocadin, R.G. Evolution of somatosensory evoked potentials after cardiac arrest induced hypoxic-ischemic injury. Resuscitation 2010, 81, 893–897. [Google Scholar] [CrossRef] [PubMed]
  12. Madhok, J.; Maybhate, A.; Xiong, W.; Koenig, M.A.; Geocadin, R.G.; Jia, X.; Thakor, N.V. Quantitative assessment of somatosensory-evoked potentials after cardiac arrest in rats: Prognostication of functional outcomes. Crit. Care Med. 2010, 38, 1709–1717. [Google Scholar] [CrossRef] [PubMed]
  13. Neumar, R.W.; Nolan, J.P.; Adrie, C.; Aibiki, M.; Berg, R.A.; Bottiger, B.W.; Callaway, C.; Clark, R.S.; Geocadin, R.G.; Jauch, E.C.; et al. Post-cardiac arrest syndrome: Epidemiology, pathophysiology, treatment, and prognostication. A consensus statement from the international liaison committee on resuscitation (american heart association, australian and new zealand council on resuscitation, european resuscitation council, heart and stroke foundation of canada, interamerican heart foundation, resuscitation council of asia, and the resuscitation council of southern Africa); the american heart association emergency cardiovascular care committee; the council on cardiovascular surgery and anesthesia; the council on cardiopulmonary, perioperative, and critical care; the council on clinical cardiology; and the stroke council. Circulation 2008, 118, 2452–2483. [Google Scholar] [PubMed]
  14. Stienen, M.N.; Smoll, N.R.; Weisshaupt, R.; Fandino, J.; Hildebrandt, G.; Studerus-Germann, A.; Schatlo, B. Delayed cerebral ischemia predicts neurocognitive impairment following aneurysmal subarachnoid hemorrhage. World Neurosurg. 2014, 82, e599–e605. [Google Scholar] [CrossRef] [PubMed]
  15. Murthy, T.; Bhatia, P.; Sandhu, K.; Prabhakar, T.; Gogna, R. Secondary brain injury: Prevention and intensive care management. Indian J. Neurotrauma 2005, 2, 7–12. [Google Scholar] [CrossRef]
  16. Hofmeijer, J.; van Putten, M.J. EEG in postanoxic coma: Prognostic and diagnostic value. Clin. Neurophysiol. 2016, 127, 2047–2055. [Google Scholar] [CrossRef] [PubMed]
  17. Haque, A.; Ray, S.K.; Cox, A.; Banik, N.L. Neuron specific enolase: A promising therapeutic target in acute spinal cord injury. Metab. Brain Dis. 2016, 31, 487–495. [Google Scholar] [CrossRef] [PubMed]
  18. Rech, T.H.; Vieira, S.R.; Nagel, F.; Brauner, J.S.; Scalco, R. Serum neuron-specific enolase as early predictor of outcome after in-hospital cardiac arrest: A cohort study. Crit. Care 2006, 10, R133. [Google Scholar] [CrossRef] [PubMed]
  19. Stammet, P.; Collignon, O.; Hassager, C.; Wise, M.P.; Hovdenes, J.; Aneman, A.; Horn, J.; Devaux, Y.; Erlinge, D.; Kjaergaard, J.; et al. Neuron-specific enolase as a predictor of death or poor neurological outcome after out-of-hospital cardiac arrest and targeted temperature management at 33 degrees C and 36 degrees C. J. Am. Coll. Cardiol. 2015, 65, 2104–2114. [Google Scholar] [CrossRef] [PubMed]
  20. Tawk, R.G.; Grewal, S.S.; Heckman, M.G.; Rawal, B.; Miller, D.A.; Edmonston, D.; Ferguson, J.L.; Navarro, R.; Ng, L.; Brown, B.L.; et al. The relationship between serum neuron-specific enolase levels and severity of bleeding and functional outcomes in patients with nontraumatic subarachnoid hemorrhage. Neurosurgery 2016, 78, 487–491. [Google Scholar] [CrossRef] [PubMed]
  21. Cheng, F.; Yuan, Q.; Yang, J.; Wang, W.; Liu, H. The prognostic value of serum neuron-specific enolase in traumatic brain injury: Systematic review and meta-analysis. PLoS ONE 2014, 9, e106680. [Google Scholar] [CrossRef] [PubMed]
  22. Pfeifer, R.; Ferrari, M.; Borner, A.; Deufel, T.; Figulla, H.R. Serum concentration of nse and S-100B during LVAD in non-resuscitated patients. Resuscitation 2008, 79, 46–53. [Google Scholar] [CrossRef] [PubMed]
  23. Wolf, H.; Krall, C.; Pajenda, G.; Hajdu, S.; Widhalm, H.; Leitgeb, J.; Sarahrudi, K. Preliminary findings on biomarker levels from extracerebral sources in patients undergoing trauma surgery: Potential implications for TBI outcome studies. Brain Inj. 2016, 30, 1220–1225. [Google Scholar] [CrossRef] [PubMed]
  24. Donato, R.; Cannon, B.R.; Sorci, G.; Riuzzi, F.; Hsu, K.; Weber, D.J.; Geczy, C.L. Functions of S100 proteins. Curr. Mol. Med. 2013, 13, 24–57. [Google Scholar] [CrossRef] [PubMed]
  25. Calderon, L.M.; Guyette, F.X.; Doshi, A.A.; Callaway, C.W.; Rittenberger, J.C. Combining NSE and S100B with clinical examination findings to predict survival after resuscitation from cardiac arrest. Resuscitation 2014, 85, 1025–1029. [Google Scholar] [CrossRef] [PubMed]
  26. Stammet, P.; Wagner, D.R.; Gilson, G.; Devaux, Y. Modeling serum level of S100β and bispectral index to predict outcome after cardiac arrest. J. Am. Coll. Cardiol. 2013, 62, 851–858. [Google Scholar] [CrossRef] [PubMed]
  27. Kellermann, I.; Kleindienst, A.; Hore, N.; Buchfelder, M.; Brandner, S. Early CSF and serum S100B concentrations for outcome prediction in traumatic brain injury and subarachnoid hemorrhage. Clin. Neurol. Neurosurg. 2016, 145, 79–83. [Google Scholar] [CrossRef] [PubMed]
  28. Lai, P.M.; Du, R. Association between S100B levels and long-term outcome after aneurysmal subarachnoid hemorrhage: Systematic review and pooled analysis. PLoS ONE 2016, 11, e0151853. [Google Scholar] [CrossRef] [PubMed]
  29. Thelin, E.P.; Jeppsson, E.; Frostell, A.; Svensson, M.; Mondello, S.; Bellander, B.M.; Nelson, D.W. Utility of neuron-specific enolase in traumatic brain injury; relations to S100B levels, outcome, and extracranial injury severity. Crit. Care 2016, 20, 285. [Google Scholar] [CrossRef] [PubMed]
  30. Savola, O.; Pyhtinen, J.; Leino, T.K.; Siitonen, S.; Niemela, O.; Hillbom, M. Effects of head and extracranial injuries on serum protein S100B levels in trauma patients. J. Trauma 2004, 56, 1229–1234. [Google Scholar] [CrossRef] [PubMed]
  31. Brandner, S.; Thaler, C.; Buchfelder, M.; Kleindienst, A. Brain-derived protein concentrations in the cerebrospinal fluid: Contribution of trauma resulting from ventricular drain insertion. J. Neurotrauma 2013, 30, 1205–1210. [Google Scholar] [CrossRef] [PubMed]
  32. Kaneko, T.; Kasaoka, S.; Miyauchi, T.; Fujita, M.; Oda, Y.; Tsuruta, R.; Maekawa, T. Serum glial fibrillary acidic protein as a predictive biomarker of neurological outcome after cardiac arrest. Resuscitation 2009, 80, 790–794. [Google Scholar] [CrossRef] [PubMed]
  33. Larsson, I.M.; Wallin, E.; Kristofferzon, M.L.; Niessner, M.; Zetterberg, H.; Rubertsson, S. Post-cardiac arrest serum levels of glial fibrillary acidic protein for predicting neurological outcome. Resuscitation 2014, 85, 1654–1661. [Google Scholar] [CrossRef] [PubMed]
  34. Vos, P.E.; van Gils, M.; Beems, T.; Zimmerman, C.; Verbeek, M.M. Increased GFAP and s100β but not NSE serum levels after subarachnoid haemorrhage are associated with clinical severity. Eur. J. Neurol. 2006, 13, 632–638. [Google Scholar] [CrossRef] [PubMed]
  35. Nylen, K.; Csajbok, L.Z.; Ost, M.; Rashid, A.; Blennow, K.; Nellgard, B.; Rosengren, L. Serum glial fibrillary acidic protein is related to focal brain injury and outcome after aneurysmal subarachnoid hemorrhage. Stroke 2007, 38, 1489–1494. [Google Scholar] [CrossRef] [PubMed]
  36. Wiesmann, M.; Steinmeier, E.; Magerkurth, O.; Linn, J.; Gottmann, D.; Missler, U. Outcome prediction in traumatic brain injury: Comparison of neurological status, CT findings, and blood levels of S100B and GFAP. Acta Neurol. Scand. 2010, 121, 178–185. [Google Scholar] [CrossRef] [PubMed]
  37. Raheja, A.; Sinha, S.; Samson, N.; Bhoi, S.; Subramanian, A.; Sharma, P.; Sharma, B.S. Serum biomarkers as predictors of long-term outcome in severe traumatic brain injury: Analysis from a randomized placebo-controlled phase II clinical trial. J. Neurosurg. 2016, 125, 631–641. [Google Scholar] [CrossRef] [PubMed]
  38. Papa, L.; Silvestri, S.; Brophy, G.M.; Giordano, P.; Falk, J.L.; Braga, C.F.; Tan, C.N.; Ameli, N.J.; Demery, J.A.; Dixit, N.K.; et al. GFAP out-performs s100β in detecting traumatic intracranial lesions on computed tomography in trauma patients with mild traumatic brain injury and those with extracranial lesions. J. Neurotrauma 2014, 31, 1815–1822. [Google Scholar] [CrossRef] [PubMed]
  39. Papa, L.; Brophy, G.M.; Welch, R.D.; Lewis, L.M.; Braga, C.F.; Tan, C.N.; Ameli, N.J.; Lopez, M.A.; Haeussler, C.A.; Mendez Giordano, D.I.; et al. Time course and diagnostic accuracy of glial and neuronal blood biomarkers GFAP and UCH-L1 in a large cohort of trauma patients with and without mild traumatic brain injury. JAMA Neurol. 2016, 73, 551–560. [Google Scholar] [PubMed]
  40. Hart, J.; Novak, V.; Saunders, C.; Gremaud, P.A. Transcranial doppler-based surrogates for cerebral blood flow: A statistical study. PLoS ONE 2016, 11, e0165536. [Google Scholar] [CrossRef] [PubMed]
  41. Fantini, S.; Sassaroli, A.; Tgavalekos, K.T.; Kornbluth, J. Cerebral blood flow and autoregulation: Current measurement techniques and prospects for noninvasive optical methods. Neurophotonics 2016, 3, 031411. [Google Scholar] [CrossRef] [PubMed]
  42. Tisdall, M.M.; Tachtsidis, I.; Leung, T.S.; Elwell, C.E.; Smith, M. Increase in cerebral aerobic metabolism by normobaric hyperoxia after traumatic brain injury. J. Neurosurg. 2008, 109, 424–432. [Google Scholar] [CrossRef] [PubMed]
  43. Leal-Noval, S.R.; Cayuela, A.; Arellano-Orden, V.; Marin-Caballos, A.; Padilla, V.; Ferrandiz-Millon, C.; Corcia, Y.; Garcia-Alfaro, C.; Amaya-Villar, R.; Murillo-Cabezas, F. Invasive and noninvasive assessment of cerebral oxygenation in patients with severe traumatic brain injury. Intensive Care Med. 2010, 36, 1309–1317. [Google Scholar] [CrossRef] [PubMed]
  44. Mutoh, T.; Ishikawa, T.; Suzuki, A.; Yasui, N. Continuous cardiac output and near-infrared spectroscopy monitoring to assist in management of symptomatic cerebral vasospasm after subarachnoid hemorrhage. Neurocrit. Care 2010, 13, 331–338. [Google Scholar] [CrossRef] [PubMed]
  45. Verdecchia, K.; Diop, M.; Lee, A.; Morrison, L.B.; Lee, T.Y.; St Lawrence, K. Assessment of a multi-layered diffuse correlation spectroscopy method for monitoring cerebral blood flow in adults. Biomed. Opt. Express 2016, 7, 3659–3674. [Google Scholar] [CrossRef] [PubMed]
  46. Kim, M.N.; Durduran, T.; Frangos, S.; Edlow, B.L.; Buckley, E.M.; Moss, H.E.; Zhou, C.; Yu, G.; Choe, R.; Maloney-Wilensky, E.; et al. Noninvasive measurement of cerebral blood flow and blood oxygenation using near-infrared and diffuse correlation spectroscopies in critically brain-injured adults. Neurocrit. Care 2010, 12, 173–180. [Google Scholar] [CrossRef] [PubMed]
  47. Dunn, A.K. Laser speckle contrast imaging of cerebral blood flow. Ann. Biomed. Eng. 2012, 40, 367–377. [Google Scholar] [CrossRef] [PubMed]
  48. Murari, K.; Li, N.; Rege, A.; Jia, X.; All, A.; Thakor, N. Contrast-enhanced imaging of cerebral vasculature with laser speckle. Appl. Opt. 2007, 46, 5340–5346. [Google Scholar] [CrossRef] [PubMed]
  49. Li, N.; Thakor, N.V.; Jia, X. Laser speckle imaging reveals multiple aspects of cerebral vascular responses to whole body mild hypothermia in rats. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2011, 2011, 2049–2052. [Google Scholar] [PubMed]
  50. Junyun, H.; Hongyang, L.; Ruoxian, D.; Young, L.; Shanbao, T.; Xiaofeng, J. Real-time monitoring of cerebral blood flow by laser speckle contrast imaging after cardiac arrest in rat. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2015, 2015, 6971–6974. [Google Scholar]
  51. Li, N.; Jia, X.; Murari, K.; Parlapalli, R.; Rege, A.; Thakor, N.V. High spatiotemporal resolution imaging of the neurovascular response to electrical stimulation of rat peripheral trigeminal nerve as revealed by in vivo temporal laser speckle contrast. J. Neurosci. Methods 2009, 176, 230–236. [Google Scholar] [CrossRef] [PubMed]
  52. Jia, X. Translational medicine: Creating the crucial bidirectional bridge between bench and bedside. Int. J. Mol. Sci. 2016, 17, 1918. [Google Scholar] [CrossRef] [PubMed]
  53. Parthasarathy, A.B.; Weber, E.L.; Richards, L.M.; Fox, D.J.; Dunn, A.K. Laser speckle contrast imaging of cerebral blood flow in humans during neurosurgery: A pilot clinical study. J. Biomed. Opt. 2010, 15, 066030. [Google Scholar] [CrossRef] [PubMed]
  54. Hecht, N.; Woitzik, J.; Konig, S.; Horn, P.; Vajkoczy, P. Laser speckle imaging allows real-time intraoperative blood flow assessment during neurosurgical procedures. J. Cereb. Blood Flow Metab. 2013, 33, 1000–1007. [Google Scholar] [CrossRef] [PubMed]
  55. Hutchinson, P.J.; Kolias, A.G.; Timofeev, I.S.; Corteen, E.A.; Czosnyka, M.; Timothy, J.; Anderson, I.; Bulters, D.O.; Belli, A.; Eynon, C.A.; et al. Trial of decompressive craniectomy for traumatic intracranial hypertension. N. Engl. J. Med. 2016, 375, 1119–1130. [Google Scholar] [CrossRef] [PubMed]
  56. Carney, N.; Totten, A.M.; O’Reilly, C.; Ullman, J.S.; Hawryluk, G.W.; Bell, M.J.; Bratton, S.L.; Chesnut, R.; Harris, O.A.; Kissoon, N.; et al. Guidelines for the management of severe traumatic brain injury, fourth edition. Neurosurgery 2016, in press. [Google Scholar] [CrossRef] [PubMed]
  57. Yuan, Q.; Wu, X.; Sun, Y.; Yu, J.; Li, Z.; Du, Z.; Mao, Y.; Zhou, L.; Hu, J. Impact of intracranial pressure monitoring on mortality in patients with traumatic brain injury: A systematic review and meta-analysis. J. Neurosurg. 2015, 122, 574–587. [Google Scholar] [CrossRef] [PubMed]
  58. Chesnut, R.M.; Temkin, N.; Carney, N.; Dikmen, S.; Rondina, C.; Videtta, W.; Petroni, G.; Lujan, S.; Pridgeon, J.; Barber, J.; et al. A trial of intracranial-pressure monitoring in traumatic brain injury. N. Engl. J. Med. 2012, 367, 2471–2481. [Google Scholar] [CrossRef] [PubMed]
  59. Talving, P.; Karamanos, E.; Teixeira, P.G.; Skiada, D.; Lam, L.; Belzberg, H.; Inaba, K.; Demetriades, D. Intracranial pressure monitoring in severe head injury: Compliance with brain trauma foundation guidelines and effect on outcomes: A prospective study. J. Neurosurg. 2013, 119, 1248–1254. [Google Scholar] [CrossRef] [PubMed]
  60. Cossu, G.; Messerer, M.; Stocchetti, N.; Levivier, M.; Daniel, R.T.; Oddo, M. Intracranial pressure and outcome in critically ill patients with aneurysmal subarachnoid hemorrhage: A systematic review. Minerva Anestesiol. 2016, in press. [Google Scholar]
  61. Wijdicks, E.F.; Hijdra, A.; Young, G.B.; Bassetti, C.L.; Wiebe, S. Practice parameter: Prediction of outcome in comatose survivors after cardiopulmonary resuscitation (an evidence-based review): Report of the quality standards subcommittee of the american academy of neurology. Neurology 2006, 67, 203–210. [Google Scholar] [CrossRef] [PubMed]
  62. Nordmark, J.; Rubertsson, S.; Mortberg, E.; Nilsson, P.; Enblad, P. Intracerebral monitoring in comatose patients treated with hypothermia after a cardiac arrest. Acta Anaesthesiol. Scand. 2009, 53, 289–298. [Google Scholar] [CrossRef] [PubMed]
  63. Tseng, E.E.; Brock, M.V.; Lange, M.S.; Troncoso, J.C.; Blue, M.E.; Lowenstein, C.J.; Johnston, M.V.; Baumgartner, W.A. Glutamate excitotoxicity mediates neuronal apoptosis after hypothermic circulatory arrest. Ann. Thorac. Surg. 2010, 89, 440–445. [Google Scholar] [CrossRef] [PubMed]
  64. Dreier, J.; Major, S.; Manning, A.; Woitzik, J.; Drenckhahn, C.; Steinbrink, J.; Tolias, C.; Oliveira-Ferreira, A.; Fabricius, M.; Hartings, J.; et al. Cortical spreading ischaemia is a novel process involved in ischaemic damage in patients with aneurysmal subarachnoid hemorrhage. Brain 2009, 132, 1866–1881. [Google Scholar] [CrossRef] [PubMed]
  65. Hinzman, J.M.; Wilson, J.A.; Mazzeo, A.T.; Bullock, M.R.; Hartings, J.A. Excitotoxicity and metabolic crisis are associated with spreading depolarizations in severe traumatic brain injury patients. J. Neurotrauma 2016, 33, 1775–1783. [Google Scholar] [CrossRef] [PubMed]
  66. Oddo, M.; Levine, J.M.; Frangos, S.; Maloney-Wilensky, E.; Carrera, E.; Daniel, R.T.; Levivier, M.; Magistretti, P.J.; LeRoux, P.D. Brain lactate metabolism in humans with subarachnoid hemorrhage. Stroke 2012, 43, 1418–1421. [Google Scholar] [CrossRef] [PubMed]
  67. Rostami, E.; Engquist, H.; Johnson, U.; Howells, T.; Ronne-Engstrom, E.; Nilsson, P.; Hillered, L.; Lewen, A.; Enblad, P. Monitoring of cerebral blood flow and metabolism bedside in patients with subarachnoid hemorrhage—A xenon-CT and microdialysis study. Front. Neurol. 2014, 5, 89. [Google Scholar] [CrossRef] [PubMed]
  68. Bouzat, P.; Marques-Vidal, P.; Zerlauth, J.B.; Sala, N.; Suys, T.; Schoettker, P.; Bloch, J.; Daniel, R.T.; Levivier, M.; Meuli, R.; et al. Accuracy of brain multimodal monitoring to detect cerebral hypoperfusion after traumatic brain injury. Crit. Care Med. 2015, 43, 445–452. [Google Scholar] [CrossRef] [PubMed]
  69. Timofeev, I.; Carpenter, K.L.; Nortje, J.; Al-Rawi, P.G.; O’Connell, M.T.; Czosnyka, M.; Smielewski, P.; Pickard, J.D.; Menon, D.K.; Kirkpatrick, P.J.; et al. Cerebral extracellular chemistry and outcome following traumatic brain injury: A microdialysis study of 223 patients. Brain 2011, 134, 484–494. [Google Scholar] [CrossRef] [PubMed]
  70. Kurtz, P.; Claassen, J.; Helbok, R.; Schmidt, J.; Fernandez, L.; Presciutti, M.; Stuart, R.M.; Connolly, E.S.; Lee, K.; Badjatia, N.; et al. Systemic glucose variability predicts cerebral metabolic distress and mortality after subarachnoid hemorrhage: A retrospective observational study. Crit. Care 2014, 18, R89. [Google Scholar] [CrossRef] [PubMed]
  71. Gupta, D.K.; Singla, R.; Kale, S.S.; Sharma, B.S. Intracerebral hypoglycemia and its clinical relevance as a prognostic indicator in severe traumatic brain injury: A cerebral microdialysis study from india. Neurol. India 2016, 64, 259–264. [Google Scholar] [CrossRef] [PubMed]
  72. Rostami, E.; Bellander, B.M. Monitoring of glucose in brain, adipose tissue, and peripheral blood in patients with traumatic brain injury: A microdialysis study. J. Diabetes Sci. Technol. 2011, 5, 596–604. [Google Scholar] [CrossRef] [PubMed]
  73. Laureys, S.; Antoine, S.; Boly, M.; Elincx, S.; Faymonville, M.; Berré, J.; Sadzot, B.; Ferring, M.; de Tiège, X.; van Bogaert, P.; et al. Brain function in the vegetative state. Acta Neurol. Belg. 2002, 102, 177–185. [Google Scholar] [PubMed]
  74. De Volder, A.; Michel, C.; Guérit, J.; Bol, A.; Georges, B.; de Barsy, T.; Laterre, C. Brain glucose metabolism in postanoxic syndrome due to cardiac arrest. Acta Neurol. Belg. 1994, 94, 183–189. [Google Scholar] [PubMed]
  75. Krinsley, J.S. Glycemic variability: A strong independent predictor of mortality in critically ill patients. Crit. Care Med. 2008, 36, 3008–3013. [Google Scholar] [CrossRef] [PubMed]
  76. Kurtz, P.; Claassen, J.; Schmidt, J.M.; Helbok, R.; Hanafy, K.A.; Presciutti, M.; Lantigua, H.; Connolly, E.S.; Lee, K.; Badjatia, N.; et al. Reduced brain/serum glucose ratios predict cerebral metabolic distress and mortality after severe brain injury. Neurocrit. Care 2013, 19, 311–319. [Google Scholar] [CrossRef] [PubMed]
  77. Antunes, A.P.; Schiefecker, A.J.; Beer, R.; Pfausler, B.; Sohm, F.; Fischer, M.; Dietmann, A.; Lackner, P.; Hackl, W.O.; Ndayisaba, J.P.; et al. Higher brain extracellular potassium is associated with brain metabolic distress and poor outcome after aneurysmal subarachnoid hemorrhage. Crit. Care 2014, 18, R119. [Google Scholar] [CrossRef] [PubMed]
  78. Misini, B.; Freinbichler, W.; Colivicchi, M.A.; Bisilimi, K.; Linert, W.; Tipton, K.F.; Della Corte, L. Continuous monitoring of highly reactive oxygen radicals during in vivo microdialysis. J. Neurosci. Methods 2015, 251, 1–6. [Google Scholar] [CrossRef] [PubMed]
  79. Helbok, R.; Schiefecker, A.J.; Beer, R.; Dietmann, A.; Antunes, A.P.; Sohm, F.; Fischer, M.; Hackl, W.O.; Rhomberg, P.; Lackner, P.; et al. Early brain injury after aneurysmal subarachnoid hemorrhage: A multimodal neuromonitoring study. Crit. Care 2015, 19, 75. [Google Scholar] [CrossRef] [PubMed]
  80. Aries, M.J.; Czosnyka, M.; Budohoski, K.P.; Steiner, L.A.; Lavinio, A.; Kolias, A.G.; Hutchinson, P.J.; Brady, K.M.; Menon, D.K.; Pickard, J.D.; et al. Continuous determination of optimal cerebral perfusion pressure in traumatic brain injury. Crit. Care Med. 2012, 40, 2456–2463. [Google Scholar] [CrossRef] [PubMed]
  81. Dias, C.; Silva, M.J.; Pereira, E.; Monteiro, E.; Maia, I.; Barbosa, S.; Silva, S.; Honrado, T.; Cerejo, A.; Aries, M.J.; et al. Optimal cerebral perfusion pressure management at bedside: A single-center pilot study. Neurocrit. Care 2015, 23, 92–102. [Google Scholar] [CrossRef] [PubMed]
  82. Sugimoto, K.; Shirao, S.; Koizumi, H.; Inoue, T.; Oka, F.; Maruta, Y.; Suehiro, E.; Sadahiro, H.; Oku, T.; Yoneda, H.; et al. Continuous monitoring of spreading depolarization and cerebrovascular autoregulation after aneurysmal subarachnoid hemorrhage. J. Stroke Cerebrovasc. Dis. 2016, 25, e171–e177. [Google Scholar] [CrossRef] [PubMed]
  83. Johnson, U.; Engquist, H.; Howells, T.; Nilsson, P.; Ronne-Engstrom, E.; Lewen, A.; Rostami, E.; Enblad, P. Bedside xenon-ct shows lower cbf in sah patients with impaired cbf pressure autoregulation as defined by pressure reactivity index (PRx). Neurocrit. Care 2016, 25, 47–55. [Google Scholar] [CrossRef] [PubMed]
  84. Le Roux, P.; Menon, D.K.; Citerio, G.; Vespa, P.; Bader, M.K.; Brophy, G.M.; Diringer, M.N.; Stocchetti, N.; Videtta, W.; Armonda, R.; et al. Consensus summary statement of the international multidisciplinary consensus conference on multimodality monitoring in neurocritical care: A statement for healthcare professionals from the neurocritical care society and the european society of intensive care medicine. Neurocrit. Care 2014, 21, S1–S26. [Google Scholar] [PubMed]
  85. Kurtz, P.; Helbok, R.; Claassen, J.; Schmidt, J.M.; Fernandez, L.; Stuart, R.M.; Connolly, E.S.; Lee, K.; Mayer, S.A.; Badjatia, N. The effect of packed red blood cell transfusion on cerebral oxygenation and metabolism after subarachnoid hemorrhage. Neurocrit. Care 2016, 24, 118–121. [Google Scholar] [CrossRef] [PubMed]
  86. Deshaies, E.M.; Jacobsen, W.; Singla, A.; Li, F.; Gorji, R. Brain tissue oxygen monitoring to assess reperfusion after intra-arterial treatment of aneurysmal subarachnoid hemorrhage-induced cerebral vasospasm: A retrospective study. Am. J. Neuroradiol. 2012, 33, 1411–1415. [Google Scholar] [CrossRef] [PubMed]
  87. Spiotta, A.M.; Stiefel, M.F.; Gracias, V.H.; Garuffe, A.M.; Kofke, W.A.; Maloney-Wilensky, E.; Troxel, A.B.; Levine, J.M.; Le Roux, P.D. Brain tissue oxygen-directed management and outcome in patients with severe traumatic brain injury. J. Neurosurg. 2010, 113, 571–580. [Google Scholar] [CrossRef] [PubMed]
  88. Narotam, P.K.; Morrison, J.F.; Nathoo, N. Brain tissue oxygen monitoring in traumatic brain injury and major trauma: Outcome analysis of a brain tissue oxygen-directed therapy. J. Neurosurg. 2009, 111, 672–682. [Google Scholar] [CrossRef] [PubMed]
  89. Lin, C.M.; Lin, M.C.; Huang, S.J.; Chang, C.K.; Chao, D.P.; Lui, T.N.; Ma, H.I.; Liu, M.Y.; Chung, W.Y.; Shih, Y.H.; et al. A prospective randomized study of brain tissue oxygen pressure-guided management in moderate and severe traumatic brain injury patients. BioMed Res. Int. 2015, 2015, 529580. [Google Scholar] [CrossRef] [PubMed]
  90. Kistka, H.; Dewan, M.C.; Mocco, J. Evidence-based cerebral vasospasm surveillance. Neurol. Res. Int. 2013, 2013, 256713. [Google Scholar] [CrossRef] [PubMed]
  91. Crowley, R.W.; Medel, R.; Kassell, N.F.; Dumont, A.S. New insights into the causes and therapy of cerebral vasospasm following subarachnoid hemorrhage. Drug Discov. Today 2008, 13, 254–260. [Google Scholar] [CrossRef] [PubMed]
  92. Nakajima, R.; Jung, A.; Yoon, B.J.; Baker, B.J. Optogenetic monitoring of synaptic activity with genetically encoded voltage indicators. Front. Synaptic Neurosci. 2016, 8, 22. [Google Scholar] [CrossRef] [PubMed]
  93. Gong, Y.; Huang, C.; Li, J.Z.; Grewe, B.F.; Zhang, Y.; Eismann, S.; Schnitzer, M.J. High-speed recording of neural spikes in awake mice and flies with a fluorescent voltage sensor. Science 2015, 350, 1361–1366. [Google Scholar] [CrossRef] [PubMed]
  94. Cao, G.; Platisa, J.; Pieribone, V.A.; Raccuglia, D.; Kunst, M.; Nitabach, M.N. Genetically targeted optical electrophysiology in intact neural circuits. Cell 2013, 154, 904–913. [Google Scholar] [CrossRef] [PubMed]
  95. Jayaprakash, N.; Wang, Z.; Hoeynck, B.; Krueger, N.; Kramer, A.; Balle, E.; Wheeler, D.S.; Wheeler, R.A.; Blackmore, M.G. Optogenetic interrogation of functional synapse formation by corticospinal tract axons in the injured spinal cord. J. Neurosci. 2016, 36, 5877–5890. [Google Scholar] [CrossRef] [PubMed]
Ijms 18 00043 g001 550
Figure 1. Computed tomography showing External ventricular drain (EVD) and microdialysis (µD) probe in place in aSAH patient. Sometimes the multimodality monitoring probes are in proximity to injured brain, but often they are not. Severe vasospasm resulting in ischemic brain (arrows) occurred days after anterior communicating artery aneurysm clipping (*).
Figure 1. Computed tomography showing External ventricular drain (EVD) and microdialysis (µD) probe in place in aSAH patient. Sometimes the multimodality monitoring probes are in proximity to injured brain, but often they are not. Severe vasospasm resulting in ischemic brain (arrows) occurred days after anterior communicating artery aneurysm clipping (*).
Ijms 18 00043 g001
Table
Table 1. Techniques for brain monitoring.
Table 1. Techniques for brain monitoring.
TechniqueDetailAdvantagesDisadvantages
Neurologic examinationGlobal assessment of consciousness, sensory and motor responses, cranial nerve assessment, and ancillary testsCan be used in all patients; findings can direct additional confirmatory testing or imagingAffected by sedation, fever, seizure; in severely injured, exam may be static despite dynamic neurologic injury
Intracranial pressure (ICP) monitorAvailable as ventricular or parenchymal probeWell-established in traumatic brain injury; Ventricular drain allows removal of cerebrospinal fluid for ICP therapy/labsInvasive monitor, potential risk of infection, hardware malfunction
Pressure reactivity index (PRx)Algorithm relates changes in blood pressure to ICP to determine measure of autoregulationIndividualized measure of autoregulation and goal directed cerebral perfusion pressure (CPP) therapyRequires concurrent ICP monitor; an optimal CPP not always able to be calculated; software malfunction
MicrodialysisIntraparenchymal probe obtains dialysate for lab assaysInformative of cerebral microenvironment and metabolic state; special lab assays possibleInvasive monitor, potential risk of infection, hardware malfunction, results potentially not reflective of entire brain
PbtO2Intraparenchymal probe measures partial pressure of oxygenEnables targeted therapyInvasive monitor, potential risk of infection, hardware malfunction, results potentially not reflective of entire brain
Serum markersMeasure of proteins indicative of neuronal injuryNon-invasive prognosticator of outcomeNot “real-time”. Affected by extracranial trauma and timing of injury. Subject to differences in specimen handling, hemolysis and differences between laboratory assays
Continuous electroencephalographyAssess brain electrical activity through scalp electrodesCerebral metabolic rate related to brain activity. Despite effects of sedative medications, may still be clinically useful [16]May be affected by sedation, intracranial mass lesions, presence of other intracranial monitors; inherently subjective interpretation; hardware malfunction; continuous monitoring not widely available
Near-infrared spectroscopy/diffuse correlation spectroscopyOptical probes placed on scalp. Measures cerebral oxygenation (NIS) and cerebral blood flow (DCS)Non-invasive, cerebral oxygenation and extraction related to metabolism, cerebral blood flow, continuous monitoring possibleAssess brain tissue to a depth of 2–3 cm, typically frontal lobes
Table
Table 2. Use of multimodality monitoring.
Table 2. Use of multimodality monitoring.
GroupModalities UsedFindingsComment
Bouzat et al., 2015 [68]ICP monitorMultimodality monitoring is more accurate than ICP monitoring alone to predict cerebral hypoperfusionMultimodality monitoring provides better guidance for the intensivist than ICP monitoring alone
PbtO2
cerebral microdialysis
Spiotta et al., 2010 [87]ICP monitoring, PbtO2Concurrent ICP/PbtO2 targeted therapy resulted in lower mortality (25.7% vs. 45.3%, p < 0.05) and improved 3-month favorable outcomes (64.3% vs. 39.6%, p = 0.01) compared to ICP monitoring aloneUse of multiple markers of the brain microenvironment improves clinical outcomes
Narotam et al., 2009 [88]Standard ICP/PbtO2 goal directed therapy led to reduction in mortality (25.9% vs. 41.5%) and improved 6-month GOS outcomes over standard ICP/CPP therapy alone
Lin et al., 2015 [89]Concurrent goal directed ICP/PbtO2 therapy in TBI patients resulted in improved 3 and 6 month mortality compared to ICP therapy alone
Dias et al., 2015 [81]ICP monitoringPatients with unfavorable outcomes at 6 months had a median difference in CPP from CPPopt of −6.6 mmHg, compared with a difference of −1.0 mmHg in the favorable outcomes group (p = 0.04)Individualized goal-directed therapy improves outcomes
PRx

Share and Cite

MDPI and ACS Style

Jones, S.; Schwartzbauer, G.; Jia, X. Brain Monitoring in Critically Neurologically Impaired Patients. Int. J. Mol. Sci. 2017, 18, 43. https://doi.org/10.3390/ijms18010043

AMA Style

Jones S, Schwartzbauer G, Jia X. Brain Monitoring in Critically Neurologically Impaired Patients. International Journal of Molecular Sciences. 2017; 18(1):43. https://doi.org/10.3390/ijms18010043

Chicago/Turabian Style

Jones, Salazar, Gary Schwartzbauer, and Xiaofeng Jia. 2017. "Brain Monitoring in Critically Neurologically Impaired Patients" International Journal of Molecular Sciences 18, no. 1: 43. https://doi.org/10.3390/ijms18010043

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop