Multi-Center Study of Diffusion-Weighted Imaging in Coma After Cardiac Arrest

Quantitative analysis of apparent diffusion coefficients to predict neurological prognosis in cardiac arrest survivors: an observational derivation and internal-external validation study

BACKGROUND

This study aimed to validate apparent diffusion coefficient (ADC) values and thresholds to predict poor neurological outcomes in out-of-hospital cardiac arrest (OHCA) survivors by quantitatively analysing the ADC values via brain magnetic resonance imaging (MRI).

METHODS

This observational study used prospectively collected data from two tertiary academic hospitals. The derivation cohort comprised 70% of the patients randomly selected from one hospital, whereas the internal validation cohort comprised the remaining 30%. The external validation cohort used the data from another hospital, and the MRI data were restricted to scans conducted at 3 T within 72-96 h after an OHCA experience. We analysed the percentage of brain volume below a specific ADC value at 50-step intervals ranging from 200 to 1200 × 10-6 mm2/s, identifying thresholds that differentiate between good and poor outcomes. Poor neurological outcomes were defined as cerebral performance categories 3-5, 6 months after experiencing an OHCA.

RESULTS

A total of 448 brain MRI scans were evaluated, including a derivation cohort (n = 224) and internal/external validation cohorts (n = 96/128, respectively). The proportion of brain volume with ADC values below 450, 500, 550, 600, and 650 × 10-6 mm2/s demonstrated good to excellent performance in predicting poor neurological outcomes in the derivation group (area under the curve [AUC] 0.89-0.91), and there were no statistically significant differences in performances among the derivation, internal validation, and external validation groups (all P > 0.5). Among these, the proportion of brain volume with an ADC below 600 × 10-6 mm2/s predicted a poor outcome with a 0% false-positive rate (FPR) and 76% (95% confidence interval [CI] 68-83) sensitivity at a threshold of > 13.2% in the derivation cohort. In both the internal and external validation cohorts, when using the same threshold, a specificity of 100% corresponded to sensitivities of 71% (95% CI 58-81) and 78% (95% CI 66-87), respectively.

CONCLUSIONS

In this validation study, by consistently restricting the MRI types and timing during quantitative analysis of ADC values in brain MRI, we observed high reproducibility and sensitivity at a 0% FPR. Prospective multicentre studies are necessary to validate these findings.

Feasibility of Magnetic Resonance-Based Conductivity Imaging as a Tool to Estimate the Severity of Hypoxic-Ischemic Brain Injury in the First Hours After Cardiac Arrest

BACKGROUND

Early identification of the severity of hypoxic-ischemic brain injury (HIBI) after cardiac arrest can be used to help plan appropriate subsequent therapy. We evaluated whether conductivity of cerebral tissue measured using magnetic resonance-based conductivity imaging (MRCI), which provides contrast derived from the concentration and mobility of ions within the imaged tissue, can reflect the severity of HIBI in the early hours after cardiac arrest.

METHODS

Fourteen minipigs were resuscitated after 5 min or 12 min of untreated cardiac arrest. MRCI was performed at baseline and at 1 h and 3.5 h after return of spontaneous circulation (ROSC).

RESULTS

In both groups, the conductivity of cerebral tissue significantly increased at 1 h after ROSC compared with that at baseline (P = 0.031 and 0.016 in the 5-min and 12-min groups, respectively). The increase was greater in the 12-min group, resulting in significantly higher conductivity values in the 12-min group (P = 0.030). At 3.5 h after ROSC, the conductivity of cerebral tissue in the 12-min group remained increased (P = 0.022), whereas that in the 5-min group returned to its baseline level.

CONCLUSIONS

The conductivity of cerebral tissue was increased in the first hours after ROSC, and the increase was more prominent and lasted longer in the 12-min group than in the 5-min group. Our findings suggest the promising potential of MRCI as a tool to estimate the severity of HIBI in the early hours after cardiac arrest.

Association of EEG Background With Diffusion-Weighted Magnetic Resonance Neuroimaging and Short-Term Outcomes After Pediatric Cardiac Arrest

BACKGROUND AND OBJECTIVES

EEG and MRI features are independently associated with pediatric cardiac arrest (CA) outcomes, but it is unclear whether their combination improves outcome prediction. We aimed to assess the association of early EEG background category with MRI ischemia after pediatric CA and determine whether addition of MRI ischemia to EEG background features and clinical variables improves short-term outcome prediction.

METHODS

This was a single-center retrospective cohort study of pediatric CA with EEG initiated ≤24 hours and MRI obtained ≤7 days of return of spontaneous circulation. Initial EEG background was categorized as normal, slow/disorganized, discontinuous/burst-suppression, or attenuated-featureless. MRI ischemia was defined as percentage of brain tissue with apparent diffusion coefficient (ADC) <650 × 10-6 mm2/s and categorized as high (≥10%) or low (<10%). Outcomes were mortality and unfavorable neurologic outcome (Pediatric Cerebral Performance Category increase ≥1 from baseline resulting in ICU discharge score ≥3). The Kruskal-Wallis test evaluated the association of EEG with MRI. Area under the receiver operating characteristic (AUROC) curve evaluated predictive accuracy. Logistic regression and likelihood ratio tests assessed multivariable outcome prediction.

RESULTS

We evaluated 90 individuals. EEG background was normal in 16 (18%), slow/disorganized in 42 (47%), discontinuous/burst-suppressed in 12 (13%), and attenuated-featureless in 20 (22%) individuals. The median percentage of MRI ischemia was 5% (interquartile range 1-18); 32 (36%) individuals had high MRI ischemia burden. Twenty-eight (31%) individuals died, and 58 (64%) had unfavorable neurologic outcome. Worse EEG background category was associated with more MRI ischemia (p < 0.001). The combination of EEG background and MRI ischemia burden had higher predictive accuracy than EEG alone (AUROC: mortality: 0.92 vs 0.87, p = 0.03) or MRI alone (AUROC: mortality: 0.92 vs 0.84, p = 0.02; unfavorable: 0.83 vs 0.73, p < 0.01). Addition of percentage of MRI ischemia to clinical variables and EEG background category improved prediction for mortality (χ2 = 19.1, p < 0.001) and unfavorable neurologic outcome (χ2 = 4.8, p = 0.03) and achieved high predictive accuracy (AUROC: mortality: 0.97; unfavorable: 0.92).

DISCUSSION

Early EEG background category was associated with MRI ischemia after pediatric CA. Combining EEG and MRI data yielded higher outcome predictive accuracy than either modality alone. The addition of MRI ischemia to clinical variables and EEG background improved short-term outcome prediction.

Recovery and Survival of Patients After Out-of-Hospital Cardiac Arrest: A Literature Review Showcasing the Big Picture of Intensive Care Unit-Related Factors

As an important public health issue, out-of-hospital cardiac arrest (OHCA) requires several stages of high quality medical care, both on-field and after hospital admission. Post-cardiac arrest shock can lead to severe neurological injury, resulting in poor recovery outcome and increased risk of death. These characteristics make this condition one of the most important issues to deal with in post-OHCA patients hospitalized in intensive care units (ICUs). Also, the majority of initial post-resuscitation survivors have underlying coronary diseases making revascularization procedure another crucial step in early management of these patients. Besides keeping myocardial blood flow at a satisfactory level, other tissues must not be neglected as well, and maintaining mean arterial pressure within optimal range is also preferable. All these procedures can be simplified to a certain level along with using targeted temperature management methods in order to decrease metabolic demands in ICU-hospitalized post-OHCA patients. Additionally, withdrawal of life-sustaining therapy as a controversial ethical topic is under constant re-evaluation due to its possible influence on overall mortality rates in patients initially surviving OHCA. Focusing on all of these important points in process of managing ICU patients is an imperative towards better survival and complete recovery rates.

Quantitative analysis of early apparent diffusion coefficient values from MRIs for predicting neurological prognosis in survivors of out-of-hospital cardiac arrest: an observational study

BACKGROUND

This study aimed to quantitatively analyse ultra-early brain diffusion-weighted magnetic resonance imaging (DW-MRI) findings to determine the apparent diffusion coefficient (ADC) threshold associated with neurological outcomes in comatose survivors of out-of-hospital cardiac arrest (OHCA).

METHODS

This retrospective study included adult survivors of comatose OHCA who underwent DW-MRI imaging scans using a 3-T MRI scanner within 6 h of the return of spontaneous circulation (ROSC). We investigated the association between neurological outcomes and ADC values obtained through voxel-based analysis on DW-MRI. Additionally, we constructed multivariable logistic regression models with pupillary light reflex (PLR), serum neuron-specific enolase (NSE), and ADC values as independent variables to predict poor neurological outcomes. The primary outcome was poor neurological outcome 6 months after ROSC, determined by the Cerebral Performance Category 3-5.

RESULTS

Overall, 131 patients (26% female) were analysed, of whom 74 (57%) showed poor neurological outcomes. The group with a poor neurological outcome had lower mean whole brain ADC values (739.1 vs. 787.1 × 10-6 mm/s) and higher percentages of voxels with ADC below threshold in all ranges (250-1150) (all P < 0.001). The mean whole brain ADC values (area under the receiver operating characteristic curve [AUC] 0.83) and the percentage of voxels with ADC below 600 (AUC 0.81) had the highest sensitivity of 51% (95% confidence interval [CI] 39.4-63.1; cut-off value ≤ 739.2 × 10-6 mm2/s and > 17.2%, respectively) when the false positive rate (FPR) was 0%. In the multivariable model, which also included PLR, NSE, and mean whole brain ADC values, poor neurological outcome was predicted with the highest accuracy (AUC 0.91; 51% sensitivity). This model showed more accurate prediction and sensitivity at an FPR of 0% than did the combination of PLR and NSE (AUC 0.86; 30% sensitivity; P = 0.03).

CONCLUSIONS

In this cohort study, early voxel-based quantitative ADC analysis after ROSC was associated with poor neurological outcomes 6 months after cardiac arrest. The mean whole brain ADC value demonstrated the highest sensitivity when the FPR was 0%, and including it in the multivariable model improved the prediction of poor neurological outcomes.

Neuroprognostication after cardiac arrest: what the cardiologist should know

Two aspects are a key to mastering prognostication of comatose cardiac arrest survivors: a detailed knowledge about the clinical trajectories of consciousness recovery (or lack thereof) and the ability to correctly interpret the results of multimodal investigations, which include clinical examination, electroencephalography, neuroimaging, evoked potentials, and blood biomarkers. While the very good and the very poor ends of the clinical spectrum typically do not pose diagnostic challenges, the intermediate 'grey zone' of post-cardiac arrest encephalopathy requires cautious interpretation of the available information and sufficiently long clinical observation. Late recovery of coma patients with initially ambiguous diagnostic results is increasingly reported, as are unresponsive patients with various forms of residual consciousness, including so-called cognitive motor dissociation, rendering prognostication of post-anoxic coma highly complex. The aim of this paper is to provide busy clinicians with a high-yield, concise overview of neuroprognostication after cardiac arrest, emphasizing notable developments in the field since 2020.

Prognosis of Cardiac Arrest-Peri-arrest and Post-arrest Considerations

There has been only a small improvement in survival and neurologic outcomes in patients with cardiac arrest in recent decades. Type of arrest, length of total arrest time, and location of arrest alter the trajectory of survival and neurologic outcome. In the post-arrest phase, clinical markers such as blood markers, pupillary light response, corneal reflex, myoclonic jerking, somatosensory evoked potential, and electroencephalography testing can be used to help guide neurological prognostication. Most of the testing should be performed 72 hours post-arrest with special considerations for longer observation periods in patients who underwent TTM or who had prolonged sedation and/or neuromuscular blockade.

Guidelines for Neuroprognostication in Comatose Adult Survivors of Cardiac Arrest

BACKGROUND

Among cardiac arrest survivors, about half remain comatose 72 h following return of spontaneous circulation (ROSC). Prognostication of poor neurological outcome in this population may result in withdrawal of life-sustaining therapy and death. The objective of this article is to provide recommendations on the reliability of select clinical predictors that serve as the basis of neuroprognostication and provide guidance to clinicians counseling surrogates of comatose cardiac arrest survivors.

METHODS

A narrative systematic review was completed using Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. Candidate predictors, which included clinical variables and prediction models, were selected based on clinical relevance and the presence of an appropriate body of evidence. The Population, Intervention, Comparator, Outcome, Timing, Setting (PICOTS) question was framed as follows: "When counseling surrogates of comatose adult survivors of cardiac arrest, should [predictor, with time of assessment if appropriate] be considered a reliable predictor of poor functional outcome assessed at 3 months or later?" Additional full-text screening criteria were used to exclude small and lower-quality studies. Following construction of the evidence profile and summary of findings, recommendations were based on four GRADE criteria: quality of evidence, balance of desirable and undesirable consequences, values and preferences, and resource use. In addition, good practice recommendations addressed essential principles of neuroprognostication that could not be framed in PICOTS format.

RESULTS

Eleven candidate clinical variables and three prediction models were selected based on clinical relevance and the presence of an appropriate body of literature. A total of 72 articles met our eligibility criteria to guide recommendations. Good practice recommendations include waiting 72 h following ROSC/rewarming prior to neuroprognostication, avoiding sedation or other confounders, the use of multimodal assessment, and an extended period of observation for awakening in patients with an indeterminate prognosis, if consistent with goals of care. The bilateral absence of pupillary light response > 72 h from ROSC and the bilateral absence of N20 response on somatosensory evoked potential testing were identified as reliable predictors. Computed tomography or magnetic resonance imaging of the brain > 48 h from ROSC and electroencephalography > 72 h from ROSC were identified as moderately reliable predictors.

CONCLUSIONS

These guidelines provide recommendations on the reliability of predictors of poor outcome in the context of counseling surrogates of comatose survivors of cardiac arrest and suggest broad principles of neuroprognostication. Few predictors were considered reliable or moderately reliable based on the available body of evidence.

Parieto-Occipital Injury on Diffusion MRI Correlates with Poor Neurologic Outcome following Cardiac Arrest

BACKGROUND AND PURPOSE

MR imaging of the brain provides unbiased neuroanatomic evaluation of brain injury and is useful for neurologic prognostication following cardiac arrest. Regional analysis of diffusion imaging may provide additional prognostic value and help reveal the neuroanatomic underpinnings of coma recovery. The purpose of this study was to evaluate global, regional, and voxelwise differences in diffusion-weighted MR imaging signal in patients in a coma after cardiac arrest.

MATERIALS AND METHODS

We retrospectively analyzed diffusion MR imaging data from 81 subjects who were comatose for >48 hours following cardiac arrest. Poor outcome was defined as the inability to follow simple commands at any point during hospitalization. ADC differences between groups were evaluated across the whole brain, locally by using voxelwise analysis and regionally by using ROI-based principal component analysis.

RESULTS

Subjects with poor outcome had more severe brain injury as measured by lower average whole-brain ADC (740 [SD, 102] × 10-6 mm2/s versus 833 [SD, 23] × 10-6 mm2/s, P < .001) and larger average volumes of tissue with ADC below 650 × 10-6 mms/s (464 [SD, 469] mL versus 62 [SD, 51] mL, P < .001). Voxelwise analysis showed lower ADC in the bilateral parieto-occipital areas and perirolandic cortices for the poor outcome group. ROI-based principal component analysis showed an association between lower ADC in parieto-occipital regions and poor outcome.

CONCLUSIONS

Brain injury affecting the parieto-occipital region measured with quantitative ADC analysis was associated with poor outcomes after cardiac arrest. These results suggest that injury to specific brain regions may influence coma recovery.

Free water corrected diffusion tensor imaging discriminates between good and poor outcomes of comatose patients after cardiac arrest

OBJECTIVES

Approximately 50% of comatose patients after cardiac arrest never regain consciousness. Cerebral ischaemia may lead to cytotoxic and/or vasogenic oedema, which can be detected by diffusion tensor imaging (DTI). Here, we evaluate the potential value of free water corrected mean diffusivity (MD) and fractional anisotropy (FA) based on DTI, for the prediction of neurological recovery of comatose patients after cardiac arrest.

METHODS

A total of 50 patients after cardiac arrest were included in this prospective cohort study in two Dutch hospitals. DTI was obtained 2-4 days after cardiac arrest. Outcome was assessed at 6 months, dichotomised as poor (cerebral performance category 3-5; n = 20) or good (n = 30) neurological outcome. We calculated the whole brain mean MD and FA and compared between patients with good and poor outcomes. In addition, we compared a preliminary prediction model based on clinical parameters with or without the addition of MD and FA.

RESULTS

We found significant differences between patients with good and poor outcome of mean MD (good: 726 [702-740] × 10^-6 mm²/s vs. poor: 663 [575-736] × 10^-6 mm²/s; p = 0.01) and mean FA (0.30 ± 0.03 vs. 0.28 ± 0.03; p = 0.03). An exploratory prediction model combining clinical parameters, MD and FA increased the sensitivity for reliable prediction of poor outcome from 60 to 85%, compared to the model containing clinical parameters only, but confidence intervals are overlapping.

CONCLUSIONS

Free water-corrected MD and FA discriminate between patients with good and poor outcomes after cardiac arrest and hold the potential to add to multimodal outcome prediction.

KEY POINTS

• Whole brain mean MD and FA differ between patients with good and poor outcome after cardiac arrest. • Free water-corrected MD can better discriminate between patients with good and poor outcome than uncorrected MD. • A combination of free water-corrected MD (sensitive to grey matter abnormalities) and FA (sensitive to white matter abnormalities) holds potential to add to the prediction of outcome.

Association Between Quantitative Diffusion-Weighted Magnetic Resonance Neuroimaging and Outcome After Pediatric Cardiac Arrest

BACKGROUND AND OBJECTIVES

Diffusion MRI can quantify the extent of hypoxic-ischemic brain injury after cardiac arrest. Our objective was to determine the association between the adult-derived threshold of apparent diffusion coefficient (ADC) <650 × 10-6 mm2/s in >10% of brain tissue and an unfavorable outcome after pediatric cardiac arrest. Since ADC decreases exponentially as a function of increasing age, we determined the association between (1) having >10% of brain tissue below a novel age-dependent ADC threshold, and (2) age-normalized whole-brain mean ADC and unfavorable outcome.

METHODS

This was a retrospective study of patients aged ≤18 years who had cardiac arrest and a clinically obtained brain MRI within 7 days. The primary outcome was unfavorable neurologic status at hospital discharge based on the Pediatric Cerebral Performance Category score. ADC images were extracted from 3-direction diffusion imaging. We determined whether each patient had >10% of voxels with an ADC below prespecified thresholds. We computed the whole-brain mean ADC for each patient.

RESULTS

One hundred thirty-four patients were analyzed. Patients with ADC <650 × 10-6 mm2/s in >10% of voxels had 15 times higher odds (95% CI 5-65) of an unfavorable outcome compared with patients with ADC <650 × 10-6 mm2/s (area under the receiver operating characteristic curve [AUROC] 0.72 [95% CI 0.63-0.80]). These ADC criteria had a sensitivity and specificity of 0.49 and 0.94, respectively, and positive and negative predictive values of 0.93 and 0.52, respectively, for an unfavorable outcome. The age-dependent ADC threshold that yielded optimal sensitivity and specificity for unfavorable outcomes was <300 × 10-6 mm2/s below each patient's predicted whole-brain mean ADC. The sensitivity, specificity, and positive and negative predictive values for this ADC threshold were 0.53, 0.96, 0.96, and 0.54, respectively (odds ratio [OR] 26.4 [95% CI 7.5-168.3]; AUROC 0.74 [95% CI 0.66-0.83]). Lower age-normalized whole-brain mean ADC was also associated with an unfavorable outcome (OR 0.42 [0.24-0.64], AUROC 0.76 [95% CI 0.66-0.82]).

DISCUSSION

Quantitative diffusion thresholds on MRI within 7 days after cardiac arrest were associated with an unfavorable outcome in children. The age-independent ADC threshold was highly specific for predicting an unfavorable outcome. However, the specificity and sensitivity increased when using age-dependent ADC thresholds. Age-dependent ADC thresholds may improve prognostic accuracy and require further investigation in larger cohorts.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that quantitative diffusion-weighted imaging within 7 days postarrest can predict an unfavorable clinical outcome in children.

Regional Distribution of Brain Injury After Cardiac Arrest: Clinical and Electrographic Correlates

BACKGROUND AND OBJECTIVES

Disorders of consciousness, EEG background suppression, and epileptic seizures are associated with poor outcome after cardiac arrest. Our objective was to identify the distribution of diffusion MRI-measured anoxic brain injury after cardiac arrest and to define the regional correlates of disorders of consciousness, EEG background suppression, and seizures.

METHODS

We analyzed patients from a single-center database of unresponsive patients who underwent diffusion MRI after cardiac arrest (n = 204). We classified each patient according to recovery of consciousness (command following) before discharge, the most continuous EEG background (burst suppression vs continuous), and the presence or absence of seizures. Anoxic brain injury was measured with the apparent diffusion coefficient (ADC) signal. We identified ADC abnormalities relative to controls without cardiac arrest (n = 48) and used voxel lesion symptom mapping to identify regional associations with disorders of consciousness, EEG background suppression, and seizures. We then used a bootstrapped lasso regression procedure to identify robust, multivariate regional associations with each outcome variable. Last, using area under receiver operating characteristic curves, we then compared the classification ability of the strongest regional associations to that of brain-wide summary measures.

RESULTS

Compared to controls, patients with cardiac arrest demonstrated ADC signal reduction that was most significant in the occipital lobes. Disorders of consciousness were associated with reduced ADC most prominently in the occipital lobes but also in deep structures. Regional injury more accurately classified patients with disorders of consciousness than whole-brain injury. Background suppression mapped to a similar set of brain regions, but regional injury could no better classify patients than whole-brain measures. Seizures were less common in patients with more severe anoxic injury, particularly in those with injury to the lateral temporal white matter.

DISCUSSION

Anoxic brain injury was most prevalent in posterior cerebral regions, and this regional pattern of injury was a better predictor of disorders of consciousness than whole-brain injury measures. EEG background suppression lacked a specific regional association, but patients with injury to the temporal lobe were less likely to have seizures. Regional patterns of anoxic brain injury are relevant to the clinical and electrographic sequelae of cardiac arrest and may hold importance for prognosis.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that disorders of consciousness after cardiac arrest are associated with widely lower ADC values on diffusion MRI and are most strongly associated with reductions in occipital ADC.

Outcome and prognostication after cardiac arrest

The outcome after out-of-hospital cardiac arrest has historically been grim at best. The current overall survival rate of patients admitted to a hospital is approximately 10%, making cardiac arrest one of the leading causes of death in the United States. The situation is improving with the incorporation of therapeutic temperature modulation, aggressive prevention of secondary brain injury, and improved access to advanced cardiovascular support, all of which have decreased mortality and allowed for better outcomes. Mortality after cardiac arrest is often the direct result of active withdrawal of life-sustaining therapy based on the perception that neurological recovery is not possible. This reality highlights the importance of providing accurate estimates of neurological prognosis to decision makers when discussing goals of care. The current standard of care for assessing neurological status in patients with hypoxic-ischemic encephalopathy emphasizes a multimodal approach that includes five elements: (1) neurological examination off sedation, (2) continuous electroencephalography, (3) serum neuron-specific enolase levels, (4) magnetic resonance brain imaging, and (5) somatosensory-evoked potential testing. Sophisticated decision support systems that can integrate these clinical, imaging, and biomarker and neurophysiologic data and translate it into meaningful projections of neurological outcome are urgently needed.

Somatosensory Evoked Potentials and Neuroprognostication After Cardiac Arrest

Improved understanding of post-cardiac arrest syndrome and clinical practices such as targeted temperature management have led to improved mortality in this cohort. Attention has now been placed on development of tools to aid in predicting functional outcome in comatose cardiac arrest survivors. Current practice uses a multimodal approach including physical examination, neuroimaging, and electrophysiologic data, with a primary utility in predicting poor functional outcome. These modalities remain confounded by self-fulfilling prophecy and the withdrawal of life-sustaining therapies. To date, a reliable measure to predict good functional outcome has not been established or validated, but the use of quantitative somatosensory evoked potential (SSEP) shows potential for this use. MEDLINE and EMBASE search using words "Cardiac Arrest" and "SSEP," "Somato sensory evoked potentials," "qSSEP," "quantitative SSEP," "targeted temperature management in cardiac arrest" was conducted. Relevant recent studies on targeted temperature management in cardiac arrest, plus studies on SSEP in cardiac arrest in the setting of hypothermia and without hypothermia, were included. In addition, animal studies evaluating the role of different components of SSEP in cardiac arrest were reviewed. SSEP is a specific indicator of poor outcomes in post-cardiac arrest patients but lacks sensitivity and has not clinically been established to foresee good outcomes. Novel methods of analyzing quantitative SSEP (qSSEP) signals have shown potential to predict good outcomes in animal and human studies. In addition, qSSEP has potential to track cerebral recovery and guide treatment strategy in post-cardiac arrest patients. Lying beyond the current clinical practice of dichotomized absent/present N20 peaks, qSSEP has the potential to emerge as one of the earliest predictors of good outcome in comatose post-cardiac arrest patients. Validation of qSSEP markers in prospective studies to predict good and poor outcomes in the cardiac arrest population in the setting of hypothermia could advance care in cardiac arrest. It has the prospect to guide allocation of health care resources and reduce self-fulfilling prophecy.

Added Value of Quantitative Apparent Diffusion Coefficient Values for Neuroprognostication After Cardiac Arrest

OBJECTIVE

To test the prognostic value of brain MRI in addition to clinical and electrophysiologic variables in patients post-cardiac arrest (CA), we explored data from the randomized Neuroprotect Post-CA trial (NCT02541591).

METHODS

In this trial, brain MRIs were prospectively obtained. We calculated receiver operating characteristic (ROC) curves for the average apparent diffusion coefficient (ADC) value and percentage of brain voxels with an ADC value <650 × 10^-6 mm²/s and <450 × 10^-6 mm²/s. We constructed multivariable logistic regression models with clinical characteristics, EEG, somatosensory evoked potentials (SSEP), and ADC value as independent variables to predict good neurologic recovery.

RESULTS

In 79/102 patients, MRI data were available and in 58/79 patients all other data were available. At 180 days post-CA, 25/58 (43%) patients had good neurologic recovery. In univariable analysis of all tested MRI measures, average ADC value in the postcentral cortex had the highest accuracy to predict good neurologic recovery, with an area under the ROC curve (AUC) of 0.78. In the most optimal multivariable model, which also included corneal reflexes and EEG, this measure remained an independent predictor of good neurologic recovery (AUC 0.96, false-positive 27%). This model provided a more accurate prediction compared to the most optimal combination of EEG, corneal reflexes, and SSEP (p = 0.03).

CONCLUSIONS

Adding information on brain MRI in a multivariable model may improve the prediction of good neurologic recovery in patients post-CA.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that MRI ADC features predict neurologic recovery in patients post-CA.

Neuron-specific enolase and neuroimaging for prognostication after cardiac arrest treated with targeted temperature management

BACKGROUND

Prognostication after cardiac arrest (CA) needs a multimodal approach, but the optimal method is not known. We tested the hypothesis that the combination of neuron-specific enolase (NSE) and neuroimaging could improve outcome prediction after CA treated with targeted temperature management (TTM).

METHODS

A retrospective observational cohort study was performed on patients who underwent at least one NSE measurement between 48 and 72 hr; received both a brain computed tomography (CT) scan within 24 hr and diffusion-weighted magnetic resonance imaging (DW-MRI) within 7 days after return of spontaneous circulation (ROSC); and were treated with TTM after out-of-hospital CA between 2009 and 2017 at the Seoul St. Mary's Hospital in Korea. The primary outcome was a poor neurological outcome at 6 months after CA, defined as a cerebral performance category of 3-5.

RESULTS

A total of 109 subjects underwent all three tests and were ultimately included in this study. Thirty-four subjects (31.2%) experienced good neurological outcomes at 6 months after CA. The gray matter to white matter attenuation ratio (GWR) was weakly correlated with the mean apparent diffusion coefficient (ADC), PV400 and NSE (Spearman's rho: 0.359, -0.362 and -0.263, respectively). NSE was strongly correlated with the mean ADC and PV400 (Spearman's rho: -0.623 and 0.666, respectively). Serum NSE had the highest predictive value among the single parameters (area under the curve (AUC) 0.912, sensitivity 70.7% for maintaining 100% specificity). The combination of a DWI parameter (mean ADC or PV400) and NSE had better prognostic performance than the combination of the CT parameter (GWR) and NSE. The addition of the GWR to a DWI parameter and NSE did not improve the prediction of neurological outcomes.

CONCLUSION

The GWR (≤ 24 hr) is weakly correlated with the mean ADC (≤ 7 days) and NSE (highest between 48 and 72 hr). The combination of a DWI parameter and NSE has better prognostic performance than the combination of the GWR and NSE. The addition of the GWR to a DWI parameter and NSE does not improve the prediction of neurological outcomes after CA treatment with TTM.

Cerebral Infarction Observed on Brain MRI in Unconscious Out-of-Hospital Cardiac Arrest Survivors: A Pilot Study

BACKGROUND

Cumulative evidence regarding the use of brain magnetic resonance imaging (MRI) for predicting prognosis of unconscious out-of-hospital cardiac arrest (OHCA) survivors treated with targeted temperature management (TTM) is available. Theoretically, these patients are at a high risk of developing cerebral infarction. However, there is a paucity of reports regarding the characteristics of cerebral infarction in this population. Thus, we performed a pilot study to identify the characteristics and risk factors of cerebral infarction and to evaluate whether this infarction is associated with clinical outcomes.

METHODS

A single-center, retrospective, registry-based cohort study was conducted at Severance Hospital, a tertiary center. Unconscious OHCA survivors were registered and treated with TTM between September 2011 and December 2015. We included patients who underwent brain MRI in the first week after the return of spontaneous circulation. We excluded patients who underwent any endovascular interventions to focus on "procedure-unrelated" cerebral infarctions. We assessed hypoxic-ischemic encephalopathy (HIE) and procedure-unrelated cerebral infarction separately on MRI. Patients were categorized into the following groups based on MRI findings: HIE (-)/infarction (-), infarction-only, and HIE (+) groups. Conventional vascular risk factors showing p < 0.05 in univariate analyses were entered into multivariate logistic regression. We also evaluated if the presence of this procedure-unrelated cerebral infarction lesion or HIE was associated with a poor clinical outcome at discharge, defined as a cerebral performance category of 3-5.

RESULTS

Among 71 unconscious OHCA survivors who completed TTM, underwent MRI, and who did not undergo endovascular interventions, 14 (19.7%) patients had procedure-unrelated cerebral infarction based on MRI. Advancing age [odds ratio (OR) 1.11] and atrial fibrillation (OR 5.78) were independently associated with the occurrence of procedure-unrelated cerebral infarction (both p < 0.05). There were more patients with poor clinical outcomes at discharge in the HIE (+) group (88.1%) than in the infarction-only (30.0%) or HIE (-)/infarction (-) group (15.8%) (p < 0.001). HIE (+) (OR 38.69, p < 0.001) was independently associated with poor clinical outcomes at discharge, whereas infarction-only was not (p > 0.05), compared to HIE (-)/infarction (-).

CONCLUSIONS

In this pilot study, procedure-unrelated cerebral infarction was noted in approximately one-fifth of unconscious OHCA survivors who were treated with TTM and underwent MRI. Older age and atrial fibrillation might be associated with the occurrence of procedure-unrelated cerebral infarction, and cerebral infarction was not considered to be associated with clinical outcomes at discharge. Considering that the strict exclusion criteria in this pilot study resulted in a highly selected sample with a relatively small size, further work is needed to verify our findings.

Prognostic value of magnetic resonance imaging performed during the subacute phase in adult patients with hypoxic-ischemic encephalopathy for long-term neurological outcomes

OBJECTIVE

To investigate the value of a model based on brain magnetic resonance imaging (MRI) performed in the subacute phase (between the 1st and 30th day) in predicting long-term neurological outcomes of adult hypoxic-ischemic encephalopathy (HIE) patients.

METHODS

Ninety-six adult HIE patients who underwent conventional MRI and diffusion-weighted imaging (DWI) during the subacute phase were retrospectively analyzed. Favorable (Cerebral Performance Categories (CPC) 1-2) and unfavorable outcome (CPC 3-5) groups were created based on patient neurological status approximately three months after the onset of hypoxic-ischemic events. A multivariate stepwise regression model was applied after univariate analysis of MRI findings, and then the overall MRI score, Alberta Stroke Program Early Computed Tomography Score (ASPECTS), Bilateral ASPECTS (Bi-ASPECTS), modified ASPECTS (mASPECTS) and Bi-ASPECTS combined with posterior circulation ASPECTS (PC-ASPECTS) were calculated based on MRI findings. Receiver operating characteristic (ROC) curves were used to assess prognostic accuracy.

RESULTS

Both univariate and multivariate analyses showed the cerebral cortex and cerebellum, neostriatum, hippocampus, brainstem and postanoxic leukoencephalopathy were independent prognostic factors for unfavorable outcomes. The multivariate regression analysis resulted in an overall classification accuracy of 84.4%, a sensitivity of 84.2% (95% CI, 71.6-92.1%), and a specificity of 92.3% (95% CI, 78.0-98.0%) for unfavorable outcomes. The model had an areas under the ROC curves (AUC) of 0.944 (95% CI, 0.901-0.987); the MRI overall scores were 0.918 (95% CI, 0.866, 0.971), ASPECTS 0.839 (95% CI, 0.755, 0.923), Bi-ASPECTS 0.837 (95% CI, 0.753, 0.922), mASPECTS 0.851(95% CI, 0.771, 0.931) and Bi-ASPECTS+PC-ASPECTS 0.876 (95% CI, 0.806, 0.946).

CONCLUSIONS

The multivariate model based on conventional MRI combined with DWI performed in the subacute phase could help predict the prognosis of adult HIE with high performance.

Qualitative and quantitative analysis of diffusion-weighted brain MR imaging in comatose survivors after cardiac arrest

PURPOSE

The aim of this study is to compare a qualitative and a quantitative assessment of brain diffusion-weighted imaging (DWI) in predicting outcome of comatose patients after cardiac arrest (CA).

METHODS

Two observers used a scoring template to analyze the DWI of 75 patients. A total of 13 regions were scored from 0 to 3 (0 = normal, 1 = probably normal, 2 = probably abnormal, 3 = definitely abnormal). The total cerebral cortex (TCC), the total deep grey nuclei (TDGN), the total brain stem, the total cerebellum, and the total brain score were calculated. Intra- and inter-observer variability were tested. The mean whole brain apparent diffusion coefficient (ADC) values and percentage of voxels below a specific ADC value cut-off were calculated. The data were correlated with clinical outcome (cerebral performance category score after 180 days, dichotomized in a score 1-2 with favorable outcome and score 3-5 with unfavorable outcome) using ROC analysis.

RESULTS

Intra-observer variability was excellent for the TCC score (ICC 0.95 and 0.86) and the TDGN score (ICC 0.89 and 0.75). Inter-observer variability was good to excellent for total cerebral cortex score and total deep grey nuclei score in both the first (ICC 0.78 and 0.69) and third (ICC 0.86 and 0.83) image assessment. TCC and TDGN score show the best correlation with clinical outcome (highest AUC values 0.87 and 0.87). Quantitative parameters did not show good correlation with clinical outcome (AUC values 0.57 and 0.60).

CONCLUSION

A qualitative assessment of brain DWI using a scoring template provides useful data regarding patient outcome while quantitative data appeared less reliable.

Non-invasive cerebral perfusion monitoring in cardiac arrest patients: a prospective cohort study

OBJECTIVES

To determine if non-invasive cerebral perfusion estimation provided by a new acousto-optic technology can be used as a reliable predictor of neurological outcome.

PATIENTS AND METHODS

We performed a prospective, observational cohort study of consecutive comatose patients successfully resuscitated from out-of-hospital cardiac arrest. Patients were monitored using c-FLOW (Ornim Medical) from critical care unit admission up to 72 h, full awakening, or death. Primary outcome was favourable neurological outcome at hospital discharge, defined as a Cerebral Performance Category score of 1 or 2.

RESULTS

A total of 21 patients were enrolled, without any loss to follow-up. Mean perfusion index over the monitoring period was not associated with functional outcome at hospital discharge (OR 1.03 [0.93, 1.17]). Adjustment for initial rhythm, time to return of spontaneous circulation and Glasgow coma scale motor score did not significantly alter the results (OR 1.06 [0.99, 1.12]). Mean perfusion index showed a poor discriminative value with an area under the curve of 0.60 for functional outcome (0.64 for survival). Correlation between the probes was weak (Pearson coefficient 0.35).

CONCLUSION

Cerebral perfusion monitoring using a c-FLOW device in survivors of cardiac arrest is feasible, but reliability of the information provided has yet to be demonstrated. In our cohort, we were unable to identify any association between the perfusion index and clinical outcomes at discharge. As such, clinical management of cardiac arrest patients based on non-invasive perfusion index is not supported and should be limited to research protocols. The trial was registered with ClinicalTrials.gov, number NCT02575196.

Resting-State Brain Activity for Early Prediction Outcome in Postanoxic Patients in a Coma with Indeterminate Clinical Prognosis

BACKGROUND AND PURPOSE

Early outcome prediction of postanoxic patients in a coma after cardiac arrest proves challenging. Current prognostication relies on multimodal testing, using clinical examination, electrophysiologic testing, biomarkers, and structural MR imaging. While this multimodal prognostication is accurate for predicting poor outcome (ie, death), it is not sensitive enough to identify good outcome (ie, consciousness recovery), thus leaving many patients with indeterminate prognosis. We specifically assessed whether resting-state fMRI provides prognostic information, notably in postanoxic patients in a coma with indeterminate prognosis early after cardiac arrest, specifically for good outcome.

MATERIALS AND METHODS

We used resting-state fMRI in a prospective study to compare whole-brain functional connectivity between patients with good and poor outcomes, implementing support vector machine learning. Then, we automatically predicted coma outcome using resting-state fMRI and also compared the prediction based on resting-state fMRI with the outcome prediction based on DWI.

RESULTS

Of 17 eligible patients who completed the study procedure (among 351 patients screened), 9 regained consciousness and 8 remained comatose. We found higher functional connectivity in patients recovering consciousness, with greater changes occurring within and between the occipitoparietal and temporofrontal regions. Coma outcome prognostication based on resting-state fMRI machine learning was very accurate, notably for identifying patients with good outcome (accuracy, 94.4%; area under the receiver operating curve, 0.94). Outcome predictors using resting-state fMRI performed significantly better (P < .05) than DWI (accuracy, 60.0%; area under the receiver operating curve, 0.63).

CONCLUSIONS

Indeterminate prognosis might lead to major clinical uncertainty and significant variations in life-sustaining treatments. Resting-state fMRI might bridge the gap left in early prognostication of postanoxic patients in a coma by identifying those with both good and poor outcomes.

Prognostic value of diffusion-weighted MRI for post-cardiac arrest coma

OBJECTIVE

To validate quantitative diffusion-weighted imaging (DWI) MRI thresholds that correlate with poor outcome in comatose cardiac arrest survivors, we conducted a clinician-blinded study and prospectively obtained MRIs from comatose patients after cardiac arrest.

METHODS

Consecutive comatose post-cardiac arrest adult patients were prospectively enrolled. MRIs obtained within 7 days after arrest were evaluated. The clinical team was blinded to the DWI MRI results and followed a prescribed prognostication algorithm. Apparent diffusion coefficient (ADC) values and thresholds differentiating good and poor outcome were analyzed. Poor outcome was defined as a Glasgow Outcome Scale score of ≤2 at 6 months after arrest.

RESULTS

Ninety-seven patients were included, and 75 patients (77%) had MRIs. In 51 patients with MRI completed by postarrest day 7, the prespecified threshold of >10% of brain tissue with an ADC <650 ×10^-6 mm²/s was highly predictive for poor outcome with a sensitivity of 0.63 (95% confidence interval [CI] 0.42-0.80), a specificity of 0.96 (95% CI 0.77-0.998), and a positive predictive value (PPV) of 0.94 (95% CI 0.71-0.997). The mean whole-brain ADC was higher among patients with good outcomes. Receiver operating characteristic curve analysis showed that ADC <650 ×10^-6 mm²/s had an area under the curve of 0.79 (95% CI 0.65-0.93, p < 0.001). Quantitative DWI MRI data improved prognostication of both good and poor outcomes.

CONCLUSIONS

This prospective, clinician-blinded study validates previous research showing that an ADC <650 ×10^-6 mm²/s in >10% of brain tissue in an MRI obtained by postarrest day 7 is highly specific for poor outcome in comatose patients after cardiac arrest.

Resuscitating the Globally Ischemic Brain: TTM and Beyond

Cardiac arrest (CA) afflicts ~ 550,000 people each year in the USA. A small fraction of CA sufferers survive with a majority of these survivors emerging in a comatose state. Many CA survivors suffer devastating global brain injury with some remaining indefinitely in a comatose state. The pathogenesis of global brain injury secondary to CA is complex. Mechanisms of CA-induced brain injury include ischemia, hypoxia, cytotoxicity, inflammation, and ultimately, irreversible neuronal damage. Due to this complexity, it is critical for clinicians to have access as early as possible to quantitative metrics for diagnosing injury severity, accurately predicting outcome, and informing patient care. Current recommendations involve using multiple modalities including clinical exam, electrophysiology, brain imaging, and molecular biomarkers. This multi-faceted approach is designed to improve prognostication to avoid "self-fulfilling" prophecy and early withdrawal of life-sustaining treatments. Incorporation of emerging dynamic monitoring tools such as diffuse optical technologies may provide improved diagnosis and early prognostication to better inform treatment. Currently, targeted temperature management (TTM) is the leading treatment, with the number of patients needed to treat being ~ 6 in order to improve outcome for one patient. Future avenues of treatment, which may potentially be combined with TTM, include pharmacotherapy, perfusion/oxygenation targets, and pre/postconditioning. In this review, we provide a bench to bedside approach to delineate the pathophysiology, prognostication methods, current targeted therapies, and future directions of research surrounding hypoxic-ischemic brain injury (HIBI) secondary to CA.

Imaging for Neuroprognostication After Cardiac Arrest: Systematic Review and Meta-analysis

BACKGROUND

Predicting neurological outcome in comatose survivors of cardiac arrest relies on clinical findings, radiological and neurophysiological test results. To evaluate the predictive accuracy of brain computed tomography (CT) and magnetic resonance imaging (MRI) for prognostication of neurological outcomes after cardiac arrest.

METHODS

We searched MEDLINE (database inception to August 2018) and included all observational cohort studies or randomized controlled trials including adult (16 years or older) survivors of cardiac arrest which evaluated the diagnostic accuracy of CT or MRI for predicting neurologic outcome or mortality. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. All review stages were conducted independently by 2 reviewers, and where possible data were pooled using bivariate meta-analysis. The main outcome was to evaluate the of accuracy of CT and MRI in neuroprognostication of patients after cardiac arrest.

RESULTS

We included 44 studies that examined brain CT (n = 24) or MRI (n = 21) in 4008 (n per study, 9-398) patients. Decreased grey to white matter ratio on CT (20 studies) was useful for predicting poor neurological outcome (sensitivity 0.44, 95% CI 0.29-0.60; specificity 0.97, 95% CI 0.93-0.99; positive likelihood ratio [LR+] 13.8, 95% CI 6.9-27.7). Similarly, diffusion-weighted imaging (DWI) on MRI (16 studies; sensitivity 0.77, 95% CI 0.65-0.85; specificity 0.92, 95% CI 0.85-0.96; LR+ 9.2, 95% CI 5.2-16.4) and DWI and fluid-attenuated inversion recovery (FLAIR) MRI (4 studies, sensitivity 0.70, 95% CI 0.43-0.88; specificity 0.95, 95% CI 0.79-0.99; LR+ 13.4, 95% CI 3.5-51.2) were useful for predicting poor neurological outcomes. We found marked heterogeneity in timing of radiological examinations and neurological assessments relative to the cardiac arrest.

CONCLUSION

Decreased grey to white matter ratio on CT and DWI or DWI and FLAIR on MRI are useful adjuncts for predicting poor early neurological outcome after cardiac arrest.

Prediction of poor outcome after hypoxic-ischemic brain injury by diffusion-weighted imaging: A systematic review and meta-analysis

Accurate prediction of the neurological outcome following hypoxic–ischemic brain injury (HIBI) remains difficult. Diffusion-weighted imaging (DWI) can detect acute and subacute brain abnormalities following global cerebral hypoxia. Therefore, DWI can be used to predict the outcomes of HIBI. To this end, we searched the PubMed, EMBASE, and Cochrane Library databases for studies that examine the diagnostic accuracy of DWI in predicting HIBI outcomes in adult patients between January1995 and September 2019. Next, we conducted a comprehensive meta-analysis using the Meta-DiSc and several complementary techniques. Following the application of inclusion and exclusion criteria, a total of 28 studies were included with 98 data subsets. The overall sensitivity and specificity, with 95% confidence interval, were 0.613(0.599–0.628) and 0.958(0.947–0.967), respectively, and the area under the curve was 0.9090. Significant heterogeneity among the included studies and a threshold effect were observed (p<0.001). Different positive indices were the major sources for the heterogeneity, followed by the anatomical region examined, both of which significantly affected the prognostic accuracy. In conclusion, we demonstrated that DWI can be an instrumental modality in predicting the outcome of HIBI with good prognostic accuracy. However, the lack of clear and generally accepted positive indices limits its clinical application. Therefore, using more reliable positive indices and combining DWI with other clinical predictors may improve the diagnostic accuracy of HIBI.

The Influence of Therapeutics on Prognostication After Cardiac Arrest

PURPOSE OF REVIEW

The goal of this review is to highlight the influence of therapeutic maneuvers on neuro-prognostication measures administered to comatose survivors of cardiac arrest. We focus on the effect of sedation regimens in the setting of targeted temperature management (TTM), one of the principle interventions known to improve neurological recovery after cardiac arrest. Further, we discuss the critical need for novel markers, as well as refinement of existing markers, among patients receiving extracorporeal membrane oxygenation (ECMO) in the setting of failed conventional resuscitation, known as extracorporeal cardiopulmonary resuscitation (ECPR).

RECENT FINDINGS

Automated pupillometry may have some advantage over standard pupillary examination for prognostication following TTM, sedation, or the use of ECMO after cardiac arrest. New serum biomarkers such as Neurofilament light chain have shown good predictive abilities and need further validation in these populations. There is a high-level uncertainty in brain death declaration protocols particularly related to apnea testing and appropriate ancillary tests in patients receiving ECMO. Both sedation and TTM alone and in combination have been shown to affect prognostic markers to varying degrees. The optimal approach to analog-sedation is unknown, and requires further study. Moreover, validation of known prognostic markers, as well as brain death declaration processes in patients receiving ECMO is warranted. Data on the effects of TTM, sedation, and ECMO on biomarkers (e.g., neuron-specific enolase) and electrophysiology measures (e.g., somatosensory-evoked potentials) is sparse. The best approach may be one customized to the individual patient, a precision-medicine approach.

Cerebral Edema After Cardiopulmonary Resuscitation: A Therapeutic Target Following Cardiac Arrest?

We sought to review the role that cerebral edema plays in neurologic outcome following cardiac arrest, to understand whether cerebral edema might be an appropriate therapeutic target for neuroprotection in patients who survive cardiopulmonary resuscitation. Articles indexed in PubMed and written in English. Following cardiac arrest, cerebral edema is a cardinal feature of brain injury and is a powerful prognosticator of neurologic outcome. Like other conditions characterized by cerebral ischemia/reperfusion, neuroprotection after cardiac arrest has proven to be difficult to achieve. Neuroprotection after cardiac arrest generally has focused on protecting neurons, not the microvascular endothelium or blood-brain barrier. Limited preclinical data suggest that strategies to reduce cerebral edema may improve neurologic outcome. Ongoing research will be necessary to determine whether targeting cerebral edema will improve patient outcomes after cardiac arrest.

Prognostication via early computed tomography head in patients treated with targeted temperature management after cardiac arrest

BACKGROUND

We evaluated computed tomography head (CTH) imaging obtained prior to targeted temperature management (TTM) in patients after cardiac arrest, and its role in prognostication.

METHODS

In this retrospective cohort study in a tertiary-care hospital, 341 adults presenting with out-of-hospital cardiac arrest received a CTH prior to TTM. Associations between outcomes and neuroimaging variables were evaluated with Chi-square analysis for significant associations that yielded a composite neuroimaging score-Tennessee Early Neuroimaging Score (TENS). Univariable and multivariable logistic regression analysis including TENS as an independent variable and the four outcome dependent variables were analyzed.

RESULTS

Four of the neuroimaging variables-sulcal effacement, partial gray-white matter effacement, total gray-white matter effacement, deep nuclei effacement-had significant associations with each of the four outcome variables and yielded TENS. In multivariable logistic regression models adjusted for potential confounders, TENS was associated with poor discharge CPC (OR 2.15, 95%CI 1.16-3.98, p = .015), poor disposition (OR 2.62, 95%CI 1.37-5.02, p = .004), in-hospital mortality (OR 1.99, 95%CI 1.09-3.62, p = .024), and ICU mortality (OR 1.89, 95%CI 1.12-3.20, p = .018).

CONCLUSION

Imaging prior to TTM may help identify post-cardiac arrest patients with severe anoxic brain injury and poor outcomes.

The prognostic value of quantitative diffusion-weighted MRI after pediatric cardiopulmonary arrest

OBJECTIVES

The prognostic value of quantitative diffusion-weighted magnetic resonance imaging (DWI MRI) in predicting neurologic outcomes after pediatric cardiopulmonary arrest (CPA) has not been determined. The aim of this study was to identify a DWI MRI threshold for brain volume percent that correlates with neurologic outcome in children who remain comatose or display significant neurologic deficits immediately after resuscitation from CPA.

METHODS

This single-center retrospective study analyzed DWI MRIs of pediatric patients who remained neurologically impaired after CPA. Any MRI obtained within 2 weeks after CPA was analyzed. The apparent diffusion coefficient (ADC) value of each voxel within the brain was determined. Percentage brain volume with voxels below each ADC threshold between 300 and 1200 × 10^-6 mm²/s with a step of 50 were calculated. Area under the receiver operating characteristics curve (AUC) was used to identify optimal DWI MRI thresholds for brain volume percent most predictive of poor neurologic outcome. The primary outcome measure was neurologic outcome 6-months after CPA based on Pediatric Cerebral Performance Category (PCPC) score. Poor neurologic outcome was defined as PCPC score of 3-6, or a worsening from baseline score ≥1 if baseline PCPC score was ≥3.

RESULTS

Twenty-six patients were included in this study. The median age was 8.5 years (2.2-14) and median time from CPA to MRI was 4 days (2-7). Two ADC thresholds for brain volume percent had the largest AUC for predicting poor neurologic outcome. An ADC threshold of <600 × 10^-6 mm²/s in ≥7% of brain volume; and <650 × 10^-6 mm²/s in ≥11% of brain volume both demonstrated a specificity of 1.0 (0.76-1.0, 95% CI) and a sensitivity of 0.8 (0.44-0.96, 95% CI) for poor outcome.

CONCLUSIONS

In pediatric patients who remain comatose or have significant neurologic deficits after CPA, quantitative DWI MRI correlates with neurologic outcome. Both an ADC threshold of <600 × 10^-6 mm²/s in ≥7% of brain volume and <650 × 10^-6 mm²/s in ≥11% of brain volume are highly specific for predicting poor neurologic outcome. A prospective trial to validate these thresholds is needed.

A prediction model for good neurological outcome in successfully resuscitated out-of-hospital cardiac arrest patients

BACKGROUND

In the initial hours after out-of-hospital cardiac arrest (OHCA), it remains difficult to estimate whether the degree of post-ischemic brain damage will be compatible with long-term good neurological outcome. We aimed to construct prognostic models able to predict good neurological outcome of OHCA patients within 48 h after CCU admission using variables that are bedside available.

METHODS

Based on prospectively gathered data, a retrospective data analysis was performed on 107 successfully resuscitated OHCA patients with a presumed cardiac cause of arrest. Targeted temperature management at 33 °C was initiated at CCU admission. Prediction models for good neurological outcome (CPC1-2) at 180 days post-CA were constructed at hour 1, 12, 24 and 48 after CCU admission. Following multiple imputation, variables were selected using the elastic-net method. Each imputed dataset was divided into training and validation sets (80% and 20% of patients, respectively). Logistic regression was fitted on training sets and prediction performance was evaluated on validation sets using misclassification rates.

RESULTS

The prediction model at hour 24 predicted good neurological outcome with the lowest misclassification rate (21.5%), using a cut-off probability of 0.55 (sensitivity = 75%; specificity = 82%). This model contained sex, age, diabetes status, initial rhythm, percutaneous coronary intervention, presence of a BIS 0 value, mean BIS value and lactate as predictive variables for good neurological outcome.

DISCUSSION

This study shows that good neurological outcome after OHCA can be reasonably predicted as early as 24 h following ICU admission using parameters that are bedside available. These prediction models could identify patients who would benefit the most from intensive care.

Brain imaging in comatose survivors of cardiac arrest: Pathophysiological correlates and prognostic properties

INTRODUCTION

Hypoxic-ischemic brain injury is the main cause of death and disability of comatose patients after cardiac arrest. Early and reliable prognostication is challenging. Common prognostic tools include clinical neurological examination and electrophysiological measures. Brain imaging is well established for diagnosis of focal cerebral ischemia but has so far not found worldwide application in this patient group.

OBJECTIVE

To review the value of Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET) for early prediction of neurological outcome of comatose survivors of cardiac arrest.

METHODS

A literature search was performed to identify publications on CT, MRI or PET in comatose patients after cardiac arrest.

RESULTS

We included evidence from 51 articles, 21 on CT, 27 on MRI, 1 on CT and MRI, and 2 on PET imaging. Studies varied regarding timing of measurements, choice of determinants, and cut-off values predicting poor outcome. Most studies were small (n = 6-398) and retrospective (60%). In general, cytotoxic oedema, defined by a grey-white matter ratio <1.10, derived from CT, or MRI-diffusion weighted imaging <650 × 10^-6 mm²/s in >10% of the brain could differentiate between patients with favourable and unfavourable outcomes on a group level within 1-3 days after cardiac arrest. Advanced imaging techniques such as functional MRI or diffusion tensor imaging show promising results, but need further evaluation.

CONCLUSION

CT derived grey-white matter ratio and MRI based measures of diffusivity and connectivity hold promise to improve outcome prediction after cardiac arrest. Prospective validation studies in a multivariable approach are needed to determine the additional value for the individual patient.

Targeted Temperature Management and Multimodality Monitoring of Comatose Patients After Cardiac Arrest

Out-of-hospital cardiac arrest (CA) remains a leading cause of sudden morbidity and mortality; however, outcomes have continued to improve in the era of targeted temperature management (TTM). In this review, we highlight the clinical use of TTM, and provide an updated summary of multimodality monitoring possible in a modern ICU. TTM is neuroprotective for survivors of CA by inhibiting multiple pathophysiologic processes caused by anoxic brain injury, with a final common pathway of neuronal death. Current guidelines recommend the use of TTM for out-of-hospital CA survivors who present with a shockable rhythm. Further studies are being completed to determine the optimal timing, depth and duration of hypothermia to optimize patient outcomes. Although a multidisciplinary approach is necessary in the CA population, neurologists and neurointensivists are central in selecting TTM candidates and guiding patient care and prognostic evaluation. Established prognostic tools include clinal exam, SSEP, EEG and MR imaging, while functional MRI and invasive monitoring is not validated to improve outcomes in CA or aid in prognosis. We recommend that an evidence-based TTM and prognostication algorithm be locally implemented, based on each institution's resources and limitations. Given the high incidence of CA and difficulty in predicting outcomes, further study is urgently needed to determine the utility of more recent multimodality devices and studies.

Glibenclamide Prevents Water Diffusion Abnormality in the Brain After Cardiac Arrest in Rats

BACKGROUND

Glibenclamide (GBC) improves neurological outcome after cardiac arrest (CA) in rats. In this study, we sought to elucidate the mechanism responsible for the neuroprotective effects of GBC by using a high-field MRI system.

METHODS

Male Sprague-Dawley rats were subjected to 10-min asphyxial CA followed by cardiopulmonary resuscitation (CPR). Diffusion-weighted imaging (DWI) as well as conventional T2-weighted imaging was conducted prior to CA and at 24, 48, and 72 h after resuscitation. Afterward, histological examination was performed.

RESULTS

Twelve rats were randomized to receive GBC (n = 6) or vehicle (n = 6) at 15 min after return of spontaneous circulation, while four rats were set as sham control. Rats that underwent CA/CPR and received vehicle exhibited distinct neurological deficit, which was alleviated by GBC treatment. Marked water diffusion abnormality as demonstrated by hyperintense DWI in vulnerable regions of the brain was detected after CA/CPR, with the most prominent hyperintense DWI observed in the hippocampal CA1 region at 72 h. Consistently, histological examination revealed neuronal swelling, dendritic injury, and activation of astrocytes and microglia in the hippocampal CA1 region in vehicle-treated rats. Correlation analysis revealed that the ADC values in the hippocampus were significantly correlated with the histological findings (all p < 0.05).

CONCLUSION

These results suggest that the neuroprotective effects of GBC after CA was exerted, as least in part, through prevention of water diffusion abnormality, namely brain edema.

Prognostication after cardiac arrest

Hypoxic-ischaemic brain injury (HIBI) is the main cause of death in patients who are comatose after resuscitation from cardiac arrest. A poor neurological outcome-defined as death from neurological cause, persistent vegetative state, or severe neurological disability-can be predicted in these patients by assessing the severity of HIBI. The most commonly used indicators of severe HIBI include bilateral absence of corneal and pupillary reflexes, bilateral absence of N₂O waves of short-latency somatosensory evoked potentials, high blood concentrations of neuron specific enolase, unfavourable patterns on electroencephalogram, and signs of diffuse HIBI on computed tomography or magnetic resonance imaging of the brain. Current guidelines recommend performing prognostication no earlier than 72 h after return of spontaneous circulation in all comatose patients with an absent or extensor motor response to pain, after having excluded confounders such as residual sedation that may interfere with clinical examination. A multimodal approach combining multiple prognostication tests is recommended so that the risk of a falsely pessimistic prediction is minimised.

Acute brain lesions on magnetic resonance imaging in relation to neurological outcome after cardiac arrest

BACKGROUND

Magnetic resonance imaging (MRI) of the brain including diffusion-weighted imaging (DWI) is reported to have high prognostic accuracy in unconscious post-cardiac arrest (CA) patients. We documented acute MRI findings in the brain in both conscious and unconscious post-CA patients treated with target temperature management (TTM) at 32-34°C for 24 h as well as the relation to patients' neurological outcome after 6 months.

METHODS

A prospective observational study with MRI was performed regardless of the level of consciousness in post-CA patients treated with TTM. Neurological outcome was assessed using the Cerebral Performance Categories scale and dichotomized into good and poor outcome.

RESULTS

Forty-six patients underwent MRI at 3-5 days post-CA. Patients with good outcome had minor, mainly frontal and parietal, lesions. Acute hypoxic/ischemic lesions on MRI including DWI were more common in patients with poor outcome (P = 0.007). These lesions affected mostly gray matter (deep or cortical), with or without involvement of the underlying white matter. Lesions in the occipital and temporal lobes, deep gray matter and cerebellum showed strongest associations with poor outcome. Decreased apparent diffusion coefficient, was more common in patients with poor outcome.

CONCLUSIONS

Extensive acute hypoxic/ischemic MRI lesions in the cortical regions, deep gray matter and cerebellum detected by visual analysis as well as low apparent diffusion coefficient values from quantitative measurements were associated with poor outcome. Patients with good outcome had minor hypoxic/ischemic changes, mainly in the frontal and parietal lobes.

Mean arterial pressure of 65 mm Hg versus 85-100 mm Hg in comatose survivors after cardiac arrest: Rationale and study design of the Neuroprotect post-cardiac arrest trial

BACKGROUND

Post-cardiac arrest (CA) patients admitted to the intensive care unit (ICU) have a poor prognosis, with estimated survival rates of around 30%-50%. On admission, these patients have a large cerebral penumbra at risk for additional damage in case of suboptimal brain oxygenation during their stay in the ICU. The aim of the Neuroprotect post-CA trial is to investigate whether forcing mean arterial blood pressure (MAP) and mixed venous oxygen saturation (SVO₂) in a specific range (MAP 85-100 mm Hg, SVO₂ 65%-75%) with additional pharmacological support (goal-directed hemodynamic optimization) may better salvage the penumbra, reduce cerebral ischemia, and improve functional outcome when compared with current standard of care (MAP 65 mm Hg).

DESIGN

The Neuroprotect post-CA trial (NCT02541591) is a multicenter, randomized, parallel-group, open-label, assessor-blinded, monitored, and investigator-driven clinical trial. The trial will be conducted in 2 tertiary care hospitals in Belgium (UZ Leuven and ZOL-Genk). A total of 112 eligible patients will be randomly assigned in a 1:1 ratio to goal-directed hemodynamic optimization or standard care strategy by an interactive voice response system. Patients will be stratified according to the presence of an initial shockable rhythm. Adult patients (≥18 years) resuscitated from out-of-hospital CA of a presumed cardiac cause who are unconscious upon hospital admission are eligible for inclusion. Patients can be included irrespective of their presenting heart rhythm but need to have a sustained return of spontaneous circulation. Trial interventions will take 36 hours starting from ICU admission. The primary outcome is the extent of cerebral ischemia as quantified by the apparent diffusion coefficient on diffusion-weighted magnetic resonance imaging to be performed at day 4-5 post-CA. Secondary outcomes include surrogate biomarkers of brain injury (neuron specific enolase) at day 1-5, neuropsychological and functional testing at hospital discharge, a Short Form-36 health questionnaire at 180 days, and outcome as assessed with cerebral performance category scores at ICU discharge and at 180 days.

CONCLUSIONS

The Neuroprotect post-CA trial will investigate whether a more aggressive hemodynamic strategy to obtain a MAP 85-100 mm Hg and SVO₂ 65%-75% reduces brain ischemia and improves outcome when compared with standard treatment (MAP 65 mm Hg) in comatose post-CA survivors.

Post-anoxic quantitative MRI changes may predict emergence from coma and functional outcomes at discharge

BACKGROUND

Traditional predictors of neurological prognosis after cardiac arrest are unreliable after targeted temperature management. Absence of pupillary reflexes remains a reliable predictor of poor outcome. Diffusion-weighted imaging has emerged as a potential predictor of recovery, and here we compare imaging characteristics to pupillary exam.

METHODS

We identified 69 patients who had MRIs within seven days of arrest and used a semi-automated algorithm to perform quantitative volumetric analysis of apparent diffusion coefficient (ADC) sequences at various thresholds. Area under receiver operating characteristic curves (ROC-AUC) were estimated to compare predictive values of quantitative MRI with pupillary exam at days 3, 5 and 7 post-arrest, for persistence of coma and functional outcomes at discharge. Cerebral Performance Category scores of 3-4 were considered poor outcome.

RESULTS

Excluding patients where life support was withdrawn, ≥2.8% diffusion restriction of the entire brain at an ADC of ≤650×10^-6m²/s was 100% specific and 68% sensitive for failure to wake up from coma before discharge. The ROC-AUC of ADC changes at ≤450×10^-6mm²/s and ≤650×10^-6mm²/s were significantly superior in predicting failure to wake up from coma compared to bilateral absence of pupillary reflexes. Among survivors, >0.01% of diffusion restriction of the entire brain at an ADC ≤450×10^-6m²/s was 100% specific and 46% sensitive for poor functional outcome at discharge. The ROC curve predicting poor functional outcome at ADC ≤450×10^-6mm²/s had an AUC of 0.737 (0.574-0.899, p=0.04).

CONCLUSION

Post-anoxic diffusion changes using quantitative brain MRI may aid in predicting persistent coma and poor functional outcomes at hospital discharge.

Neurological prognostication of outcome in patients in coma after cardiac arrest

Management of coma after cardiac arrest has improved during the past decade, allowing an increasing proportion of patients to survive, thus prognostication has become an integral part of post-resuscitation care. Neurologists are increasingly confronted with raised expectations of next of kin and the necessity to provide early predictions of long-term prognosis. During the past decade, as technology and clinical evidence have evolved, post-cardiac arrest prognostication has moved towards a multimodal paradigm combining clinical examination with additional methods, consisting of electrophysiology, blood biomarkers, and brain imaging, to optimise prognostic accuracy. Prognostication should never be based on a single indicator; although some variables have very low false positive rates for poor outcome, multimodal assessment provides resassurance about the reliability of a prognostic estimate by offering concordant evidence.