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

Prognostic value of grey-white matter ratio obtained within two hours after return of spontaneous circulation in out-of-hospital cardiac arrest survivors: A multicenter, observational study

Background

Grey-white matter ratio (GWR) measured by head computed tomography (CT) scan is known as a neurological prognostication tool for out-of-hospital cardiac arrest (OHCA) survivors. The prognostic value of GWR obtained early (within two hours after return of spontaneous circulation [ROSC]) remains a matter of debate.

Methods

We conducted a multicenter, retrospective, observational study at five hospitals. We included adult OHCA survivors who underwent head CT within two hours following ROSC. GWR values were measured using head CT. Average GWR values were calculated by the mean of the GWR-basal ganglia and GWR-Cerebrum. We divided the patients into poor or favorable neurological outcome groups defined by Glasgow-Pittsburgh Cerebral Performance Category scores. The predictive accuracy of GWR performance was assessed using the area under the curve (AUC). The sensitivities and specificities for predicting poor outcome were examined.

Results

Of 377 eligible patients, 281 (74.5%) showed poor neurological outcomes at one month after ROSC. Average GWR values of the poor neurological outcome group were significantly lower than those of the favorable neurological outcome. The average GWR value to predict neurological outcome with Youden index was 1.24 with AUC of 0.799. When average GWR values were 1.15 or lower, poor neurological outcomes could be predicted with 100% specificity.

Conclusions

GWR values measured by head CT scans early (within two hours after ROSC) demonstrated moderate predictive performance for overall ROSC patients. When limited to the patients with GWR values of 1.15 or lower, poor neurological outcomes could be predicted with high specificity.

Quantitative and Radiological Assessment of Post-cardiac-Arrest Comatose Patients with Diffusion-Weighted Magnetic Resonance Imaging

BACKGROUND

Although magnetic resonance imaging, particularly diffusion-weighted imaging, has increasingly been used as part of a multimodal approach to prognostication in patients who are comatose after cardiac arrest, the performance of quantitative analysis of apparent diffusion coefficient (ADC) maps, as compared to standard radiologist impression, has not been well characterized. This retrospective study evaluated quantitative ADC analysis to the identification of anoxic brain injury by diffusion abnormalities on standard clinical magnetic resonance imaging reports.

METHODS

The cohort included 204 previously described comatose patients after cardiac arrest. Clinical outcome was assessed by (1) 3-6 month post-cardiac-arrest cerebral performance category and (2) coma recovery to following commands. Radiological evaluation was obtained from clinical reports and characterized as diffuse, cortex only, deep gray matter structures only, or no anoxic injury. Quantitative analyses of ADC maps were obtained in specific regions of interest (ROIs), whole cortex, and whole brain. A subgroup analysis of 172 was performed after eliminating images with artifacts and preexisting lesions.

RESULTS

Radiological assessment outperformed quantitative assessment over all evaluated regions (area under the curve [AUC] 0.80 for radiological interpretation and 0.70 for the occipital region, the best performing ROI, p = 0.011); agreement was substantial for all regions. Radiological assessment still outperformed quantitative analysis in the subgroup analysis, though by smaller margins and with substantial to near-perfect agreement. When assessing for coma recovery only, the difference was no longer significant (AUC 0.83 vs. 0.81 for the occipital region, p = 0.70).

CONCLUSIONS

Although quantitative analysis eliminates interrater differences in the interpretation of abnormal diffusion imaging and avoids bias from other prediction modalities, clinical radiologist interpretation has a higher predictive value for outcome. Agreement between radiological and quantitative analysis improved when using high-quality scans and when assessing for coma recovery using following commands. Quantitative assessment may thus be more subject to variability in both clinical management and scan quality than radiological assessment.

Performance of the MRI lesion pattern score in predicting neurological outcome after out of hospital cardiac arrest: a retrospective cohort analysis

BACKGROUND

Despite advances in resuscitation practice, patient survival following cardiac arrest remains poor. The utilization of MRI in neurological outcome prognostication post-cardiac arrest is growing and various classifications has been proposed; however a consensus has yet to be established. MRI, though valuable, is resource-intensive, time-consuming, costly, and not universally available. This study aims to validate a MRI lesion pattern score in a cohort of out of hospital cardiac arrest patients at a tertiary referral hospital in Switzerland.

METHODS

This cohort study spanned twelve months from February 2021 to January 2022, encompassing all unconscious patients aged ≥ 18 years who experienced out-of-hospital cardiac arrest of any cause and were admitted to the intensive care unit (ICU) at Inselspital, University Hospital Bern, Switzerland. We included patients who underwent the neuroprognostication process, assessing the performance and validation of a MRI scoring system.

RESULTS

Over the twelve-month period, 137 patients were admitted to the ICU, with 52 entering the neuroprognostication process and 47 undergoing MRI analysis. Among the 35 MRIs indicating severe hypoxic brain injury, 33 patients (94%) experienced an unfavourable outcome (UO), while ten (83%) of the twelve patients with no or minimal MRI lesions had a favourable outcome. This yielded a sensitivity of 0.94 and specificity of 0.83 for predicting UO with the proposed MRI scoring system. The positive and negative likelihood ratios were 5.53 and 0.07, respectively, resulting in an accuracy of 91.49%.

CONCLUSION

We demonstrated the effectiveness of the MLP scoring scheme in predicting neurological outcome in patients following cardiac arrest. However, to ensure a comprehensive neuroprognostication, MRI results need to be combined with other assessments. While neuroimaging is a promising objective tool for neuroprognostication, given the absence of sedation-related confounders-compared to electroencephalogram (EEG) and clinical examination-the current lack of a validated scoring system necessitates further studies. Incorporating standardized MRI techniques and grading systems is crucial for advancing the reliability of neuroimaging for neuroprognostication.

TRIAL REGISTRATION

Registry of all Projects in Switzerland (RAPS) 2020-01761.

Standardised and automated assessment of head computed tomography reliably predicts poor functional outcome after cardiac arrest: a prospective multicentre study

PURPOSE

Application of standardised and automated assessments of head computed tomography (CT) for neuroprognostication after out-of-hospital cardiac arrest.

METHODS

Prospective, international, multicentre, observational study within the Targeted Hypothermia versus Targeted Normothermia after out-of-hospital cardiac arrest (TTM2) trial. Routine CTs from adult unconscious patients obtained > 48 h ≤ 7 days post-arrest were assessed qualitatively and quantitatively by seven international raters blinded to clinical information using a pre-published protocol. Grey-white-matter ratio (GWR) was calculated from four (GWR-4) and eight (GWR-8) regions of interest manually placed at the basal ganglia level. Additionally, GWR was obtained using an automated atlas-based approach. Prognostic accuracies for prediction of poor functional outcome (modified Rankin Scale 4-6) for the qualitative assessment and for the pre-defined GWR cutoff < 1.10 were calculated.

RESULTS

140 unconscious patients were included; median age was 68 years (interquartile range [IQR] 59-76), 76% were male, and 75% had poor outcome. Standardised qualitative assessment and all GWR models predicted poor outcome with 100% specificity (95% confidence interval [CI] 90-100). Sensitivity in median was 37% for the standardised qualitative assessment, 39% for GWR-8, 30% for GWR-4 and 41% for automated GWR. GWR-8 was superior to GWR-4 regarding prognostic accuracies, intra- and interrater agreement. Overall prognostic accuracy for automated GWR (area under the curve [AUC] 0.84, 95% CI 0.77-0.91) did not significantly differ from manually obtained GWR.

CONCLUSION

Standardised qualitative and quantitative assessments of CT are reliable and feasible methods to predict poor functional outcome after cardiac arrest. Automated GWR has the potential to make CT quantification for neuroprognostication accessible to all centres treating cardiac arrest patients.

Simple approach to quantify hypoxic-ischemic brain injury severity from computed tomography imaging files after cardiac arrest

BACKGROUND

Grey-white ratio (GWR) can estimate severity of cytotoxic cerebral edema secondary to hypoxic-ischemic brain injury after cardiac arrest and predict progression to death by neurologic criteria (DNC). Current approaches to calculating GWR are not standardized and have variable interrater reliability. We tested if measures of variance of brain density on early computed tomographic (CT) imaging after cardiac arrest could predict DNC.

METHODS

We performed a retrospective cohort study, identifying post-arrest patients treated between 2011 and 2020 at our single center. We extracted demographic data from our registry and Digital Imaging and Communication in Medicine (DICOM) files for each patient's first brain CT. We analyzed slices 15-20 of each DICOM, corresponding to the level of the basal ganglia while accommodating differences in patient anatomy. We extracted pixel arrays and converted the radiodensities to Hounsfield units (HU). To focus on brain tissue densities, we excluded HU > 60 and < 10. We calculated the variance of each patient's HU distribution and the difference between the means of a two-group Gaussian finite mixture model. We compared these novel metrics to existing measures of cerebral edema, then randomly divided our data into 80% training and 20% test sets and used logistic regression to predict DNC.

RESULTS

Of 1,133 included subjects, 457 (40%) were female, mean (standard deviation) age was 58 (16) years, and 115 (10%) progressed to DNC. CTs were obtained a median [interquartile range] of 4.2 [2.8-5.7] hours post-arrest. Our novel measures correlated weakly with GWR. HU variance, but not difference between mixture model means, differed significantly between subjects with and without sulcal or cistern effacement. GWR outperformed our novel measures in predicting progression to DNC with an area under the receiver operating characteristic curve (AUC) of 0.82, compared to HU variance (AUC = 0.73) and the difference between mixture model means (AUC = 0.56).

CONCLUSION

There are differences in the distribution of HU on post-arrest CT in patients with qualitative measures of cerebral edema. Current methods to quantify cerebral edema outperform simple measures of attenuation variance on early brain CT. Further analyses could investigate if these measures of variance, or other distributional characteristics of brain density, have improved predictive performance on brain CTs obtained later in the clinical course or derived from discrete regions of anatomical interest.

Associations between clinical characteristics of cardiac arrest and early CT head findings of hypoxic ischaemic brain injury following out-of-hospital cardiac arrest

BACKGROUND/OBJECTIVE

Post-cardiac arrest patients are vulnerable to hypoxic-ischaemic brain injury (HIBI), but HIBI may not be identified until computed tomography (CT) scan of the brain is obtained post-resuscitation and stabilization. We aimed to evaluate the association of clinical arrest characteristics with early CT findings of HIBI to identify those at the highest risk for HIBI.

METHODS

This is a retrospective analysis of out-of-hospital cardiac arrest (OHCA) patients who underwent whole-body imaging. Head CT reports were analyzed with an emphasis on findings suggestive of HIBI; HIBI was present if any of the following were noted on the neuroradiologist read: global cerebral oedema, sulcal effacement, blurred grey-white junction, and ventricular compression. The primary exposure was duration of cardiac arrest. Secondary exposures included age, cardiac vs noncardiac etiology, and witnessed vs unwitnessed arrest. The primary outcome was CT findings of HIBI.

RESULTS

A total of 180 patients (average age 54 years, 32% female, 71% White, 53% witnessed arrest, 32% cardiac etiology of arrest, mean CPR duration of 15 ± 10 minutes) were included in this analysis. CT findings of HIBI were seen in 47 (48.3%) patients. Multivariate logistic regression demonstrated a significant association between CPR duration and HIBI (adjusted OR = 1.1, 95% CI 1.01-1.11, p < 0.01).

CONCLUSION

Signs of HIBI are commonly seen on CT head within 6 hours of OHCA, occurring in approximately half of patients, and are associated with CPR duration. Determining risk factors for abnormal CT findings can help clinically identify patients at higher risk for HIBI and target interventions appropriately.

Neurophysiology State Dynamics Underlying Acute Neurologic Recovery After Cardiac Arrest

BACKGROUND AND OBJECTIVES

Epileptiform activity and burst suppression are neurophysiology signatures reflective of severe brain injury after cardiac arrest. We aimed to delineate the evolution of coma neurophysiology feature ensembles associated with recovery from coma after cardiac arrest.

METHODS

Adults in acute coma after cardiac arrest were included in a retrospective database involving 7 hospitals. The combination of 3 quantitative EEG features (burst suppression ratio [BSup], spike frequency [SpF], and Shannon entropy [En]) was used to define 5 distinct neurophysiology states: epileptiform high entropy (EHE: SpF ≥4 per minute and En ≥5); epileptiform low entropy (ELE: SpF ≥4 per minute and <5 En); nonepileptiform high entropy (NEHE: SpF <4 per minute and ≥5 En); nonepileptiform low entropy (NELE: SpF <4 per minute and <5 En), and burst suppression (BSup ≥50% and SpF <4 per minute). State transitions were measured at consecutive 6-hour blocks between 6 and 84 hours after return of spontaneous circulation. Good neurologic outcome was defined as best cerebral performance category 1-2 at 3-6 months.

RESULTS

One thousand thirty-eight individuals were included (50,224 hours of EEG), and 373 (36%) had good outcome. Individuals with EHE state had a 29% rate of good outcome, while those with ELE had 11%. Transitions out of an EHE or BSup state to an NEHE state were associated with good outcome (45% and 20%, respectively). No individuals with ELE state lasting >15 hours had good recovery.

DISCUSSION

Transition to high entropy states is associated with an increased likelihood of good outcome despite preceding epileptiform or burst suppression states. High entropy may reflect mechanisms of resilience to hypoxic-ischemic brain injury.

Clinical presentation, diagnosis, treatment, and outcome in 8 dogs and 2 cats with global hypoxic-ischemic brain injury (2010-2022)

BACKGROUND

Global hypoxic-ischemic brain injury (GHIBI) results in variable degrees of neurological dysfunction. Limited data exists to guide prognostication on likelihood of functional recovery.

HYPOTHESIS

Prolonged duration of hypoxic-ischemic insult and absence of neurological improvement in the first 72 hours are negative prognostic indicators.

ANIMALS

Ten clinical cases with GHIBI.

METHODS

Retrospective case series describing 8 dogs and 2 cats with GHIBI, including clinical signs, treatment, and outcome.

RESULTS

Six dogs and 2 cats experienced cardiopulmonary arrest or anesthetic complication in a veterinary hospital and were promptly resuscitated. Seven showed progressive neurological improvement within 72 hours of the hypoxic-ischemic insult. Four fully recovered and 3 had residual neurological deficits. One dog presented comatose after resuscitation at the primary care practice. Magnetic resonance imaging confirmed diffuse cerebral cortical swelling and severe brainstem compression and the dog was euthanized. Two dogs suffered out-of-hospital cardiopulmonary arrest, secondary to a road traffic accident in 1 and laryngeal obstruction in the other. The first dog was euthanized after MRI that identified diffuse cerebral cortical swelling with severe brainstem compression. In the other dog, spontaneous circulation was recovered after 22 minutes of cardiopulmonary resuscitation. However, the dog remained blind, disorientated, and ambulatory tetraparetic with vestibular ataxia and was euthanized 58 days after presentation. Histopathological examination of the brain confirmed severe diffuse cerebral and cerebellar cortical necrosis.

CONCLUSIONS AND CLINICAL IMPORTANCE

Duration of hypoxic-ischemic insult, diffuse brainstem involvement, MRI features, and rate of neurological recovery could provide indications of the likelihood of functional recovery after GHIBI.

Factors Associated with Early Withdrawal of Life-Sustaining Treatments After Out-of-Hospital Cardiac Arrest: A Subanalysis of a Randomized Trial of Prehospital Therapeutic Hypothermia

BACKGROUND

The objective of this study is to describe incidence and factors associated with early withdrawal of life-sustaining therapies based on presumed poor neurologic prognosis (WLST-N) and practices around multimodal prognostication after out-of-hospital cardiac arrest (OHCA).

METHODS

We performed a subanalysis of a randomized controlled trial assessing prehospital therapeutic hypothermia in adult patients admitted to nine hospitals in King County with nontraumatic OHCA between 2007 and 2012. Patients who underwent tracheal intubation and were unconscious following return of spontaneous circulation were included. Our outcomes were (1) incidence of early WLST-N (WLST-N within < 72 h from return of spontaneous circulation), (2) factors associated with early WLST-N compared with patients who remained comatose at 72 h without WLST-N, (3) institutional variation in early WLST-N, (4) use of multimodal prognostication, and (5) use of sedative medications in patients with early WLST-N. Analysis included descriptive statistics and multivariable logistic regression.

RESULTS

We included 1,040 patients (mean age was 65 years, 37% were female, 41% were White, and 44% presented with arrest due to ventricular fibrillation) admitted to nine hospitals. Early WLST-N accounted for 24% (n = 154) of patient deaths and occurred in half (51%) of patients with WLST-N. Factors associated with early WLST-N in multivariate regressions were older age (odds ratio [OR] 1.02, 95% confidence interval [CI]: 1.01-1.03), preexisting do-not-attempt-resuscitation orders (OR 4.67, 95% CI: 1.55-14.01), bilateral absent pupillary reflexes (OR 2.4, 95% CI: 1.42-4.10), and lack of neurological consultation (OR 2.60, 95% CI: 1.52-4.46). The proportion of patients with early WLST-N among all OHCA admissions ranged from 19-60% between institutions. A head computed tomography scan was obtained in 54% (n = 84) of patients with early WLST-N; 22% (n = 34) and 5% (n = 8) underwent ≥ 1 and ≥ 2 additional prognostic tests, respectively. Prognostic tests were more frequently performed when neurological consultation occurred. Most patients received sedating medications (90%) within 24 h before early WLST-N; the median time from last sedation to early WLST-N was 4.2 h (interquartile range 0.4-15).

CONCLUSIONS

Nearly one quarter of deaths after OHCA were due to early WLST-N. The presence of concerning neurological examination findings appeared to impact early WLST-N decisions, even though these are not fully reliable in this time frame. Lack of neurological consultation was associated with early WLST-N and resulted in underuse of guideline-concordant multimodal prognostication. Sedating medications were often coadministered prior to early WLST-N and may have further confounded the neurological examination. Standardizing prognostication, restricting early WLST-N, and a multidisciplinary approach including neurological consultation might improve outcomes after OHCA.

Association between the extent of diffusion restriction on brain diffusion-weighted imaging and neurological outcomes after an out-of-hospital cardiac arrest

BACKGROUND

This study evaluated the association between the extent of diffusion restriction on brain diffusion-weighted imaging (DWI) and neurological outcomes in patients who underwent targeted temperature management (TTM) after an out-of-hospital cardiac arrest (OHCA).

METHODS

Patients who underwent brain magnetic resonance imaging within 10 days of OHCA between 2012 and 2021 were analysed. The extent of diffusion restriction was described according to the modified DWI Alberta Stroke Program Early Computed Tomography Score (DWI-ASPECTS). The 35 predefined brain regions were assigned a score if diffuse signal changes were concordantly present in DWI scans and apparent diffusion coefficient maps. The primary outcome was an unfavourable neurological outcome at 6 months. The sensitivity, specificity, and receiver operating characteristic (ROC) curves for the measured parameters were analysed. Cut-off values were determined to predict the primary outcome. The predictive cut-off DWI-ASPECTS was internally validated using five-fold cross-validation.

RESULTS

Of the 301 patients, 108 (35.9%) had 6-month favourable neurological outcomes. Patients with unfavourable outcomes had higher whole-brain DWI-ASPECTS (median, 31 [26-33] vs. 0 [0-1], P < 0.001) than those with favourable outcomes. The area under the ROC curve (AUROC) of whole-brain DWI-ASPECTS was 0.957 (95% confidence interval [CI] 0.928-0.977). A cut-off value of ≥8 for unfavourable neurological outcomes had specificity and sensitivity of 100% (95% CI 96.6-100) and 89.6% (95% CI 84.4-93.6), respectively. The mean AUROC was 0.956.

CONCLUSION

More extensive diffusion restriction on DWI-ASPECTS in patients with OHCA who underwent TTM was associated with 6-month unfavourable neurological outcomes. Running title: Diffusion restriction and neurological outcomes after cardiac arrest.

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.

Brain injury markers in blood predict signs of hypoxic ischaemic encephalopathy on head computed tomography after cardiac arrest

BACKGROUND/AIM

Signs of hypoxic ischaemic encephalopathy (HIE) on head computed tomography (CT) predicts poor neurological outcome after cardiac arrest. We explore whether levels of brain injury markers in blood could predict the likelihood of HIE on CT.

METHODS

Retrospective analysis of CT performed at 24-168 h post cardiac arrest on clinical indication within the Target Temperature Management after out-of-hospital cardiac arrest-trial. Biomarkers prospectively collected at 24- and 48 h post-arrest were analysed for neuron specific enolase (NSE), neurofilament light (NFL), total-tau and glial fibrillary acidic protein (GFAP). HIE was assessed through visual evaluation and quantitative grey-white-matter ratio (GWR) was retrospectively calculated on Swedish subjects with original images available.

RESULTS

In total, 95 patients were included. The performance to predict HIE on CT (performed at IQR 73-116 h) at 48 h was similar for all biomarkers, assessed as area under the receiving operating characteristic curve (AUC) NSE 0.82 (0.71-0.94), NFL 0.79 (0.67-0.91), total-tau 0.84 (0.74-0.95), GFAP 0.79 (0.67-0.90). The predictive performance of biomarker levels at 24 h was AUC 0.72-0.81. At 48 h biomarker levels below Youden Index accurately excluded HIE in 77.3-91.7% (negative predictive value) and levels above Youden Index correctly predicted HIE in 73.3-83.7% (positive predictive value). NSE cut-off at 48 h was 48 ng/ml. Elevated biomarker levels irrespective of timepoint significantly correlated with lower GWR.

CONCLUSION

Biomarker levels can assess the likelihood of a patient presenting with HIE on CT and could be used to select suitable patients for CT-examination during neurological prognostication in unconscious cardiac arrest patients.

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.

Prognostic accuracy of head computed tomography for prediction of functional outcome after out-of-hospital cardiac arrest: Rationale and design of the prospective TTM2-CT-substudy

Background

Head computed tomography (CT) is a guideline recommended method to predict functional outcome after cardiac arrest (CA), but standardized criteria for evaluation are lacking. To date, no prospective trial has systematically validated methods for diagnosing hypoxic-ischaemic encephalopathy (HIE) on CT after CA. We present a protocol for validation of pre-specified radiological criteria for assessment of HIE on CT for neuroprognostication after CA.

Methods/design

This is a prospective observational international multicentre substudy of the Targeted Hypothermia versus Targeted Normothermia after out-of-hospital cardiac arrest (TTM2) trial. Patients still unconscious 48 hours post-arrest at 13 participating hospitals were routinely examined with CT. Original images will be evaluated by examiners blinded to clinical data using a standardized protocol. Qualitative assessment will include evaluation of absence/presence of "severe HIE". Radiodensities will be quantified in pre-specified regions of interest for calculation of grey-white matter ratios (GWR) at the basal ganglia level. Functional outcome will be dichotomized into good (modified Rankin Scale 0-3) and poor (modified Rankin Scale 4-6) at six months post-arrest. Prognostic accuracies for good and poor outcome will be presented as sensitivities and specificities with 95% confidence intervals (using pre-specified cut-offs for quantitative analysis), descriptive statistics (Area Under the Receiver Operating Characteristics Curve), inter- and intra-rater reliabilities according to STARD guidelines.

Conclusions

The results from this prospective trial will validate a standardized approach to radiological evaluations of HIE on CT for prediction of functional outcome in comatose CA patients.The TTM2 trial and the TTM2 CT substudy are registered at ClinicalTrials.gov NCT02908308 and NCT03913065.

Comparison of intracranial pressure changes in out-of-hospital cardiac arrest patients with and without malignant blood-brain barrier disruption

OBJECTIVE

In the present study, intracranial pressure (ICP) changes were investigated in out-ofhospital cardiac arrest (OHCA) patients with and without malignant blood-brain barrier (BBB) disruption who underwent target temperature management.

METHODS

This prospective, single-center, observational study was conducted from June 2019 to December 2021. ICP and albumin quotient values were measured on days 1, 2, 3, and 4 of hospitalization. Malignant BBB disruption was defined as the sum of scores for the degree of BBB disruption ≥9 on days 1 to 4.

RESULTS

ICP in OHCA patients without malignant BBB disruption on days 1, 2, 3, and 4 of hospitalization was 9.58±0.53, 12.32±0.65, 14.39±0.76, and 13.88±0.87 mmHg, respectively, and in OHCA patients with malignant BBB disruption 13.65±0.74, 15.72±0.67, 16.10±0.92, and 15.22±0.87 mmHg, respectively (P<0.001, P<0.001, P=0.150, and P=0.280, respectively). The P-values of changes in ICP between days 1 and 2, days 2 and 3, and days 3 and 4 of hospitalization in OHCA patients without malignant BBB disruption were P<0.001, P=0.001, and P=0.540, respectively, and in OHCA patients with malignant BBB disruption were P=0.002, P=0.550, and P=0.100, respectively.

CONCLUSION

Among OHCA patients treated with target temperature management, ICP was higher on days 1 and 2 of hospitalization and an increase in ICP occurred earlier with malignant BBB disruption than without malignant BBB disruption.

MRI markers of brain network integrity relate to neurological outcome in postanoxic coma

AIM

Current multimodal approaches leave approximately half of the comatose patients after cardiac arrest with an indeterminate prognosis. Here we investigated whether early MRI markers of brain network integrity can distinguish between comatose patients with a good versus poor neurological outcome six months later.

METHODS

We performed a prospective cohort study in 48 patients after cardiac arrest submitted in a comatose state to the Intensive Care Unit of two Dutch hospitals. MRI was performed at three days after cardiac arrest, including resting state functional MRI and diffusion-tensor imaging (DTI). Resting state fMRI was used to quantify functional connectivity within ten resting-state networks, and DTI to assess mean diffusivity (MD) in these same networks. We contrasted two groups of patients, those with good (n = 29, cerebral performance category 1-2) versus poor (n = 19, cerebral performance category 3-5) outcome at six months. Mutual associations between functional connectivity, MD, and clinical outcome were studied.

RESULTS

Patients with good outcome show higher within-network functional connectivity (fMRI) and higher MD (DTI) than patients with poor outcome across 8/10 networks, most prominent in the default mode network, salience network, and visual network. While the anatomical distribution of outcome-related changes was similar for functional connectivity and MD, the pattern of inter-individual differences was very different: functional connectivity showed larger inter-individual variability in good versus poor outcome, while the opposite was observed for MD. Exploratory analyses suggested that it is possible to define network-specific cut-off values that could help in outcome prediction: (1) high functional connectivity and high MD, associated with good outcome; (2) low functional connectivity and low MD, associated with poor outcome; (3) low functional connectivity and high MD, associated with uncertain outcome.

DISCUSSION

Resting-state functional connectivity and mean diffusivity-three days after cardiac arrest are strongly associated with neurological recovery-six months later in a complementary fashion. The combination of fMRI and MD holds potential to improve prediction of outcome.

A pilot study of methods for prediction of poor outcome by head computed tomography after cardiac arrest

INTRODUCTION

In Sweden, head computed tomography (CT) is commonly used for prediction of neurological outcome after cardiac arrest, as recommended by guidelines. We compare the prognostic ability and interrater variability of routine and novel CT methods for prediction of poor outcome.

METHODS

Retrospective study including patients from Swedish sites within the Target Temperature Management after out-of-hospital cardiac arrest trial examined with CT. Original images were assessed by two independent radiologists blinded from clinical data with eye-balling without pre-specified criteria, and with a semi-quantitative assessment. Grey-white-matter ratios (GWR) were quantified using models with 4-20 manually placed regions of interest. Prognostic abilities and interrater variability were calculated for prediction of poor outcome (modified Rankin Scale 4-6 at six months) for early (<24h) and late (≥24h) examinations.

RESULTS

68/106 (64%) of included patients were examined <24h post-arrest. Eye-balling predicted poor outcome with 89-100% specificity and 15-78% sensitivity. GWR <24h predicted neurological outcome with unsatisfactory to satisfactory Area Under the Receiver Operating Characteristics Curve (AUROC: 0.54-0.64). GWR ≥24h yielded very good to excellent AUROC (0.80-0.93). Sensitivities increased >2-3 fold in examinations performed after 24h compared to early examinations. Combining eye-balling with GWR<1.15 predicted poor outcome without false positives with sensitivities remaining acceptable.

CONCLUSION

In our cohort, qualitative and quantitative CT methods predicted poor outcome with high specificity and low to moderate sensitivity. Sensitivity increased relevantly after the first 24 hours after CA. Interrater variability poses a problem and indicates the need to standardise brain CT evaluation to increase the methodś safety.

Can Optic Nerve Sheath Images on a Thin-Slice Brain Computed Tomography Reconstruction Predict the Neurological Outcomes in Cardiac Arrest Survivors?

We analyzed the prognostic performance of optic nerve sheath diameter (ONSD) on thin-slice (0.6 mm) brain computed tomography (CT) reconstruction images as compared to routine-slice (4 mm) images. We conducted a retrospective analysis of brain CT images taken within 2 h after cardiac arrest. The maximal ONSD (mONSD) and optic nerve sheath area (ONSA) were measured on thin-slice images, and the routine ONSD (rONSD) and gray-to-white matter ratio (GWR) were measured on routine-slice images. We analyzed their area under the receiver operator characteristic curve (AUC) and the cutoff values for predicting a poor 6-month neurological outcome (a cerebral performance category score of 3–5). Of the 159 patients analyzed, 113 patients had a poor outcome. There was no significant difference in rONSD between the outcome groups (p = 0.116). Compared to rONSD, mONSD (AUC 0.62, 95% CI: 0.54–0.70) and the ONSA (AUC 0.63, 95% CI: 0.55–0.70) showed better prognostic performance and had higher sensitivities to determine a poor outcome (mONSD, 20.4% [95% CI, 13.4–29.0]; ONSA, 16.8% [95% CI, 10.4–25.0]; rONSD, 7.1% [95% CI, 3.1–13.5]), with specificity of 95.7% (95% CI, 85.2–99.5). A combined cutoff value obtained by both the mONSD and GWR improved the sensitivity (31.0% [95% CI, 22.6–40.4]) of determining a poor outcome, while maintaining a high specificity. In conclusion, rONSD was clinically irrelevant, but the mONSD had an increased sensitivity in cutoff having acceptable specificity. Combination of the mONSD and GWR had an improved prognostic performance in these patients.

Brain magnetic resonance imaging and histopathology findings in a dog with global brain ischaemia following cardiopulmonary arrest

Background

Global brain ischaemia following cardiopulmonary arrest is uncommonly reported in veterinary medicine yet neurologic injury after arrest is a known morbidity.

Case report

An 18‐week‐old male entire Cavalier King Charles Spaniel‐Poodle was referred following 3 days of neurologic abnormalities after cardiopulmonary arrest. After resuscitation, the animal had decerebrate rigidity, a stuporous mentation and intermittent episodes of vocalisation and apnoea. A brain magnetic resonance imaging (MRI) was undertaken 4 days after cardiopulmonary arrest, with standard sequences (T1‐weighted, T2‐weighted and fluid‐attenuated inversion recovery) as well as diffusion‐weighted imaging to better discern ischaemic injury and cytotoxic oedema for prognostic reasons. MRI findings were consistent with global brain ischaemia affecting the hippocampus, cerebellum and substantia nigra, the latter two not previously identified in canine cases of global brain ischaemia. The patient was euthanased on day eight post‐cardiopulmonary arrest due to a lack of neurological improvement and developing sepsis as a complication. Ante‐mortem identification of affected areas of the brain was confirmed on histological examination, with evidence of ischaemic injury seen in the cerebrum, hippocampus, cerebellum, basal nuclei and thalamus.

Conclusion

This report describes ante‐mortem MRI and postmortem findings in a dog with global brain ischaemia following cardiopulmonary arrest. A multimodal approach to neuroprognostication in patients recovering from cardiopulmonary arrest is recommended.

Long Term Cognitive Function After Cardiac Arrest: A Mini-Review

Out-of-hospital cardiac arrest (OHCA) is a leading cause of mortality worldwide. With better pre- and inhospital treatment, including cardiopulmonary resuscitation (CPR) as an integrated part of public education and more public-access defibrillators available, OHCA survival has increased over the last decade. There are concerns, after successful resuscitation, of cerebral hypoxia and degrees of potential acquired brain injury with resulting poor cognitive functioning. Cognitive function is not routinely assessed in OHCA survivors, and there is a lack of consensus on screening methods for cognitive changes. This narrative mini-review, explores available evidence on hypoxic brain injury and long-term cognitive function in cardiac arrest survivors and highlights remaining knowledge deficits.

Gray-White Matter Ratio at the Level of the Basal Ganglia as a Predictor of Neurologic Outcomes in Cardiac Arrest Survivors: A Literature Review

Loss of gray-white matter discrimination is the primary early imaging finding within of cranial computed tomography in cardiac arrest survivors, and this has been also regarded as a novel predictor for evaluating neurologic outcome. As displayed clearly on computed tomography and based on sensitivity to hypoxia, the gray-white matter ratio at basal ganglia (GWR-BG) region was frequently detected to assess the neurologic outcome by several studies. The specificity of GWR-BG is 72.4 to 100%, while the sensitivity is significantly different. Herein we review the mechanisms mediating cerebral edema following cardiac arrest, demonstrate the determination procedures with respect to GWR-BG, summarize the related researches regarding GWR-BG in predicting neurologic outcomes within cardiac arrest survivors, and discuss factors associated with predicting the accuracy of this methodology. Finally, we describe the effective measurements to increase the sensitivity of GWR-BG in predicting neurologic outcome.

Deep learning of early brain imaging to predict post-arrest electroencephalography

INTRODUCTION

Guidelines recommend use of computerized tomography (CT) and electroencephalography (EEG) in post-arrest prognostication. Strong associations between CT and EEG might obviate the need to acquire both modalities. We quantified these associations via deep learning.

METHODS

We performed a single-center, retrospective study including comatose patients hospitalized after cardiac arrest. We extracted brain CT DICOMs, resized and registered each to a standard anatomical atlas, performed skull stripping and windowed images to optimize contrast of the gray-white junction. We classified initial EEG as generalized suppression, other highly pathological findings or benign activity. We extracted clinical information available on presentation from our prospective registry. We trained three machine learning (ML) models to predict EEG from clinical covariates. We used three state-of-the-art approaches to build multi-headed deep learning models using similar model architectures. Finally, we combined the best performing clinical and imaging models. We evaluated discrimination in test sets.

RESULTS

We included 500 patients, of whom 218 (44%) had benign EEG findings, 135 (27%) showed generalized suppression and 147 (29%) had other highly pathological findings that were most commonly (93%) burst suppression with identical bursts. Clinical ML models had moderate discrimination (test set AUCs 0.73-0.80). Image-based deep learning performed worse (test set AUCs 0.51-0.69), particularly discriminating benign from highly pathological findings. Adding image-based deep learning to clinical models improved prediction of generalized suppression due to accurate detection of severe cerebral edema.

DISCUSSION

CT and EEG provide complementary information about post-arrest brain injury. Our results do not support selective acquisition of only one of these modalities, except in the most severely injured patients.

Effects of targeted temperature management at 33°C vs. 36°C on comatose patients after cardiac arrest stratified by the severity of encephalopathy

OBJECTIVES

To assess neurological outcome after targeted temperature management (TTM) at 33°C vs. 36°C, stratified by the severity of encephalopathy based on EEG-patterns at 12 and 24h.

DESIGN

Post hoc analysis of prospective cohort study.

SETTING

Five Dutch Intensive Care units.

PATIENTS

479 adult comatose post-cardiac arrest patients.

INTERVENTIONS

TTM at 33°C (n=270) or 36°C (n=209) and continuous EEG monitoring.

MEASUREMENTS AND MAIN RESULTS

Outcome according to the cerebral performance category (CPC) score at 6 months post-cardiac arrest was similar after 33°C and 36°C. However, when stratified by the severity of encephalopathy based on EEG-patterns at 12 and 24h after cardiac arrest, the proportion of good outcome (CPC 1-2) in patients with moderate encephalopathy was significantly larger after TTM at 33°C (66% vs. 45%; Odds Ratios 2.38, 95% CI=1.32-4.30; p=0.004). In contrast, with mild encephalopathy, there was no statistically significant difference in the proportion of patients with good outcome between 33°C and 36°C (88% vs. 81%; OR 1.68, 95% CI=0.65-4.38; p=0.282). Ordinal regression analysis showed a shift towards higher CPC scores when treated with TTM 33°C as compared with 36°C in moderate encephalopathy (cOR 2.39; 95% CI=1.40-4.08; p=0.001), but not in mild encephalopathy (cOR 0.81 95% CI=0.41-1.59; p=0.537). Adjustment for initial cardiac rhythm and cause of arrest did not change this relationship.

CONCLUSIONS

Effects of TTM probably depend on the severity of encephalopathy in comatose patients after cardiac arrest. These results support inclusion of predefined subgroup analyses based on EEG measures of the severity of encephalopathy in future clinical trials.

Delayed head CT in out-of-hospital cardiac arrest survivors: Does this improve predictive performance of neurological outcome?

BACKGROUND

We compared the ability of head computed tomography (HCT) and MRI, respectively, obtained before or after target temperature management to predict neurologic outcomes in out-of-hospital cardiac arrest (OHCA) survivors.

METHODS

This retrospective study included adult comatose OHCA survivors who underwent neuroimaging scans within 6 h (first HCT) or 72-96 h (second HCT and MRI) after the return of spontaneous circulation (ROSC). We calculated the gray-white matter ratio (GWR), hypoxic-ischemic brain injury presence (loss of boundary at the basal ganglia level [LOB at BG], sulcal effacement at the centrum semiovale [SE at CS], and pseudo-SAH sign), and the overall score based on MRI findings (a total score of 21 brain regions individually scored according to the degree of signal abnormality).

RESULTS

Overall, 78 patients were included in this analysis, of whom 45 (58%) showed poor outcomes. The second HCT scan showed greater prognostic performance than the first HCT scan for GWR (area under curve 0.92 vs. 0.70), LOB at BG (0.93 vs. 0.65), SE at CS (0.89 vs. 0.64), and pseudo-SAH sign (0.75 vs. 0.51). The overall score on MRI (0.99) showed the highest prognostic performance. However, on the second HCT scan, the combination of GWR and LOB at BG showed prognostic performance (0.96) comparable to the overall score on MRI (P=0.12); the corresponding sensitivity and specificity values were 85.7% and 100%.

CONCLUSIONS

Overall score on MRI and the combination of GWR and LOB at BG findings on second HCT scans may help predict poor outcomes in OHCA survivors.

Enhancing cardiac arrest survival with extracorporeal cardiopulmonary resuscitation: insights into the process of death

Extracorporeal cardiopulmonary resuscitation (ECPR) is an emerging method of cardiopulmonary resuscitation to improve outcomes from cardiac arrest. This approach targets patients with out-of-hospital cardiac arrest previously unresponsive and refractory to standard treatment, combining approximately 1 h of standard CPR followed by venoarterial extracorporeal membrane oxygenation (VA-ECMO) and coronary artery revascularization. Despite its relatively new emergence for the treatment of cardiac arrest, the approach is grounded in a vast body of preclinical and clinical data that demonstrate significantly improved survival and neurological outcomes despite unprecedented, prolonged periods of CPR. In this review, we detail the principles behind VA-ECMO-facilitated resuscitation, contemporary clinical approaches with outcomes, and address the emerging new understanding of the process of death and capability for neurological recovery.

Machine Learning for Early Detection of Hypoxic-Ischemic Brain Injury After Cardiac Arrest

Background

Establishing whether a patient who survived a cardiac arrest has suffered hypoxic-ischemic brain injury (HIBI) shortly after return of spontaneous circulation (ROSC) can be of paramount importance for informing families and identifying patients who may benefit the most from neuroprotective therapies. We hypothesize that using deep transfer learning on normal-appearing findings on head computed tomography (HCT) scans performed after ROSC would allow us to identify early evidence of HIBI.

Methods

We analyzed 54 adult comatose survivors of cardiac arrest for whom both an initial HCT scan, done early after ROSC, and a follow-up HCT scan were available. The initial HCT scan of each included patient was read as normal by a board-certified neuroradiologist. Deep transfer learning was used to evaluate the initial HCT scan and predict progression of HIBI on the follow-up HCT scan. A naive set of 16 additional patients were used for external validation of the model.

Results

The median age (interquartile range) of our cohort was 61 (16) years, and 25 (46%) patients were female. Although findings of all initial HCT scans appeared normal, follow-up HCT scans showed signs of HIBI in 29 (54%) patients (computed tomography progression). Evaluating the first HCT scan with deep transfer learning accurately predicted progression to HIBI. The deep learning score was the most significant predictor of progression (area under the receiver operating characteristic curve = 0.96 [95% confidence interval 0.91–1.00]), with a deep learning score of 0.494 having a sensitivity of 1.00, specificity of 0.88, accuracy of 0.94, and positive predictive value of 0.91. An additional assessment of an independent test set confirmed high performance (area under the receiver operating characteristic curve = 0.90 [95% confidence interval 0.74–1.00]).

Conclusions

Deep transfer learning used to evaluate normal-appearing findings on HCT scans obtained early after ROSC in comatose survivors of cardiac arrest accurately identifies patients who progress to show radiographic evidence of HIBI on follow-up HCT scans.

Intracranial Pressure Patterns and Neurological Outcomes in Out-of-Hospital Cardiac Arrest Survivors after Targeted Temperature Management: A Retrospective Observational Study

We aimed to investigate intracranial pressure (ICP) changes over time and the neurologic prognosis for out-of-hospital cardiac arrest (OHCA) survivors who received targeted temperature management (TTM). ICP was measured immediately after return of spontaneous circulation (ROSC) (day 1), then at 24 h (day 2), 48 h (day 3), and 72 h (day 4), through connecting a lumbar drain catheter to a manometer or a LiquoGuard machine. Neurological outcomes were determined at 3 months after ROSC, and a poor neurological outcome was defined as Cerebral Performance Category 3–5. Of the 91 patients in this study (males, n = 67, 74%), 51 (56%) had poor neurological outcomes. ICP was significantly higher in the poor outcome group at each time point except day 4. ICP elevation was highest between days 2 and 3 in the good outcome group, and between days 1 and 2 in the poor outcome group. However, there was no difference in total ICP elevation between the poor and good outcome groups (3.0 vs. 3.1; p = 0.476). All OHCA survivors who had received TTM had elevated ICP, regardless of neurologic prognosis. However, the changing pattern of ICP levels differed depending on the neurological outcome.

Brain injury after cardiac arrest: pathophysiology, treatment, and prognosis

Post-cardiac arrest brain injury (PCABI) is caused by initial ischaemia and subsequent reperfusion of the brain following resuscitation. In those who are admitted to intensive care unit after cardiac arrest, PCABI manifests as coma, and is the main cause of mortality and long-term disability. This review describes the mechanisms of PCABI, its treatment options, its outcomes, and the suggested strategies for outcome prediction.

18F-fluorodeoxyglucose positron-emitted tomography for predicting neurological outcome in hypoxic-ischemic encephalopathy

Background: ¹⁸F-fluorodeoxyglucose positron-emitted tomography (FDG-PET) is a promising yet unexplored functional neuroimaging tool in the study and prognosis of hypoxic-ischemic encephalopathy (HIE) after cardiac arrest or respiratory failure. The present study aimed to correlate clinical data and FDG-PET scans for both analysis and prognostic use. Methods: 24 patients from an intensive rehabilitation ward were retrospectively evaluated. Data collected included age, gender, cause of anoxic event, length of stay in acute and rehabilitation units, discharge destination, and evaluation at admission and discharge using three clinical scales to assess cognitive function, independence and disability. Subjects were identified as good and bad performers on the basis of quantitative analysis of FDG-PET scans with the Cortex ID software. The relation between glucose uptake reduction and neurological outcome was evaluated. Results: good and bad performers presented no statistically significant difference regarding demographical data and in-hospital length of stay. The two categories significantly differed for impairment and disability levels both at admission and at discharge from the inpatient rehabilitation unit. Conclusions: FDG-PET considerably facilitates the early identification of patients with HIE who will have poor neurological outcome and could inform planning for their rehabilitation and care.

Upregulation of hemeoxygenase enzymes HO-1 and HO-2 following ischemia-reperfusion injury in connection with experimental cardiac arrest and cardiopulmonary resuscitation: Neuroprotective effects of methylene blue

Oxidative stress plays an important role in neuronal injuries after cardiac arrest. Increased production of carbon monoxide (CO) by the enzyme hemeoxygenase (HO) in the brain is induced by the oxidative stress. HO is present in the CNS in two isoforms, namely the inducible HO-1 and the constitutive HO-2. Elevated levels of serum HO-1 occurs in cardiac arrest patients and upregulation of HO-1 in cardiac arrest is seen in the neurons. However, the role of HO-2 in cardiac arrest is not well known. In this review involvement of HO-1 and HO-2 enzymes in the porcine brain following cardiac arrest and resuscitation is discussed based on our own observations. In addition, neuroprotective role of methylene blue- an antioxidant dye on alterations in HO under in cardiac arrest is also presented. The biochemical findings of HO-1 and HO-2 enzymes using ELISA were further confirmed by immunocytochemical approach to localize selective regional alterations in cardiac arrest. Our observations are the first to show that cardiac arrest followed by successful cardiopulmonary resuscitation results in significant alteration in cerebral concentrations of HO-1 and HO-2 levels indicating a prominent role of CO in brain pathology and methylene blue during CPR followed by induced hypothermia leading to superior neuroprotection after return of spontaneous circulation (ROSC), not reported earlier.

Automated Assessment of Brain CT After Cardiac Arrest-An Observational Derivation/Validation Cohort Study

Objectives

Prognostication of outcome is an essential step in defining therapeutic goals after cardiac arrest. Gray-white-matter ratio obtained from brain CT can predict poor outcome. However, manual placement of regions of interest is a potential source of error and interrater variability. Our objective was to assess the performance of poor outcome prediction by automated quantification of changes in brain CTs after cardiac arrest.

Design

Observational, derivation/validation cohort study design. Outcome was determined using the Cerebral Performance Category upon hospital discharge. Poor outcome was defined as death or unresponsive wakefulness syndrome/coma. CTs were automatically decomposed using coregistration with a brain atlas.

Setting

ICUs at a large, academic hospital with circulatory arrest center.

Patients

We identified 433 cardiac arrest patients from a large previously established database with brain CTs within 10 days after cardiac arrest.

Interventions

None.

Measurements and Main Results

Five hundred sixteen brain CTs were evaluated (derivation cohort n = 309, validation cohort n = 207). Patients with poor outcome had significantly lower radiodensities in gray matter regions. Automated GWR_si (putamen/posterior limb of internal capsule) was performed with an area under the curve of 0.86 (95%-CI: 0.80-0.93) for CTs taken later than 24 hours after cardiac arrest (similar performance in the validation cohort). Poor outcome (Cerebral Performance Category 4-5) was predicted with a specificity of 100% (95% CI, 87-100%, derivation; 88-100%, validation) at a threshold of less than 1.10 and a sensitivity of 49% (95% CI, 36-58%, derivation) and 38% (95% CI, 27-50%, validation) for CTs later than 24 hours after cardiac arrest. Sensitivity and area under the curve were lower for CTs performed within 24 hours after cardiac arrest.

Conclusions

Automated gray-white-matter ratio from brain CT is a promising tool for prediction of poor neurologic outcome after cardiac arrest with high specificity and low-to-moderate sensitivity. Prediction by gray-white-matter ratio at the basal ganglia level performed best. Sensitivity increased considerably for CTs performed later than 24 hours after cardiac arrest.

Novel approaches to prediction in severe brain injury

PURPOSE OF REVIEW

Recovery after severe brain injury is variable and challenging to accurately predict at the individual patient level. This review highlights new developments in clinical prognostication with a special focus on the prediction of consciousness and increasing reliance on methods from data science.

RECENT FINDINGS

Recent research has leveraged serum biomarkers, quantitative electroencephalography, MRI, and physiological time-series to build models for recovery prediction. The analysis of high-resolution data and the integration of features from different modalities can be approached with efficient computational techniques.

SUMMARY

Advances in neurophysiology and neuroimaging, in combination with computational methods, represent a novel paradigm for prediction of consciousness and functional recovery after severe brain injury. Research is needed to produce reliable, patient-level predictions that could meaningfully impact clinical decision making.

The Association Between Neurological Prognosis and the Degree of Blood-Brain Barrier Disruption in Cardiac Arrest Survivors Who Underwent Target Temperature Management

BACKGROUND

This study aimed to compare day-specific associations of blood-brain barrier (BBB) disruption with neurological outcome in survivors of out-of-hospital cardiac arrest (OHCA) treated with target temperature management (TTM) and lumbar drainage.

METHODS

This retrospective single-center study included 68 survivors of OHCA who underwent TTM between April 2018 and December 2019. The albumin quotient (Q_A) was calculated as Q_A = albumin_{cerebrospinal fluid}/albumin_serum immediately (day 1) and 24 (day 2), 48 (day 3), and 72 h (day 4) after the return of spontaneous circulation. The degree of BBB disruption was weighted using the following scoring system: Q_A value of 0.007 or less (normal), Q_A value greater than 0.007-0.01 (mild), Q_A value greater than 0.01-0.02 (moderate), and Q_A value greater than 0.02 (severe). Points were assigned as follows: 0 (normal), 1 (mild), 4 (moderate), and 9 (severe). Neurological outcome was determined at 6 months after the return of spontaneous circulation, as well as cerebral performance category (CPC), dichotomized as good (CPC score 1-2) and poor (CPC score 3-5) outcome.

RESULTS

We enrolled 68 patients (48 men, 71%); 37 (54%) patients had a poor neurological outcome. The distributions of poor versus good outcomes at 6 months in patients with moderate and severe BBB disruption were 19 of 22 (80%) vs. 18 of 46 (50%) on day 1, 31 of 37 (79%) vs. 6 of 31 (32%) on day 2, 32 of 37 (81%) vs. 5 of 31 (30%) on day 3, and 32 of 39 (85%) vs. 5 of 29 (30%) on day 4 (P < 0.001), respectively. Using receiver operating characteristic analyses, optimal cutoff values (sensitivity, specificity) of Q_A levels for the prediction of neurological outcome were as follows: day 1, greater than 0.009 (56.8%, 87.1%); day 2, greater than 0.012 (81.1%, 87.1%); day 3, greater than 0.013 (83.8%, 87.1%); day 4, greater than 0.013 (86.5%, 87.1%); the sum of all time points, greater than 0.039 (89.5%, 79.4%); and scoring system, greater than 9 (91.9%, 87.1%).

CONCLUSIONS

In this proof of concept study, Q_A was associated with poor neurological outcome in survivors of OHCA treated with TTM with no contraindication to lumbar drainage. A large multicenter prospective study is needed to validate the utility of BBB disruption as a prognosticator of neurological outcome.

ST-Elevation Myocardial Infarction Complicated by Out-of-Hospital Cardiac Arrest

5-10% of ST-elevated myocardial infarctions (STEMI) present with out-of-hospital cardiac arrest (OHCA). Although this subgroup of patients carries the highest in-hospital mortality among the STEMI population, it is the least likely to undergo coronary angiography and revascularization. Due to the concomitant neurologic injury, patients with OHCA STEMI require prolonged hospitalization and adjustments to standard MI management. This review systematically assesses the course of patients with OHCA STEMI from development of the arrest to hospital discharge, assesses the limiting factors for their treatment access, and presents the evidence-based optimal intervention strategy for this high-risk MI population.

European Resuscitation Council and European Society of Intensive Care Medicine guidelines 2021: post-resuscitation care

The European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) have collaborated to produce these post-resuscitation care guidelines for adults, which are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. The topics covered include the post-cardiac arrest syndrome, diagnosis of cause of cardiac arrest, control of oxygenation and ventilation, coronary reperfusion, haemodynamic monitoring and management, control of seizures, temperature control, general intensive care management, prognostication, long-term outcome, rehabilitation and organ donation.

European Resuscitation Council and European Society of Intensive Care Medicine Guidelines 2021: Post-resuscitation care

The European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) have collaborated to produce these post-resuscitation care guidelines for adults, which are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. The topics covered include the post-cardiac arrest syndrome, diagnosis of cause of cardiac arrest, control of oxygenation and ventilation, coronary reperfusion, haemodynamic monitoring and management, control of seizures, temperature control, general intensive care management, prognostication, long-term outcome, rehabilitation, and organ donation.

Neuroprotective Treatment of Postanoxic Encephalopathy: A Review of Clinical Evidence

Postanoxic encephalopathy is the key determinant of death or disability after successful cardiopulmonary resuscitation. Animal studies have provided proof-of-principle evidence of efficacy of divergent classes of neuroprotective treatments to promote brain recovery. However, apart from targeted temperature management (TTM), neuroprotective treatments are not included in current care of patients with postanoxic encephalopathy after cardiac arrest. We aimed to review the clinical evidence of efficacy of neuroprotective strategies to improve recovery of comatose patients after cardiac arrest and to propose future directions. We performed a systematic search of the literature to identify prospective, comparative clinical trials on interventions to improve neurological outcome of comatose patients after cardiac arrest. We included 53 studies on 21 interventions. None showed unequivocal benefit. TTM at 33 or 36°C and adrenaline (epinephrine) are studied most, followed by xenon, erythropoietin, and calcium antagonists. Lack of efficacy is associated with heterogeneity of patient groups and limited specificity of outcome measures. Ongoing and future trials will benefit from systematic collection of measures of baseline encephalopathy and sufficiently powered predefined subgroup analyses. Outcome measurement should include comprehensive neuropsychological follow-up, to show treatment effects that are not detectable by gross measures of functional recovery. To enhance translation from animal models to patients, studies under experimental conditions should adhere to strict methodological and publication guidelines.

Neurologic complications of cardiac arrest

Cardiac arrest is a catastrophic event with high morbidity and mortality. Despite advances over time in cardiac arrest management and postresuscitation care, the neurologic consequences of cardiac arrest are frequently devastating to patients and their families. Targeted temperature management is an intervention aimed at limiting postanoxic injury and improving neurologic outcomes following cardiac arrest. Recovery of neurologic function governs long-term outcome after cardiac arrest and prognosticating on the potential for recovery is a heavy burden for physicians. An early and accurate estimate of the potential for recovery can establish realistic expectations and avoid futile care in those destined for a poor outcome. This chapter reviews the epidemiology, pathophysiology, therapeutic interventions, prognostication, and neurologic sequelae of cardiac arrest.

Standardized visual EEG features predict outcome in patients with acute consciousness impairment of various etiologies

BACKGROUND

Early prognostication in patients with acute consciousness impairment is a challenging but essential task. Current prognostic guidelines vary with the underlying etiology. In particular, electroencephalography (EEG) is the most important paraclinical examination tool in patients with hypoxic ischemic encephalopathy (HIE), whereas it is not routinely used for outcome prediction in patients with traumatic brain injury (TBI).

METHOD

Data from 364 critically ill patients with acute consciousness impairment (GCS ≤ 11 or FOUR ≤ 12) of various etiologies and without recent signs of seizures from a prospective randomized trial were retrospectively analyzed. Random forest classifiers were trained using 8 visual EEG features-first alone, then in combination with clinical features-to predict survival at 6 months or favorable functional outcome (defined as cerebral performance category 1-2).

RESULTS

The area under the ROC curve was 0.812 for predicting survival and 0.790 for predicting favorable outcome using EEG features. Adding clinical features did not improve the overall performance of the classifier (for survival: AUC = 0.806, p = 0.926; for favorable outcome: AUC = 0.777, p = 0.844). Survival could be predicted in all etiology groups: the AUC was 0.958 for patients with HIE, 0.955 for patients with TBI and other neurosurgical diagnoses, 0.697 for patients with metabolic, inflammatory or infectious causes for consciousness impairment and 0.695 for patients with stroke. Training the classifier separately on subgroups of patients with a given etiology (and thus using less training data) leads to poorer classification performance.

CONCLUSIONS

While prognostication was best for patients with HIE and TBI, our study demonstrates that similar EEG criteria can be used in patients with various causes of consciousness impairment, and that the size of the training set is more important than homogeneity of ACI etiology.

[Brain death criterion and organ donation: current neuroscientific perspective]

In der akademischen und öffentlichen Debatte wird der irreversible Hirnfunktionsausfall als Kriterium des Todes (Hirntodkriterium) immer wieder hinterfragt. Im vorliegenden Artikel werden 6 prototypische Thesen gegen das Hirntodkriterium diskutiert: 1) Nichtsuperiorität des Gehirns gegenüber anderen Organen, 2) Unsicherheit der Hirntoddiagnostik, 3) erhaltene Schmerzempfindung Hirntoter, 4) (spontane) sexuelle Reifung und erhaltene Reproduktionsfunktion Hirntoter, 5) Symmetrie von Hirntod und Embryonalphase, 6) Gleichsetzung des intensivmedizinisch erhaltenen Restorganismus Hirntoter mit dem lebenden Menschen.

Keine dieser Thesen hält einer kritischen Analyse stand. In Deutschland wird das Ganzhirntodkriterium angewendet. Der Hirntod geht mit dem völligen Ausfall jeglicher Empfindung, Bewusstheit, Mimik, Augen‑, Zungen- und Schlundmotorik, Willkürmotorik und Sexualfunktion einher (funktionelle „Enthauptung“). Medizinisch-technisch können andere Organe bzw. ihre Primitivsteuerung ersetzt werden, nicht aber das Gehirn. Das Gehirn, nicht der Körper, ist bestimmend für das menschliche Individuum. Die Gleichsetzung des künstlich erhaltenen Restorganismus, naturphilosophisch als lebendiges System interpretierbar, mit dem Organismus desselben lebenden Menschen wird durch die beliebige Reduzierbarkeit der Anzahl beteiligter Organe ad absurdum geführt. Der irreversible Hirnfunktionsausfall führt unausweichlich zum Herzstillstand, unbehandelt innerhalb von Minuten, unter Intensivtherapie i. d. R. innerhalb von Tagen. Auch beim Embryo/Fötus führt die Fehlanlage des gesamten Gehirns zum (vorgeburtlichen) Tod. Die in Deutschland gesetzliche Richtlinie zur Hirntodfeststellung hat eine im internationalen Vergleich hohe Diagnosesicherheit, es sind damit keine bestätigten Fehldiagnosen aufgetreten.

Prediction of poor neurological outcome in comatose survivors of cardiac arrest: a systematic review

Purpose

To assess the ability of clinical examination, blood biomarkers, electrophysiology, or neuroimaging assessed within 7 days from return of spontaneous circulation (ROSC) to predict poor neurological outcome, defined as death, vegetative state, or severe disability (CPC 3–5) at hospital discharge/1 month or later, in comatose adult survivors from cardiac arrest (CA).

Methods

PubMed, EMBASE, Web of Science, and the Cochrane Database of Systematic Reviews (January 2013–April 2020) were searched. Sensitivity and false-positive rate (FPR) for each predictor were calculated. Due to heterogeneities in recording times, predictor thresholds, and definition of some predictors, meta-analysis was not performed.

Results

Ninety-four studies (30,200 patients) were included. Bilaterally absent pupillary or corneal reflexes after day 4 from ROSC, high blood values of neuron-specific enolase from 24 h after ROSC, absent N20 waves of short-latency somatosensory-evoked potentials (SSEPs) or unequivocal seizures on electroencephalogram (EEG) from the day of ROSC, EEG background suppression or burst-suppression from 24 h after ROSC, diffuse cerebral oedema on brain CT from 2 h after ROSC, or reduced diffusion on brain MRI at 2–5 days after ROSC had 0% FPR for poor outcome in most studies. Risk of bias assessed using the QUIPS tool was high for all predictors.

Conclusion

In comatose resuscitated patients, clinical, biochemical, neurophysiological, and radiological tests have a potential to predict poor neurological outcome with no false-positive predictions within the first week after CA. Guidelines should consider the methodological concerns and limited sensitivity for individual modalities. (PROSPERO CRD42019141169)

Electronic supplementary material

The online version of this article (10.1007/s00134-020-06198-w) contains supplementary material, which is available to authorized users.

Positron Emission Tomography After Ischemic Brain Injury: Current Challenges and Future Developments

Positron emission tomography (PET) is widely used in clinical and animal studies, along with the development of diverse tracers. The biochemical characteristics of PET tracers may help uncover the pathophysiological consequences of cardiac arrest (CA) and ischemic stroke, which include cerebral ischemia and reperfusion, depletion of oxygen and glucose, and neuroinflammation. PubMed was searched for studies of the application of PET for "cardiac arrest," "ischemic stroke," and "targeted temperature management." Available studies were included and classified according to the biochemical properties involved and metabolic processes of PET tracers, and were summarized. The mechanisms of ischemic brain injuries were investigated by PET with various tracers to elucidate the pathological process from the initial decrease of cerebral blood flow (CBF) to the subsequent abnormalities in energy and oxygen metabolism, to the monitoring of inflammation. In general, the trends of cerebral blood flow and oxygen metabolism after ischemic attack are not unidirectional but closely related to the time point of injury and recovery. Glucose metabolism after injury showed significant differences in different brain regions whereas global cerebral metabolic rate of glucose (CMRglc) declined. PET monitoring of neuroinflammation shows comparable efficacy to immunostaining. The technology of PET targeting in brain metabolism and the development of tracers provide new tools to track and evaluate the brain's pathological changes after ischemic brain injury. Despite no existing evidence for an available PET-based prediction method, discoveries of new tracers are expected to provide more possibilities for the whole field.