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Aim: Magnetic Resonance Imaging (MRI) is an important prognostic tool in cardiac arrest (CA) survivors given its sensitivity for detecting hypoxic-ischemic brain injury (HIBI), however, it is limited by poorly defined objective thresholds. To address this limitation, we evaluated a qualitative MRI score for predicting neurological outcome in CA survivors., Methods: Adult comatose CA survivors who underwent MRI were retrospectively identified at a single academic medical center. Two blinded neurointensivists qualitatively scored HIBI amongst 12 MRI brain regions. Scores were summated to form four distinct score groups: cortex, deep grey nuclei (DGN), cortex-DGN combined, and total (cortex, DGN, brainstem, and cerebellum). Poor neurological outcome was defined as Cerebral Performance Category (CPC) score 3-5 at hospital discharge. Inter-rater reliability was tested using intra-class correlation (ICC) and discrimination of poor neurological outcome assessed using area under the receiver operating curve (AUC)., Results: Our cohort included 219 patients with median time to MRI of 96 (IQR 81-110) hours. ICC (95% CI) was good to excellent across all MRI scores: cortex 0.92 (0.89-0.94), DGN 0.88 (0.80-0.92), cortex-DGN 0.94 (0.92-0.95), and total 0.93 (0.91-0.95). AUC (95% CI) for poor outcome was good across all MRI scores: cortex 0.84 (0.78-0.90), DGN 0.83 (0.77-0.89), cortex-DGN 0.83 (0.77-0.89), and total 0.83 (0.77-0.88)., Conclusion: A simplified, qualitative MRI score had excellent reliability and good discrimination for poor neurologic outcome. Further work is necessary to externally validate our findings in an independent, ideally prospective, cohort., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: “Dr. Tripodis receives research support from the NIH and the AMA. Dr. Greer receives research funding in the form of a grant to Boston Medical Center to conduct the INTREPID study as co-PI, including reimbursed travel to present results at major conferences. In unrelated support, Dr. Greer receives research support from NIH/NINDS, as well as personal compensation as Editor-in-Chief for Seminars in Neurology, royalties for several books, as well as medical-legal expert work.”., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The aim of this prospective, observational cohort study was to investigate and assess diverse neuroimaging biomarkers to predict patients' neurological recovery after coma. 32 patients (18-76 years, M = 44.8, SD = 17.7) with disorders of consciousness participated in the study. Multimodal neuroimaging data acquired during the patient's hospitalization were used to derive cortical glucose metabolism ( 18 F-fluorodeoxyglucose positron emission tomography/computed tomography), and structural (diffusion-weighted imaging) and functional connectivity (resting-state functional MRI) indices. The recovery outcome was defined as a continuous composite score constructed from a multivariate neurobehavioral recovery assessment administered upon the discharge from the hospital. Fractional anisotropy-based white matter integrity in the anterior forebrain mesocircuit (r = 0.72, p < .001, 95% CI: 0.87, 0.45), and the functional connectivity between the antagonistic default mode and dorsal attention resting-state networks (r = - 0.74, p < 0.001, 95% CI: - 0.46, - 0.88) strongly correlated with the recovery outcome. The association between the posterior glucose metabolism and the recovery outcome was moderate (r = 0.38, p = 0.040, 95% CI: 0.66, 0.02). Structural (adjusted R 2  = 0.84, p = 0.003) or functional connectivity biomarker (adjusted R 2  = 0.85, p = 0.001), but not their combination, significantly improved the model fit to predict the recovery compared solely to bedside neurobehavioral evaluation (adjusted R 2  = 0.75). The present study elucidates an important role of specific MRI-derived structural and functional connectivity biomarkers in diagnosis and prognosis of recovery after coma and has implications for clinical care of patients with severe brain injury., (© 2024. The Author(s).)

Background: This study aimed to explore the characteristics of abnormal regional resting-state functional magnetic resonance imaging (rs-fMRI) activity in comatose patients in the early period after cardiac arrest (CA), and to investigate their relationships with neurological outcomes. We also explored the correlations between jugular venous oxygen saturation (SjvO2) and rs-fMRI activity in resuscitated comatose patients. We also examined the relationship between the amplitude of the N20-baseline and the rs-fMRI activity within the intracranial conduction pathway of somatosensory evoked potentials (SSEPs)., Methods: Between January 2021 and January 2024, eligible post-resuscitated patients were screened to undergo fMRI examination. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) of rs-fMRI blood oxygenation level-dependent (BOLD) signals were used to characterize regional neural activity. Neurological outcomes were evaluated using the Glasgow-Pittsburgh cerebral performance category (CPC) scale at 3 months after CA., Results: In total, 20 healthy controls and 31 post-resuscitated patients were enrolled in this study. The rs-fMRI activity of resuscitated patients revealed complex changes, characterized by increased activity in some local brain regions and reduced activity in others compared to healthy controls (P < 0.05). However, the mean ALFF values of the whole brain were significantly greater in CA patients (P = 0.011). Among the clusters of abnormal rs-fMRI activity, the cluster values of ALFF in the left middle temporal gyrus and inferior temporal gyrus and the cluster values of ReHo in the right precentral gyrus, superior frontal gyrus and middle frontal gyrus were strongly correlated with the CPC score (P < 0.001). There was a strong correlation between the mean ALFF and SjvO2 in CA patients (r = 0.910, P < 0.001). The SSEP N20-baseline amplitudes in CA patients were negatively correlated with thalamic rs-fMRI activity (all P < 0.001)., Conclusions: This study revealed that abnormal rs-fMRI BOLD signals in resuscitated patients showed complex changes, characterized by increased activity in some local brain regions and reduced activity in others. Abnormal BOLD signals were associated with neurological outcomes in resuscitated patients. The mean ALFF values of the whole brain were closely related to SjvO2 levels, and changes in the thalamic BOLD signals correlated with the N20-baseline amplitudes of SSEP responses., Trial Registration: NCT05966389 (Registered July 27, 2023)., (© 2024. The Author(s).)

Background: Aneurysmal subarachnoid hemorrhage (aSAH) is frequently complicated by delayed cerebral ischemia (DCI), leading to poor outcomes. Early diagnosis of DCI is crucial for improving survival and outcomes but remains challenging in comatose patients. In this study, we aimed to evaluate computed tomography with angiography and perfusion (P-CT) as a screening modality on postictal days four and eight for impending DCI after aSAH in comatose patients using vasospasm with hypoperfusion (hVS) as a surrogate and DCI-related infarction as an outcome measure. Two objectives were set: (1) to evaluate the screening's ability to accurately risk stratify patients and (2) to assess the validity of P-CT screening., Methods: We conducted a retrospective review of the records of comatose patients with aSAH from January 2019 to December 2021 who were monitored with P-CT scans on days four and eight. The event rates of DCI-related infarction, hVS, and endovascular rescue therapy (ERT) were analyzed, and the sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) for DCI were calculated. DCI-related infarction was defined as new secondary cerebral infarction > 48 h < 6 weeks post aSAH not attributable to other causes, and hVS was defined as arterial narrowing with corresponding hypoperfusion on P-CT., Results: Fifty-six comatose patients were included, and 98 P-CT scans were performed. The incidence of DCI-related infarction was 40%. Screening P-CT on days four and eight found vasospasm in 23% of all patients, including 11% with hVS. A positive hVS on day four or eight revealed a relative risk of 2.4 [95% confidence interval (CI) 1.13-5.11, p = 0.03], sensitivity of 23% (95% CI 8-45, p = 0.03), specificity of 95% (95% CI 36-100, p = 0.03), PPV of 0.83 (95% CI 0.36-1.00, p = 0.03), and NPV of 0.65 (95% CI 0.50-0.78). Six positive P-CT scans led to digital subtraction angiography in five patients, three of whom received ERT. All ERT-intervened patients developed DCI-related infarction., Conclusions: P-CT resulted in few interventions and often resulted in late detection of DCI at an irreversible stage. Although a positive P-CT result accurately predicts impending DCI-related infarction, screening on days four and eight alone in comatose patients with aSAH often fails to timely detect impending DCI. Based on our analysis, we cannot recommend P-CT as a screening modality. P-CT is likely best used as a confirmatory test prior to invasive interventions when guided by continuous multimodal monitoring; however, prospective studies with comparison groups are warranted. The need for a reliable continuous screening modality is evident because of the high rate of deterioration and narrow treatment window., (© 2023. The Author(s).)

BACKGROUND The thalamocortical tract (TCT) links nerve fibers between the thalamus and cerebral cortex, relaying motor/sensory information. The default mode network (DMN) comprises bilateral, symmetrical, isolated cortical regions of the lateral and medial parietal and temporal brain cortex. The Coma Recovery Scale-Revised (CRS-R) is a standardized neurobehavioral assessment of disorders of consciousness (DOC). In the present study, 31 patients with hypoxic-ischemic brain injury (HI-BI) were compared for changes in the TCT and DMN with consciousness levels assessed using the CRS-R. MATERIAL AND METHODS In this retrospective study, 31 consecutive patients with HI-BI (17 DOC,14 non-DOC) and 17 age- and sex-matched normal control subjects were recruited. Magnetic resonance imaging was used to diagnose HI-BI, and the CRS-R was used to evaluate consciousness levels at the time of diffusion tensor imaging (DTI). The fractional anisotropy (FA) values and tract volumes (TV) of the TCT and DMN were compared. RESULTS In patients with DOC, the FA values and TV of both the TCT and DMN were significantly lower compared to those of patients without DOC and the control subjects (p<0.05). When comparing the non-DOC and control groups, the TV of the TCT and DMN were significantly lower in the non-DOC group (p<0.05). Moreover, the CRS-R score had strong positive correlations with the TV of the TCT (r=0.501, p<0.05), FA of the DMN (r=0.532, p<0.05), and TV of the DMN (r=0.501, p<0.05) in the DOC group. CONCLUSIONS This study suggests that both the TCT and DMN exhibit strong correlations with consciousness levels in DOC patients with HI-BI.

Early prediction of the recovery of consciousness in comatose cardiac arrest patients remains challenging. We prospectively studied task-relevant fMRI responses in 19 comatose cardiac arrest patients and five healthy controls to assess the fMRI's utility for neuroprognostication. Tasks involved instrumental music listening, forward and backward language listening, and motor imagery. Task-specific reference images were created from group-level fMRI responses from the healthy controls. Dice scores measured the overlap of individual subject-level fMRI responses with the reference images. Task-relevant responsiveness index (Rindex) was calculated as the maximum Dice score across the four tasks. Correlation analyses showed that increased Dice scores were significantly associated with arousal recovery ( P < 0.05 ) and emergence from the minimally conscious state (EMCS) by one year ( P < 0.001 ) for all tasks except motor imagery. Greater Rindex was significantly correlated with improved arousal recovery (P = 0.002) and consciousness (P = 0.001). For patients who survived to discharge ( n = 6 ), the Rindex's sensitivity was 75% for predicting EMCS (n = 4). Task-based fMRI holds promise for detecting covert consciousness in comatose cardiac arrest patients, but further studies are needed to confirm these findings. Caution is necessary when interpreting the absence of task-relevant fMRI responses as a surrogate for inevitable poor neurological prognosis., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Objectives: The distance from skin to the hyoid bone (DSHB) and skin to the anterior commissure of vocal cords (DSAC) are reliable parameters for pre-operative airway ultrasound assessment in awake patients and can be assessed in comatose patients. This study aimed to inspect its feasibility and accuracy in predicting difficult laryngoscopy for comatose patients., Methods: A prospective cohort study included patients with a Glasgow Coma Scale (GCS) of ≤8 who underwent emergency tracheal intubation between November 2019 and August 2020. The outcome was difficult laryngoscopy and classified according to the Cormack-Lehane grading., Results: A total of 151 patients were included in the study. Fifty-two (34.4%) patients were categorized as having difficult laryngoscopy. The DSHB add DSAC (hereinafter referred to as the "DSBAC") was superior to either parameter alone in the predictive performance, and the optimal cut-off value was 1.90. To optimize the predictive value, DSBAC (adjusted odds ratio [OR]: 7.76; 95% confidence interval [CI]: 2.88-20.94; P < .001), GCS (adjusted OR: 1.39; 95% CI: 3.93-26.28; P = .039), mandibular retraction (adjusted OR: 8.20; 95% CI: 1.92-35.09; P = .005) and edentulous (adjusted OR: 4.23; 95% CI: 1.40-12.80; P = .011) were included in a multivariable model and constructed a nomogram. Discrimination and calibration statistics were satisfactory, with C-index above 0.80 from both model development and internal validation., Conclusions: Ultrasound-derived factor, DSBAC, can be easily assessed and help predict difficult laryngoscopy among comatose patients. A simple nomogram including only four clinical items exhibited excellent discrimination performance and was useful when comatose patients underwent emergency tracheal intubation., (© 2023 American Institute of Ultrasound in Medicine.)

Background: It remains a challenge to judge whether comatose patients with acute intracerebral hemorrhage (ICH) can wake up. Here, we aimed to investigate the changes in right ventricle-pulmonary artery (RV-PA) coupling over time in these patients and to evaluate its performance for discriminating between those who woke up within 60 days and those who did not., Methods: Thirty-five comatose patients with acute spontaneous ICH underwent bedside echocardiography on days 1, 3, and 5 after onset with the measurement of tricuspid annular plane systolic excursion and mean pulmonary artery pressure. The RV-PA coupling (the ratio of tricuspid annular plane systolic excursion to mean pulmonary artery pressure) was calculated., Results: Within 60 days of the onset of coma, 11 individuals awakened and survived, and 24 individuals died. In awakened patients, RV-PA couplings did not differ among days 1, 3, and 5 (1.62 ± 0.38 vs. 1.61 ± 0.32 vs. 1.64 ± 0.25 mm/mm Hg, P > 0.05), whereas in unawakened patients, they decreased drastically from day 1 to day 3 and then to day 5 (1.26 ± 0.32 vs. 0.63 ± 0.05 vs. 0.43 ± 0.06 mm/mm Hg, P < 0.05). The area under receiver operating characteristic curve of 0.992 for the ratio of RV-PA coupling on day 5 to day 1 of the coma was superior to that for the Glasgow Coma Scale (area under receiver operating characteristic curve of 0.606) in the discrimination of comatose patients with ICH who woke up within 60 days from those who did not. The optimal cutoff value was 0.536, with a sensitivity of 100.00%, a specificity of 96.24%, and an accuracy of 97.13%., Conclusions: Right ventricle-pulmonary artery coupling demonstrated a high performance for discriminating comatose patients with ICH who woke up within 60 days from those who did not., (© 2022. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

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 mm 2 /s versus 833 [SD, 23] × 10 -6 mm 2 /s, P  < .001) and larger average volumes of tissue with ADC below 650 × 10 -6 mm s /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., (© 2023 by American Journal of Neuroradiology.)

Purpose: We compared the predictive accuracy of early-phase brain diffusion tensor imaging (DTI), proton magnetic resonance spectroscopy (1H-MRS), and serum neuron-specific enolase (NSE) against the motor score and epileptic seizures (ES) for poor neurological outcome after out-of-hospital cardiac arrest (OHCA)., Methods: The predictive accuracy of DTI, 1H-MRS, and NSE along with motor score at 72 h and ES for the poor neurological outcome (modified Rankin Scale, mRS, 3 - 6) in 92 comatose OHCA patients at 6 months was assessed by area under the receiver operating characteristic curve (AUROC). Combined models of the variables were included as exploratory., Results: The predictive accuracy of fractional anisotropy (FA) of DTI (AUROC 0.73, 95% CI 0.62-0.84), total N-acetyl aspartate/total creatine (tNAA/tCr) of 1H-MRS (0.78 (0.68 - 0.88)), or NSE at 72 h (0.85 (0.76 - 0.93)) was not significantly better than motor score at 72 h (0.88 (95% CI 0.80-0.96)). The addition of FA and tNAA/tCr to a combination of NSE, motor score, and ES provided a small but statistically significant improvement in predictive accuracy (AUROC 0.92 (0.85-0.98) vs 0.98 (0.96-1.00), p = 0.037)., Conclusion: None of the variables (FA, tNAA/tCr, ES, NSE at 72 h, and motor score at 72 h) differed significantly in predicting poor outcomes in this patient group. Early-phase quantitative neuroimaging provided a statistically significant improvement for the predictive value when combined with ES and motor score with or without NSE. However, in clinical practice, the additional value is small, and considering the costs and challenges of imaging in this patient group, early-phase DTI/MRS cannot be recommended for routine use., Trial Registration: ClinicalTrials.gov NCT00879892, April 13, 2009., (© 2022. The Author(s).)

Objective: We aimed to explore the pathogenesis of traumatic coma related to functional connectivity (FC) within the default mode network (DMN), within the executive control network (ECN) and between the DMN and ECN and to investigate its capacity for predicting awakening., Methods: We carried out resting-state functional magnetic resonance imaging (fMRI) examinations on 28 traumatic coma patients and 28 age-matched healthy controls. DMN and ECN nodes were split into regions of interest (ROIs), and node-to-node FC analysis was conducted on individual participants. To identify coma pathogenesis, we compared the pairwise FC differences between coma patients and healthy controls. Meanwhile, we divided the traumatic coma patients into different subgroups based on their clinical outcome scores at 6 months postinjury. Considering the awakening prediction, we calculated the area under the curve (AUC) to evaluate the predictive ability of changed FC pairs., Results: We found a massive pairwise FC alteration in the patients with traumatic coma compared to the healthy controls [45% (33/74) pairwise FC located in the DMN, 27% (20/74) pairwise FC located in the ECN, and 28% (21/74) pairwise FC located between the DMN and ECN]. Moreover, in the awake and coma groups, there were 67% (12/18) pairwise FC alterations located in the DMN and 33% (6/18) pairwise FC alterations located between the DMN and ECN. We also indicated that pairwise FC that showed a predictive value of 6-month awakening was mainly located in the DMN rather than in the ECN. Specifically, decreased FC between the right superior frontal gyrus and right parahippocampal gyrus (in the DMN) showed the highest predictive ability (AUC = 0.827)., Conclusion: In the acute phase of severe traumatic brain injury (sTBI), the DMN plays a more prominent role than the ECN and the DMN-ECN interaction in the emergence of traumatic coma and the prediction of 6-month awakening., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)

The authors present an extremely rare case of metastatic brain lesion in a patient with gastrointestinal stromal tumor of the stomach. There are literature data on 23 cases of metastatic lesions of the brain, skull and soft tissues of the head in similar patients. Atypical localization of metastases can lead to some diagnostic difficulties, unreasonable cancellation of chemotherapy and delayed surgical treatment. A feature of our observation was postoperative coma determined by the features of the underlying disease.

Aim: Pathological states of recovery after coma as a result of a severe brain injury are marked with changes in structural connectivity of the brain. This study aimed to identify a topological correlation between white matter integrity and the level of functional and cognitive impairment in patients recovering after coma., Methods: Structural connectomes were computed based on fractional anisotropy maps from 40 patients using a probabilistic human connectome atlas. We used a network based statistics approach to identify potential brain networks associated with a more favorable outcome, assessed with clinical neurobehavioral scores at the patient's discharge from the acute neurorehabilitation unit., Results: We identified a subnetwork whose strength of connectivity correlated with a more favorable outcome as measured with the Disability Rating Scale (network based statistics: t >3.5, P =.010). The subnetwork predominated in the left hemisphere and included the thalamic nuclei, putamen, precentral and postcentral gyri, and medial parietal regions. Spearman correlation between the mean fractional anisotropy value of the subnetwork and the score was ρ = -0.60 (P <.0001). A less extensive overlapping subnetwork correlated with the Coma Recovery Scale Revised score, consisting mostly of the left hemisphere connectivity between the thalamic nuclei and pre- and post-central gyri (network based statistics: t >3.5, P =.033; Spearman's ρ = 0.58, P <.0001)., Conclusion: The present findings suggest an important role of structural connectivity between the thalamus, putamen and somatomotor cortex in the recovery from coma as evaluated with neurobehavioral scores. These structures are part of the motor circuit involved in the generation and modulation of voluntary movement, as well as the forebrain mesocircuit supposedly underlying the maintenance of consciousness. As behavioural assessment of consciousness depends heavily on the signs of voluntary motor behaviour, further work will elucidate whether the identified subnetwork reflects the structural architecture underlying the recovery of consciousness or rather the ability to communicate its content., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objectives: Coma state and loss of consciousness are associated with impaired brain activity, particularly gamma oscillations, that integrate functional connectivity in neural networks, including the default mode network (DMN). Mechanical ventilation (MV) in comatose patients can aggravate brain activity, which has decreased in coma, presumably because of diminished nasal airflow. Nasal airflow, known to drive functional neural oscillations, synchronizing distant brain networks activity, is eliminated by tracheal intubation and MV. Hence, we proposed that rhythmic nasal air puffing in mechanically ventilated comatose patients may promote brain activity and improve network connectivity., Materials and Methods: We recorded electroencephalography (EEG) from 15 comatose patients (seven women) admitted to the intensive care unit because of opium poisoning and assessed the activity, complexity, and connectivity of the DMN before and during the nasal air-puff stimulation. Nasal cavity air puffing was done through a nasal cannula controlled by an electrical valve (open duration of 630 ms) with a frequency of 0.2 Hz (ie, 12 puff/min)., Results: Our analyses demonstrated that nasal air puffing enhanced the power of gamma oscillations (30-100 Hz) in the DMN. In addition, we found that the coherence and synchrony between DMN regions were increased during nasal air puffing. Recurrence quantification and fractal dimension analyses revealed that EEG global complexity and irregularity, typically seen in wakefulness and conscious state, increased during rhythmic nasal air puffing., Conclusions: Rhythmic nasal air puffing, as a noninvasive brain stimulation method, opens a new window to modifying the brain connectivity integration in comatose patients. This approach may potentially influence comatose patients' outcomes by increasing brain reactivity and network connectivity., (Copyright © 2021 International Neuromodulation Society. Published by Elsevier Inc. All rights reserved.)

Background: Despite application of the multimodal European Resuscitation Council and European Society of Intensive Care Medicine algorithm, neurological prognosis of patients who remain comatose after cardiac arrest remains uncertain in a large group of patients. In this study, we investigate the additional predictive value of visual and quantitative brain magnetic resonance imaging (MRI) to electroencephalography (EEG) for outcome estimation of comatose patients after cardiac arrest., Methods: We performed a prospective multicenter cohort study in patients after cardiac arrest submitted in a comatose state to the intensive care unit of two Dutch hospitals. Continuous EEG was recorded during the first 3 days and MRI was performed at 3 ± 1 days after cardiac arrest. EEG at 24 h and ischemic damage in 21 predefined brain regions on diffusion weighted imaging and fluid-attenuated inversion recovery on a scale from 0 to 4 were related to outcome. Quantitative MRI analyses included mean apparent diffusion coefficient (ADC) and percentage of brain volume with ADC < 450 × 10 -6 mm 2 /s, < 550 × 10 -6 mm 2 /s, and < 650 × 10 -6 mm 2 /s. Poor outcome was defined as a Cerebral Performance Category score of 3-5 at 6 months., Results: We included 50 patients, of whom 20 (40%) demonstrated poor outcome. Visual EEG assessment correctly identified 3 (15%) with poor outcome and 15 (50%) with good outcome. Visual grading of MRI identified 13 (65%) with poor outcome and 25 (89%) with good outcome. ADC analysis identified 11 (55%) with poor outcome and 3 (11%) with good outcome. EEG and MRI combined could predict poor outcome in 16 (80%) patients at 100% specificity, and good outcome in 24 (80%) at 63% specificity. Ischemic damage was most prominent in the cortical gray matter (75% vs. 7%) and deep gray nuclei (45% vs. 3%) in patients with poor versus good outcome., Conclusions: Magnetic resonance imaging is complementary with EEG for the prediction of poor and good outcome of patients after cardiac arrest who are comatose at admission., (© 2022. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

Background: There is an unfulfilled need to find the best way to automatically capture, analyze, organize, and merge structural and functional brain magnetic resonance imaging (MRI) data to ultimately extract relevant signals that can assist the medical decision process at the bedside of patients in postanoxic coma. We aimed to develop and validate a deep learning model to leverage multimodal 3D MRI whole-brain times series for an early evaluation of brain damages related to anoxoischemic coma., Methods: This proof-of-concept, prospective, cohort study was undertaken at the intensive care unit affiliated with the University Hospital (Toulouse, France), between March 2018 and May 2020. All patients were scanned in coma state at least 2 days (4 ± 2 days) after cardiac arrest. Over the same period, age-matched healthy volunteers were recruited and included. Brain MRI quantification encompassed both "functional data" from regions of interest (precuneus and posterior cingulate cortex) with whole-brain functional connectivity analysis and "structural data" (gray matter volume, T1-weighted, fractional anisotropy, and mean diffusivity). A specifically designed 3D convolutional neuronal network (CNN) was created to allow conscious state discrimination (coma vs. controls) by using raw MRI indices as the input. A voxel-wise visualization method based on the study of convolutional filters was applied to support CNN outcome. The Ethics Committee of the University Teaching Hospital of Toulouse, France (2018-A31) approved the study and informed consent was obtained from all participants., Results: The final cohort consisted of 29 patients in postanoxic coma and 34 healthy volunteers. Coma patients were successfully discerned from controls by using 3D CNN in combination with different MR indices. The best accuracy was achieved by functional MRI data, in particular with resting-state functional MRI of the posterior cingulate cortex, with an accuracy of 0.96 (range 0.94-0.98) on the test set from 10-time repeated tenfold cross-validation. Even more satisfactory performances were achieved through the majority voting strategy, which was able to compensate for mistakes from single MR indices. Visualization maps allowed us to identify the most relevant regions for each MRI index, notably regions previously described as possibly being involved in consciousness emergence. Interestingly, a posteriori analysis of misclassified patients indicated that they may present some common functional MRI traits with controls, which suggests further favorable outcomes., Conclusions: A fully automated identification of clinically relevant signals from complex multimodal neuroimaging data is a major research topic that may bring a radical paradigm shift in the neuroprognostication of patients with severe brain injury. We report for the first time a successful discrimination between patients in postanoxic coma patients from people serving as controls by using 3D CNN whole-brain structural and functional MRI data. Clinical Trial Number http://ClinicalTrials.gov (No. NCT03482115)., (© 2022. The Author(s).)

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., (© 2021. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

To determine the role of early acquisition of blood oxygen level-dependent (BOLD) signals and diffusion tensor imaging (DTI) for analysis of the connectivity of the ascending arousal network (AAN) in predicting neurological outcomes after acute traumatic brain injury (TBI), cardiopulmonary arrest (CPA), or stroke. A prospective analysis of 50 comatose patients was performed during their ICU stay. Image processing was conducted to assess structural and functional connectivity of the AAN. Outcomes were evaluated after 3 and 6 months. Nineteen patients (38%) had stroke, 18 (36%) CPA, and 13 (26%) TBI. Twenty-three patients were comatose (44%), 11 were in a minimally conscious state (20%), and 16 had unresponsive wakefulness syndrome (32%). Univariate analysis demonstrated that measurements of diffusivity, functional connectivity, and numbers of fibers in the gray matter, white matter, whole brain, midbrain reticular formation, and pontis oralis nucleus may serve as predictive biomarkers of outcome depending on the diagnosis. Multivariate analysis demonstrated a correlation of the predicted value and the real outcome for each separate diagnosis and for all the etiologies together. Findings suggest that the above imaging biomarkers may have a predictive role for the outcome of comatose patients after acute TBI, CPA, or stroke., (© 2021. The Author(s).)

Background: This study aimed to assess the prognostic value regarding neurologic outcome of CT neuroimaging based Gray-White-Matter-Ratio measurement in patients after resuscitation from cardiac arrest., Methods: We retrospectively evaluated CT neuroimaging studies of 91 comatose patients resuscitated from cardiac arrest and 46 non-comatose controls. We tested the diagnostic performance of Gray-White-Matter-Ratio compared with established morphologic signs of hypoxic-ischaemic brain injury, e. g. loss of distinction between gray and white matter, and laboratory parameters, i. e. neuron-specific enolase, for the prediction of poor neurologic outcomes after resuscitated cardiac arrest. Primary endpoint was neurologic function assessed with cerebral performance category score 30 days after the index event., Results: Gray-White-Matter-Ratio showed encouraging interobserver variability (ICC 0.670 [95% CI: 0.592-0.741] compared to assessment of established morphologic signs of hypoxic-ischaemic brain injury (Fleiss kappa 0.389 [95% CI: 0.320-0.457]) in CT neuroimaging studies. It correlated with cerebral performance category score with lower Gray-White-Matter-Ratios associated with unfavourable neurologic outcomes. A cut-off of 1.17 derived from the control population predicted unfavourable neurologic outcomes in adult survivors of cardiac arrest with 100% specificity, 50.3% sensitivity, 100% positive predictive value, and 39.3% negative predictive value. Gray-White-Matter-Ratio prognostic power depended on the time interval between circulatory arrest and CT imaging, with increasing sensitivity the later the image acquisition was executed., Conclusions: A reduced Gray-White-Matter-Ratio is a highly specific prognostic marker of poor neurologic outcomes early after resuscitation from cardiac arrest. Sensitivity seems to be dependent on the time interval between circulatory arrest and image acquisition, with limited value within the first 12 h., (© 2021. The Author(s).)

Background: Late recovery in patients following prolonged coma from carbon monoxide poisoning have been reported, but the probability is unclear. The purpose of this research was to assess the prognosis of patients in prolonged coma after severe carbon monoxide poisoning and related clinical and imaging features., Methods: There were 13 patients who had been in a state of coma for >7 days after acute carbon monoxide poisoning in the retrospective observational study, and demographic data, clinical data, laboratory data, complications, and image data were collected. Outcome was assessed by means of the Glasgow outcome scale after 1 year. The relationship between complications and imaging manifestations and prognosis was also analyzed., Results: One year after severe carbon monoxide poisoning, two patients (15.4%) had died (GOS 1), nine (69.2%) were in a persistent vegetative state (GOS 2), one (7.7%) was moderately disabled (GOS 4), and one (7.7%) achieved a good recovery (GOS 5) with minimal disability., Conclusions: Most patients with prolonged coma after severe carbon monoxide poisoning had a poor prognosis, although the younger patients had a better prognosis. Respiratory failure, hypotension and renal failure during the course of the disease were associated with a poor prognosis. The prognosis of patients with injuries in two sites in early CT was poor. Multiple lesions (≥3) and extensive white matter damage (Fazekas grade (PVH or DWMH) = 3) on MRI of chronic phase were also associated with a poor prognosis.

Background: In patients with severe traumatic brain injury (TBI), coma is associated with impaired subcortical arousal mechanisms. However, it is unknown which nuclei involved in arousal (arousal nuclei) are implicated in coma pathogenesis and are compatible with coma recovery., Methods: We mapped an atlas of arousal nuclei in the brainstem, thalamus, hypothalamus, and basal forebrain onto 3 tesla susceptibility-weighted images (SWI) in 12 patients with acute severe TBI who presented in coma and recovered consciousness within 6 months. We assessed the spatial distribution and volume of SWI microbleeds and evaluated the association of microbleed volume with the duration of unresponsiveness and functional recovery at 6 months., Results: There was no single arousal nucleus affected by microbleeds in all patients. Rather, multiple combinations of microbleeds in brainstem, thalamic, and hypothalamic arousal nuclei were associated with coma and were compatible with recovery of consciousness. Microbleeds were frequently detected in the midbrain (100%), thalamus (83%), and pons (75%). Within the brainstem, the microbleed incidence was largest within the mesopontine tegmentum (e.g., pedunculotegmental nucleus, mesencephalic reticular formation) and ventral midbrain (e.g., substantia nigra, ventral tegmental area). Brainstem arousal nuclei were partially affected by microbleeds, with microbleed volume not exceeding 35% of brainstem nucleus volume on average. Compared to microbleed volume within nonarousal brainstem regions, the microbleed volume within arousal brainstem nuclei accounted for a larger proportion of variance in the duration of unresponsiveness and 6-month Glasgow Outcome Scale-Extended scores., Conclusion: These results suggest resilience of arousal mechanisms in the human brain after severe TBI., (© 2021 American Academy of Neurology.)

Background: Diagnosing brain death (BD) with accuracy and urgency is of great importance because an early diagnosis may guide the clinical management, optimize hospital beds, and facilitate organ transplantation. The clinical diagnosis of nonreactive and irreversible coma can be confirmed with additional tests. Among the complimentary exams that may testify brain circulatory arrest, transcranial Doppler (TCD) can be an option. It is a real-time, bedside, inexpensive, noninvasive method that assesses cerebral blood flow. In patients with suspected BD, especially those who are under sedative drugs, early diagnosis is imperative. The aim of the present study was to evaluate the role of TCD in predicting BD., Methods: One hundred consecutive comatose patients with a Glasgow Coma Scale score of less than 5, owing to different etiologies, were included. TCD was performed in all patients. The TCD operator was blinded for clinical and neurologic data. This study is in compliance with the Declaration of Helsinki., Results: Sixty-nine patients with TCD-brain circulatory collapse were diagnosed later with BD. Of the 31 patients with brain circulatory activity, 8 (25.8%) were clinically brain dead and 23 (74.2%) were alive. TCD showing brain circulatory collapse had a sensitivity of 89.6%, specificity of 100%, positive predictive value of 100%, and negative predictive value of 74.2%., Conclusion: TCD is highly specific (100%) and sensitive (89.6%) as a method to confirm the clinical diagnosis of BD, even in patients under sedation. The possibility of patients presenting with cerebral circulatory activity and clinical diagnosis of BD was demonstrated to occur., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Objective: To examine whether the combination of quantitative regional apparent diffusion coefficient (ADC) and amplitude-integrated electroencephalogram (aEEG) can predict the outcome of comatose patients with severe traumatic brain injury (sTBI)., Methods: A prospective study was conducted. The patients with coma caused by sTBI [Glasgow coma scale (GCS) < 8] admitted to Suqian First Hospital from January 2016 to June 2019 were enrolled. All patients underwent aEEG examination and magnetic resonance imaging (MRI) scan within 1 week after emergency treatment. The ADC values of 9 regions of interest (frontal gray matter and white matter, parietal gray matter and white matter, temporal gray matter and white matter, caudate nucleus of basal ganglia, lenticular nucleus and thalamus) were measured by head MRI, and the mean ADC values of frontal lobe, parietal lobe, temporal lobe and basal ganglia were calculated respectively. According to the follow-up results after 12 months, the differences of each index between patients with poor prognosis [Glasgow outcome score (GOS) 1-2] and patients with good prognosis (GOS 3-5) were compared; the receiver operating characteristic curve (ROC curve) was drawn to evaluate the predictive ability of aEEG and ADC for the good prognosis of patients with sTBI, and the predictive value of the combination of aEEG and ADC., Results: A total of 52 patients with sTBI were enrolled, with mean age of (36.7±13.9) years old, 35 of whom were male. Within 12 months follow-up, 29 patients had achieved favorable outcomes and 23 patients had unfavorable outcome. There were 21, 17 and 14 patients with aEEG, and grade, respectively, and 19, 10 and 0 patients had good prognosis respectively. ADC values of 9 regions of interest in patients with good prognosis were significantly higher than those in patients with poor prognosis (×10 -6 mm 2 /s: 924±107 vs. 531±87 in frontal gray matter, 804±95 vs. 481±74 in frontal white matter, 831±93 vs. 683±72 in temporal gray matter, 726±87 vs. 654±63 in temporal white matter, 767±79 vs. 690±75 in parietal gray matter, 716±84 vs. 642±62 in parietal white matter, 689±70 vs. 465±68 in caudate nucleus, 723±84 vs. 587±71 in lenticular nucleus, 807±79 vs. 497±67 in thalamus, all P < 0.01). ROC curve analysis showed that the area under ROC curve (AUC) of aEEG for predicting good prognosis of sTBI patients was 0.826, when the cut-off value of aEEG was < 1.5, the sensitivity was 94.7% and the specificity was 72.8%. Among the ADC value prediction abilities in the interested areas, the prediction of ADC value in frontal lobe and basal ganglia area were better than that in sTBI patients. AUC was 0.817 and 0.903 respectively. The best cut-off values were > 726×10 -6 mm 2 /s and > 624×10 -6 mm 2 /s respectively, the sensitivity of predicting prognosis were both 100%, and the specificity was 63.4% and 61.8%. A model combining frontal ADC and basal ganglia ADC with aEEG was 91.0% sensitive and 93.7% specific for favorable outcome of sTBI patients., Conclusions: Combination of the quantitative measurement of regional ADC and aEEG may be useful for predicting the outcome of the patients with sTBI.

Objective: We report a case series of patients with prolonged but reversible unconsciousness after coronavirus disease 2019 (COVID-19)-related severe respiratory failure., Methods: A case series of patients who were admitted to the intensive care unit due to COVID-19-related acute respiratory failure is described., Results: After cessation of sedatives, the described cases all showed a prolonged comatose state. Diagnostic neurologic workup did not show signs of devastating brain injury. The clinical pattern of awakening started with early eye opening without obeying commands and persistent flaccid weakness in all cases. Time between cessation of sedatives to the first moment of being fully responsive with obeying commands ranged from 8 to 31 days., Conclusion: Prolonged unconsciousness in patients with severe respiratory failure due to COVID-19 can be fully reversible, warranting a cautious approach for prognostication based on a prolonged state of unconsciousness., (Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

We were to investigate the time course of lesions for awakening in acute Percheron artery ischemic coma (PAIC), which was previously unknown. Patients who had newly identified acute PAIC events in 2012-2015 and had not received thrombolytic therapy were enrolled retrospectively. The time course of lesions in PAIC was investigated by diffusion-weighted imaging (DWI). Ninety-three patients met the inclusion criteria, of whom 63 and 30 had transient PAIC and persistent PAIC, respectively. The time course of awakening events in persistent PAIC decreased over time, with large lesions in the bilateral paramedian thalamus/ rostral midbrain on DWI almost in all patients who was either plus or minus a "top of basilar artery" strokes. Whereas awakening events in transient PAIC increased over time, with small or lacunar lesions in the unilateral or bilateral thalamus/rostral midbrain about in 30.2 % cases, and the rest in naturally recanalization of infarcts or TIA. Lesion volumes were larger for persistent PAIC than for transient PAIC (median, 2.4 cm 3 vs. 0.03 cm 3 , P < 0.0001). In Cox hazards ratio (HR) analysis, a lower GCS score was associated with mortality (HR, 5.5; 95 % confidence interval [CI],1.427-21.45). Multivaliate analysis shown that the predictors of higher risk of persistent PAIC were only increased NIHSS scores (HR,1.3; 95 % CI,1.109-1.640) and large lesions in bilateral thalamus/rostral midbrain (HR,15.0; 95 % CI,1.440-58.13). The time course of acute PAIC included transient and persistent. Most persistent PAIC was associated with large lesions in bilateral paramedian thalamus/ rostral midbrain, and with high mortality., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

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.

Many patients with severe coronavirus disease 2019 (COVID-19) remain unresponsive after surviving critical illness. Although several structural brain abnormalities have been described, their impact on brain function and implications for prognosis are unknown. Functional neuroimaging, which has prognostic significance, has yet to be explored in this population. Here we describe a patient with severe COVID-19 who, despite prolonged unresponsiveness and structural brain abnormalities, demonstrated intact functional network connectivity, and weeks later recovered the ability to follow commands. When prognosticating for survivors of severe COVID-19, clinicians should consider that brain networks may remain functionally intact despite structural injury and prolonged unresponsiveness. ANN NEUROL 2020;88:851-854., (© 2020 American Neurological Association.)

Objectives: Recovery from coma might critically depend on the structural and functional integrity of frontoparietal networks. We aimed to measure this integrity in traumatic brain injury and anoxo-ischemic (cardiac arrest) coma patients by using an original multimodal MRI protocol., Design: Prospective cohort study., Setting: Three Intensive Critical Care Units affiliated to the University in Toulouse (France)., Patients: We longitudinally recruited 43 coma patients (Glasgow Coma Scale at the admission < 8; 29 cardiac arrest and 14 traumatic brain injury) and 34 age-matched healthy volunteers. Exclusion criteria were disorders of consciousness lasting more than 30 days and focal brain damage within the explored brain regions. Patient assessments were conducted at least 2 days (5 ± 2 d) after complete withdrawal of sedation. All patients were followed up (Coma Recovery Scale-Revised) 3 months after acute brain injury., Interventions: None., Measurements and Main Results: Functional and structural MRI data were recorded, and the analysis was targeted on the posteromedial cortex, the medial prefrontal cortex, and the cingulum. Univariate analyses and machine learning techniques were used to assess diagnostic and predictive values. Coma patients displayed significantly lower medial prefrontal cortex-posteromedial cortex functional connectivity (area under the curve, 0.94; 95% CI, 0.93-0.95). Cardiac arrest patients showed specific structural disturbances within posteromedial cortex. Significant cingulum architectural disturbances were observed in traumatic brain injury patients. The machine learning medial prefrontal cortex-posteromedial cortex multimodal classifier had a significant predictive value (area under the curve, 0.96; 95% CI, 0.95-0.97), best combination of subregions that discriminates a binary outcome based on Coma Recovery Scale-Revised)., Conclusions: This exploratory study suggests that frontoparietal functional disconnections are specifically observed in coma and their structural counterpart provides information about brain injury mechanisms. Multimodal MRI biomarkers of frontoparietal disconnection predict 3-month outcome in our sample. These findings suggest that fronto-parietal disconnection might be particularly relevant for coma outcome prediction and could inspire innovative precision medicine approaches.

Predicting outcome in comatose patients after successful cardiopulmonary resuscitation is challenging. Our primary aim was to assess the potential contribution of resting-state-functional magnetic resonance imaging (RS-fMRI) in predicting neurological outcome. RS-fMRI was used to evaluate functional and effective connectivity within the default mode network in a cohort of 90 comatose patients and their impact on functional neurological outcome after 3 months. The RS-fMRI processing protocol comprises the evaluation of functional and effective connectivity within the default mode network. Seed-to-voxel and ROI-to-ROI feature analysis was performed as starting point for a supervised machine-learning approach. Classification of the Cerebral Performance Category (CPC) 1-3 (good to acceptable outcome) versus CPC 4-5 (adverse outcome) achieved a positive predictive value of 91.7%, sensitivity of 90.2%, and accuracy of 87.8%. A direct link to the level of consciousness and outcome after 3 months was identified for measures of segregation in the precuneus, in medial and right frontal regions. Thalamic connectivity appeared significantly reduced in patients without conscious response. Decreased within-network connectivity in the default mode network and within cortico-thalamic circuits correlated with clinical outcome after 3 months. Our results indicate a potential role of these markers for decision-making in comatose patients early after cardiac arrest.

Objectives: Lateral displacement and impaired cerebral autoregulation are associated with worse outcomes following acute brain injury, but their effect on long-term clinical outcomes remains unclear. We assessed the relationship between lateral displacement, disturbances to cerebral autoregulation, and clinical outcomes in acutely comatose patients., Design: Retrospective analysis of prospectively collected data., Setting: Neurocritical care unit of the Johns Hopkins Hospital., Patients: Acutely comatose patients (Glasgow Coma Score ≤ 8)., Interventions: None., Measurements and Main Results: Cerebral oximetry index, derived from near-infrared spectroscopy multimodal monitoring, was used to evaluate cerebral autoregulation. Associations between lateral brain displacement, global cerebral autoregulation, and interhemispheric cerebral autoregulation asymmetry were assessed using mixed random effects models with random intercept. Patients were grouped by functional outcome, determined by the modified Rankin Scale. Associations between outcome group, lateral displacement, and cerebral oximetry index were assessed using multivariate linear regression. Increasing lateral brain displacement was associated with worsening global cerebral autoregulation (p = 0.01 septum; p = 0.05 pineal) and cerebral autoregulation asymmetry (both p < 0.001). Maximum lateral displacement during the first 3 days of coma was significantly different between functional outcome groups at hospital discharge (p = 0.019 pineal; p = 0.008 septum), 3 months (p = 0.026; p = 0.007), 6 months (p = 0.018; p = 0.010), and 12 months (p = 0.022; p = 0.012). Global cerebral oximetry index was associated with functional outcomes at 3 months (p = 0.019) and 6 months (p = 0.013)., Conclusions: During the first 3 days of acute coma, increasing lateral brain displacement is associated with worsening global cerebral autoregulation and cerebral autoregulation asymmetry, and poor long-term clinical outcomes in acutely comatose patients. The impact of acute interventions on outcome needs to be explored.

Super-resolution microscopy techniques are versatile and powerful tools for visualizing organelle structures, interactions, and protein functions in biomedical research. However, whole-cell and tissue specimens challenge the achievable resolution and depth of nanoscopy methods. We focus on three-dimensional single-molecule localization microscopy and review some of the major roadblocks and developing solutions to resolving thick volumes of cells and tissues at the nanoscale in three dimensions. These challenges include background fluorescence, system- and sample-induced aberrations, and information carried by photons, as well as drift correction, volume reconstruction, and photobleaching mitigation. We also highlight examples of innovations that have demonstrated significant breakthroughs in addressing the abovementioned challenges together with their core concepts as well as their trade-offs.

Rationale: We report a stroke patient who showed increased thalamocortical connectivity to the medial prefrontal cortex (mPFC) with recovery of impaired consciousness that was demonstrated on diffusion tensor tractography (DTT) of the ascending reticular activating system (ARAS)., Patients Concerns: A 48-year-old male patient underwent craniectomy and hematoma removal for spontaneous intracerebral hemorrhage in the right basal ganglia and thalamus. When he started rehabilitation at 5 weeks after onset he was in a vegetative state with a Coma Recovery Scale-Revised score of 6., Diagnoses: The patient was diagnosed spontaneous intracerebral hemorrhage in the right basal ganglia and thalamus., Interventions: He underwent comprehensive rehabilitation including neurotropic durgs, transcranial direct current stimulation, and repetitive transcranial magnetic stimulation of the left prefrontal lobe (Brodmann area 10)., Outcomes: After 5 weeks of rehabilitation, the patient had recovered to a nearly normal conscious state with a Coma Recovery Scale-Revised score of 22. On 10-week DTT, thickening of the lower dorsal ARAS was observed on both sides compared with 5-week DTT. Decreased neural connectivity to the left PFC was observed on 5-week DTT whereas decreased neural connectivity to the left PFC was increased on 10-week DTT, especially the mPFC., Lessons: Increased thalamocortical connectivity to the mPFC was demonstrated in a stroke patient who showed concomitant recovery from a vegetative state to a nearly normal conscious state. The results suggest that the increased neural connectivity to the mPMC contributed to recovery of consciousness in this patient.

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 mm 2 /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 mm 2 /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 mm 2 /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., (© 2020 American Academy of Neurology.)

Background: Sepsis-induced brain dysfunction (SIBD) is often encountered in sepsis patients and is related to increased morbidity. No specific tests are available for SIBD, and neuroimaging findings are often normal. In this study, our aim was to analyze the diagnostic value of volumetric analysis of the brain structures and to find out its significance as a prognostic measure., Methods: In this prospective observational study, brain magnetic resonance imaging (MRI) sections of 25 consecutively enrolled SIBD patients (17 with encephalopathy and 8 with coma) and 22 healthy controls underwent volumetric evaluation by an automated segmentation method., Results: Ten SIBD patients had normal MRI, and 15 patients showed brain lesions or atrophy. The most prominent volume reduction was found in cerebral and cerebellar white matter, cerebral cortex, hippocampus, and amygdala, whereas deep gray matter regions and cerebellar cortex were relatively less affected. SIBD patients with normal MRI showed significantly reduced volumes in hippocampus and cerebral white matter. Caudate nuclei, putamen, and thalamus showed lower volume values in non-survivor SIBD patients, and left putamen and right thalamus showed a more pronounced volume reduction in coma patients., Conclusions: Volumetric analysis of the brain appears to be a sensitive measure of volumetric changes in SIBD. Volume reduction in specific deep gray matter regions might be an indicator of unfavorable outcome.

The call to the bedside and the prognostication of a comatose patient-telling family members what to expect-commonly falls to neurologists. The assessment is often confounded by the treatment paradigms of modern intensive care (ie, drugs, drug interactions and targeted temperature management). Patients may be too unstable to leave the intensive care unit for neuroimaging; thus, repeated clinical examinations are decisive. Despite diverse causes, certain principles do apply: (1) Many patients can improve, although with significant abnormalities; (2) Neuroimaging and electrodiagnostic tests can help but are rarely definitive; (3) Secondary involvement of the upper brainstem marks a tipping point with much lower probability for an independent outcome; (4) We rarely predict mortality or diagnose brain death; usually the major concern is anticipated neurological deficits; and (5) Prior comorbidity and permanent organ dysfunction are critical factors in making decisions about de-escalation or escalation of care. This review provides a practical approach to evaluating outcome of a comatose patient. Prognostication is difficult, and we should only attempt it when the diagnosis is confirmed and appropriate (often aggressive) medical or surgical treatment has been tried., Competing Interests: Competing interests: EFMW receives book royalties from Oxford University Press and Elsevier Publishing for authored books on coma, brain death and other issues of critical care neurology., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

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.

Objective: This research is aimed to study the clinical and MRI predictors of coma duration, the intensity of critical care, and outcome of traumatic brain injury (TBI)., Material and Methods: The data from 309 patients with TBI of varying severity were included in the analysis, of whom 257 (86.7%) were treated in the intensive care unit (ICU), including 196 (63.4%) patients admitted in a comatose state lasting longer than 1 day. All patients underwent brain MRI within 21 days after the injury. MRI findings were classified according to MRI grading scale of brain damage level and localization proposed previously., Results: The proposed MRI grading significantly correlated with the Glasgow coma (GCS, r=-0.67; p<0.0001) and Glasgow outcome (0.69; p<0.001) scores in the entire group. In a subgroup of comatose patients (GCS<9) it correlated with coma duration (r=0.52; p<0.0001). Spearman correlation analysis showed a significant relationship between the MRI classification and a number of parameters: ICU length of stay (r=0.62; p<0.0001), the duration of artificial ventilation (r=0.47; p<0.0001), the rate of artificial ventilation, sedatives, analgesics, mannitol, hypertonic saline and vasopressors usage (p<0.01). These data confirm the relationship between higher grades of MRI classification (deep brain damage) and the need for the escalation of intensive care main components., Conclusion: Our results support the hypothesis that the levels and localization of brain damage, estimated by the proposed MRI grading scale, might be predictors of coma duration, intensity and duration of intensive care, and TBI outcomes. A prognosis based on clinical and neuroimaging data comparison can be valuable for planning and efficient use of the hospital beds and ICU resources, for optimizing the patient flow and timing of patient transfer to neurorehabilitation facilities.

Prognostication for comatose patients after cardiac arrest is a difficult but essential task. Currently, visual interpretation of electroencephalogram (EEG) is one of the main modality used in outcome prediction. There is a growing interest in computer-assisted EEG interpretation, either to overcome the possible subjectivity of visual interpretation, or to identify complex features of the EEG signal. We used a one-dimensional convolutional neural network (CNN) to predict functional outcome based on 19-channel-EEG recorded from 267 adult comatose patients during targeted temperature management after CA. The area under the receiver operating characteristic curve (AUC) on the test set was 0.885. Interestingly, model architecture and fine-tuning only played a marginal role in classification performance. We then used gradient-weighted class activation mapping (Grad-CAM) as visualization technique to identify which EEG features were used by the network to classify an EEG epoch as favorable or unfavorable outcome, and also to understand failures of the network. Grad-CAM showed that the network relied on similar features than classical visual analysis for predicting unfavorable outcome (suppressed background, epileptiform transients). This study confirms that CNNs are promising models for EEG-based prognostication in comatose patients, and that Grad-CAM can provide explanation for the models' decision-making, which is of utmost importance for future use of deep learning models in a clinical setting., (© 2019 Wiley Periodicals, Inc.)

Background: Electroencephalography (EEG) is commonly used to assess the neurological prognosis of comatose patients after cardiac arrest (CA). However, the early prognostic accuracy of EEG may be affected by postresuscitation interventions. Recent animal studies found that hydrogen inhalation after CA greatly improved neurological outcomes by selectively neutralizing highly reactive oxidants, but the effect of hydrogen inhalation on EEG recovery and its prognostication value are still unclear. The present study investigated the effects of hydrogen inhalation on early postresuscitation EEG characteristics in an asphyxial CA rat model., Methods: Cardiopulmonary resuscitation was initiated after 5 min of untreated CA in 40 adult female Sprague-Dawley rats. Animals were randomized for ventilation with 98% oxygen plus 2% hydrogen (H2) or 98% oxygen plus 2% nitrogen (Ctrl) under normothermia for 1 h. EEG characteristics were continuously recorded for 4 h, and the relationships between quantitative EEG characteristics and 96 h neurological outcomes were investigated., Results: No differences in baseline and resuscitation data were observed between groups, but the survival rate was significantly higher in the H2 group than in the Ctrl group (90% vs. 40%, P < 0.01). Compared to the Ctrl group, the H2 group showed a shorter burst onset time (21.85 [20.00-23.38] vs. 25.70 [22.48-30.05], P < 0.01) and time to normal trace (169.83 [161.63-208.55] vs. 208.39 [186.29-248.80], P < 0.01). Additionally, the burst suppression ratio (0.66 ± 0.09 vs. 0.52 ± 0.17, P < 0.01) and weighted-permutation entropy (0.47 ± 0.16 vs. 0.34 ± 0.13, P < 0.01) were markedly higher in the H2 group. The areas under the receiver operating characteristic curves for the 4 EEG characteristics in predicting survival were 0.82, 0.84, 0.88, and 0.83, respectively., Conclusions: In this asphyxial CA rat model, the improved postresuscitation EEG characteristics for animals treated with hydrogen are correlated with the better 96 h neurological outcome and predicted survival., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2019 Gang Chen et al.)

Increased intracranial pressure has successfully been detected by using bedside optic nerve sheath diameter (ONSD) ultrasonography. ONSD ultrasonography has become one of the current methods used to detect potential brain death in recent years. In this study, we carried out ONSD ultrasonography for patients who were diagnosed with brain death and in comatose state. Mean ONSD values obtained from the patients with brain death were compared with ONSD values of patients in a comatose state. There was no significant difference between the mean ONSD values of the right and left eye and no significant difference in transverse and sagittal plane measurements in all groups. Mean ONSD values of Group BD were significantly higher than both Group CT (P < .05) and Group CM values (P < .05). Some of the patients with a history of intracranial hemorrhage, subdural hematoma, or traumatic brain injuries who remain in a comatose state in intensive care units may ultimately result in brain death. Therefore, it may be kept in mind that intermittent ONSD measurements of patients in deep comas might have an important role for diagnosing brain death early for purposes of cadaveric organ donation. In conclusion, transorbital ONSD measurement using bedside ultrasonography, an inexpensive, comfortable, and noninvasive test for patients in deep comas, may be helpful in determining potential brain death., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Despite the association between brainstem lesions and coma, a mechanistic understanding of coma pathogenesis and recovery is lacking. We developed a coma model in the rat mimicking human brainstem coma, which allowed multimodal analysis of a brainstem tegmentum lesion's effects on behavior, cortical electrophysiology, and global brain functional connectivity. After coma induction, we observed a transient period (∼1h) of unresponsiveness accompanied by cortical burst-suppression. Comatose rats then gradually regained behavioral responsiveness concurrent with emergence of delta/theta-predominant cortical rhythms in primary somatosensory cortex. During the acute stage of coma recovery (∼1-8h), longitudinal resting-state functional MRI revealed an increase in functional connectivity between subcortical arousal nuclei in the thalamus, basal forebrain, and basal ganglia and cortical regions implicated in awareness. This rat coma model provides an experimental platform to systematically study network-based mechanisms of coma pathogenesis and recovery, as well as to test targeted therapies aimed at promoting recovery of consciousness after coma., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Purpose: The density ratio of gray matter (GM) to white matter (WM) on brain computed tomography (CT) (gray-to-white matter ratio, GWR) helps predict the prognosis of comatose patients after cardiac arrest. However, Hounsfield units (HU) are not an absolute value and can change based on imaging parameters and CT scanners. We compared the density of brain GM and WM and the GWR by using images scanned with different types of CT machines., Method: 102 patients with normal readings who were scanned using three types of CT scanners were included in the study. HU were measured at the basal ganglia level by two observers with circular regions of interest., Result: The difference in GM was 0.98-10.30 HU and WM was 1.05-7.55 HU. The mean value of measured HU and GWR were different for each CT group. The ANOVA test showed significant difference all variables. The post hoc test for GWR, which was used to compare the differences between each scanner, was statistically significant. Interclass correlation coefficients of measured GM and WM between the two observers were very high (Cronbach's α=0.995 and 0.990, respectively) and GWR was showed good confidence level (0.798)., Conclusion: In this study, the HU values of GM and WM in the normal adult brain differed up to 23% among scanners. Unfortunately, the GWR may not compensate for the HU difference between GM and WM occurring between scanners. Therefore, rather than applying consistent GWR cut-offs, the protocol or manufacturer differences between imaging scanners should be considered., (Copyright © 2018 Elsevier Inc. All rights reserved.)