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Although evaluation of disorders of consciousness (DoC) following brain injury has traditionally relied on bedside behavioral examination, advances in neurotechnology have elucidated novel approaches to detecting and predicting recovery of consciousness. Professional society guidelines now recommend that clinicians integrate these neurotechnologies into clinical practice as part of multimodal evaluations for some patients with DoC but have not crafted concrete protocols for this translation. Little is known about the experiences and ethical perspectives held by key stakeholder groups around the clinical implementation of advanced neurotechnologies to detect and predict recovery of consciousness. Recognizing this knowledge gap, the Data-Driven Neuroethics for Consciousness Detection (DECODE) survey examined clinicians' perspectives on advanced neurotechnologies for DoC care, including access to and rates of adoption, perceived utility, facilitators and barriers to adoption in clinical settings, ethical considerations surrounding clinical implementation, and challenges encountered in ensuring care for patients with acute and prolonged DoC. Mixed-methods analysis including qualitative analysis, grounded theory methodology, and ethical analysis was employed to assess responses and key themes. Ninety-two clinicians consented to the survey. More than 70% believed that standard bedside behavioral examination is insufficient, and nearly 60% viewed advanced neurotechnologies as integral in optimal DoC evaluation. Training gaps and limited institutional infrastructure were identified as salient barriers to clinical implementation. Thematic analysis revealed concerns about the interpretation of results, impact on surrogates, and validity of test results. Ethical themes of prognostic uncertainty, nihilism, and access also permeated multiple domains. Considerations surrounding access, knowledge base, results interpretation, and communication with surrogates are cross-cutting ethical threads shaping the clinical translation of advanced neurotechnologies for DoC. These components represent opportunities for implementation science work focused on democratizing access to neurotechnologies, educating clinicians on the use of novel techniques and interpretation of results, conducting multisite validation studies, and standardizing approaches to communicating test results., (© 2024. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

Disorders of consciousness (DoC) are states of impaired arousal or awareness. Deep brain stimulation (DBS) is a potential treatment, but outcomes vary, possibly due to differences in patient characteristics, electrode placement, or stimulation of specific brain networks. We studied 40 patients with DoC who underwent DBS targeting the thalamic centromedian-parafascicular complex. Better-preserved gray matter, especially in the striatum, correlated with consciousness improvement. Stimulation was most effective when electric fields extended into parafascicular and subparafascicular nuclei-ventral to the centromedian nucleus, near the midbrain-and when it engaged projection pathways of the ascending arousal network, including the hypothalamus, brainstem, and frontal lobe. Moreover, effective DBS sites were connected to networks similar to those underlying impaired consciousness due to generalized absence seizures and acquired lesions. These findings support the therapeutic potential of DBS for DoC, emphasizing the importance of precise targeting and revealing a broader link between effective DoC treatment and mechanisms underlying other conscciousness-impairing conditions., Competing Interests: COMPETING INTERESTS AELW, MR, HF, FLWVJS, JT, SBS, JL, MMJC, KB, MUF, RJ, JEI, PWC, DF, ADB, BLE, and DC have no competing interests to report. MDF has intellectual property on the use of brain connectivity imaging to analyze lesions and guide brain stimulation, has consulted for Magnus Medical, Soterix, Abbott, Boston Scientific, and Tal Medical, and has received research funding from Neuronetics. AH reports lecture fees for Boston Scientific and is a consultant for Neuromodulation and Abbott. JDR has received past consulting payments from Medtronic, Corlieve, ClearPoint, Medtronic, and NeuroPace, and currently consults for Turing Medical.

While substantial progress has been made in mapping the connectivity of cortical networks responsible for conscious awareness, neuroimaging analysis of subcortical arousal networks that modulate arousal (i.e., wakefulness) has been limited by a lack of a robust segmentation procedures for brainstem arousal nuclei. Automated segmentation of brainstem arousal nuclei is an essential step toward elucidating the physiology of arousal in human consciousness and the pathophysiology of disorders of consciousness. We created a probabilistic atlas of brainstem arousal nuclei built on diffusion MRI scans of five ex vivo human brain specimens scanned at 750 μm isotropic resolution. Labels of arousal nuclei used to generate the probabilistic atlas were manually annotated with reference to nucleus-specific immunostaining in two of the five brain specimens. We then developed a Bayesian segmentation algorithm that utilizes the probabilistic atlas as a generative model and automatically identifies brainstem arousal nuclei in a resolution- and contrast-agnostic manner. The segmentation method displayed high accuracy in both healthy and lesioned in vivo T1 MRI scans and high test-retest reliability across both T1 and T2 MRI contrasts. Finally, we show that the segmentation algorithm can detect volumetric changes and differences in magnetic susceptibility within brainstem arousal nuclei in Alzheimer's disease and traumatic coma, respectively. We release the probabilistic atlas and Bayesian segmentation tool in FreeSurfer to advance the study of human consciousness and its disorders.

Alpha (8-12 Hz) frequency band oscillations are among the most informative features in electroencephalographic (EEG) assessment of patients with disorders of consciousness (DoC). Because interareal alpha synchrony is thought to facilitate long-range communication in healthy brains, coherence measures of resting-state alpha oscillations may provide insights into a patient's capacity for higher-order cognition beyond channel-wise estimates of alpha power. In multi-channel EEG, global coherence methods may be used to augment standard spectral analysis methods by both estimating the strength and identifying the structure of coherent oscillatory networks. We performed global coherence analysis in 95 separate clinical EEG recordings (28 healthy controls and 33 patients with acute or chronic DoC, 25 of whom returned for follow-up) collected between two academic medical centers. We found that posterior alpha coherence is associated with recovery of higher-level cognition. We developed a measure of network organization, based on the distance between eigenvectors of the alpha cross-spectral matrix, that detects recovery of posterior alpha networks. In patients who have emerged from a minimally conscious state, we showed that coherence-based alpha networks are reconfigured prior to restoration of alpha power to resemble those seen in healthy controls. This alpha network measure performs well in classifying recovery from DoC (AUC = 0.78) compared to common representations of functional connectivity using the weighted phase lag index (AUC = 0.50 - 0.57). Lastly, we observed that activity within these alpha networks is suppressed during positive responses to task-based EEG command-following paradigms, supporting the potential utility of this biomarker to detect covert cognition. Our findings suggest that restored alpha networks may represent a sensitive early signature of cognitive recovery in patients with DoC. Therefore, network detection methods may augment the utility of EEG assessments for DoC., Competing Interests: Disclosures The authors declare no competing interests. The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Research Council Executive Agency (ERCEA) and the European Commission.

Subcortical arousal systems are known to play a key role in controlling sustained changes in attention and conscious awareness. Recent studies indicate that these systems have a major influence on short-term dynamic modulation of visual attention, but their role across sensory modalities is not fully understood. In this study, we investigated shared subcortical arousal systems across sensory modalities during transient changes in attention using block and event-related fMRI paradigms. We analyzed massive publicly available fMRI datasets collected while 1,561 participants performed visual, auditory, tactile, and taste perception tasks. Our analyses revealed a shared circuit of subcortical arousal systems exhibiting early transient increases in activity in midbrain reticular formation and central thalamus across perceptual modalities, as well as less consistent increases in pons, hypothalamus, basal forebrain, and basal ganglia. Identifying these networks is critical for understanding mechanisms of normal attention and consciousness and may help facilitate subcortical targeting for therapeutic neuromodulation.

Among patients with severe traumatic brain injury (TBI), there is high prognostic uncertainty but growing evidence that recovery of independence is possible. Nevertheless, families are often asked to make decisions about withdrawal of life-sustaining treatment (WLST) within days of injury. The range of potential outcomes for patients who died after WLST (WLST+) is unknown, posing a challenge for prognostic modeling and clinical counseling. We investigated the potential for survival and recovery of independence after acute TBI in patients who died after WLST. We used Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) data and propensity score matching to pair participants with WLST+ to those with a similar probability of WLST (based on demographic and clinical characteristics), but for whom life-sustaining treatment was not withdrawn (WLST-). To optimize matching, we divided the WLST- cohort into tiers (Tier 1 = 0-11%, Tier 2 = 11-27%, Tier 3 = 27-70% WLST propensity). We estimated the level of recovery that could be expected in WLST+ participants by evaluating 3-, 6-, and 12-month Glasgow Outcome Scale-Extended (GOSE) and Disability Rating Scale outcomes in matched WLST- participants. Of 90 WLST+ participants (80% male, mean [standard deviation; SD] age = 59.2 [17.9] years, median [IQR] days to WLST = 5.4 [2.2, 11.7]), 80 could be matched to WLST- participants. Of 56 WLST- participants who were followed at 6 months, 31 (55%) died. Among survivors in the overall sample and survivors in Tiers 1 and 2, more than 30% recovered at least partial independence (GOSE ≥4). In Tier 3, recovery to GOSE ≥4 occurred at 12 months, but not 6 months, post-injury. These results suggest a substantial proportion of patients with TBI and WLST may have survived and achieved at least partial independence. However, death or severe disability is a common outcome when the probability of WLST is high. While further validation is needed, our findings support a more cautious clinical approach to WLST and more complete reporting on WLST in TBI studies.

Objective: To determine, in persons with traumatic brain injury (TBI), the association between cognitive change after inpatient rehabilitation discharge and 1-year participation and life satisfaction outcomes., Design: Secondary analysis of prospectively collected TBI Model Systems (TBIMS) data., Setting: Inpatient rehabilitation and community., Participants: 499 individuals with TBI requiring inpatient rehabilitation who completed the Brief Test of Adult Cognition by Telephone (BTACT) at inpatient rehabilitation discharge (ie, baseline) and 1-year postinjury., Main Outcome Measures: Participation Assessment with Recombined Tools-Objective (PART-O) and Satisfaction with Life Scale (SWLS)., Results: Of 2,840 TBIMS participants with baseline BTACT, 499 met inclusion criteria (mean [standard deviation] age = 45 [19] years; 72% male). Change in BTACT executive function (EF) was not associated with 1-year participation (PART-O; β = 0.087, 95% CI [-0.004, 0.178], P = .061) when it was the sole model predictor. Change in BTACT episodic memory (EM) was associated with 1-year participation (β = 0.096, [0.007, 0.184], P = .035), but not after adjusting for demographic, clinical, and functional status covariates (β = 0.067, 95% CI [-0.010, 0.145], P = .089). Change in BTACT EF was not associated with life satisfaction total scores (SWLS) when it was the sole model predictor (β = 0.091, 95% CI [-0.001, 0.182], P = .0503). Change in BTACT EM was associated with 1-year life satisfaction before (β = 0.114, 95% CI [0.025, 0.202], P = .012) and after adjusting for covariates (β = 0.103, [0.014, 0.191], P = .023). In secondary analyses, change in BTACT EF was associated with PART-O Social Relations and Out and About subdomains before (Social Relations: β = 0.127, 95% CI [0.036, 0.217], P = .006; Out and About: β = 0.141, 95% CI [0.051, 0.232], P = .002) and after (Social Relations: β = 0.168, 95% CI [0.072, 0.265], P < .002; Out and About: β = 0.156, 95% CI [0.061, 0.252], P < .002) adjusting for functional status and further adjusting for covariates (Social Relations: β = 0.127, 95% CI [0.040, 0.214], P = .004; Out and About: β = 0.136, 95% CI [0.043, 0.229], P = .004). However, only the models adjusting for functional status remained significant after multiple comparison correction (ie, Bonferroni-adjusted alpha level = 0.002)., Conclusion: EF gains during the first year after TBI were related to 1-year social and community participation. Gains in EM were associated with 1-year life satisfaction. These results highlight the potential benefit of cognitive rehabilitation after inpatient rehabilitation discharge and the need for interventions targeting specific cognitive functions that may contribute to participation and life satisfaction after TBI., Competing Interests: The authors declare no conflicts of interests., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Magnetic resonance imaging (MRI) is the standard tool to image the human brain in vivo. In this domain, digital brain atlases are essential for subject-specific segmentation of anatomical regions of interest (ROIs) and spatial comparison of neuroanatomy from different subjects in a common coordinate frame. High-resolution, digital atlases derived from histology (e.g., Allen atlas [7], BigBrain [13], Julich [15]), are currently the state of the art and provide exquisite 3D cytoarchitectural maps, but lack probabilistic labels throughout the whole brain. Here we present NextBrain, a next-generation probabilistic atlas of human brain anatomy built from serial 3D histology and corresponding highly granular delineations of five whole brain hemispheres. We developed AI techniques to align and reconstruct ~10,000 histological sections into coherent 3D volumes with joint geometric constraints (no overlap or gaps between sections), as well as to semi-automatically trace the boundaries of 333 distinct anatomical ROIs on all these sections. Comprehensive delineation on multiple cases enabled us to build the first probabilistic histological atlas of the whole human brain. Further, we created a companion Bayesian tool for automated segmentation of the 333 ROIs in any in vivo or ex vivo brain MRI scan using the NextBrain atlas. We showcase two applications of the atlas: automated segmentation of ultra-high-resolution ex vivo MRI and volumetric analysis of Alzheimer's disease and healthy brain ageing based on ~4,000 publicly available in vivo MRI scans. We publicly release: the raw and aligned data (including an online visualisation tool); the probabilistic atlas; the segmentation tool; and ground truth delineations for a 100 μm isotropic ex vivo hemisphere (that we use for quantitative evaluation of our segmentation method in this paper). By enabling researchers worldwide to analyse brain MRI scans at a superior level of granularity without manual effort or highly specific neuroanatomical knowledge, NextBrain holds promise to increase the specificity of MRI findings and ultimately accelerate our quest to understand the human brain in health and disease., Competing Interests: Competing interests The authors have no relevant financial or non-financial interests to disclose.

Objectives: For critically ill patients with acute severe brain injuries, consciousness may reemerge before behavioral responsiveness. The phenomenon of covert consciousness (i.e., cognitive motor dissociation) may be detected by advanced neurotechnologies such as task-based functional MRI (fMRI) and electroencephalography (EEG) in patients who appear unresponsive on the bedside behavioral examination. In this narrative review, we summarize the state-of-the-science in ICU detection of covert consciousness. Further, we consider the prognostic and therapeutic implications of diagnosing covert consciousness in the ICU, as well as its potential to inform discussions about continuation of life-sustaining therapy for patients with severe brain injuries., Data Sources: We reviewed salient medical literature regarding covert consciousness., Study Selection: We included clinical studies investigating the diagnostic performance characteristics and prognostic utility of advanced neurotechnologies such as task-based fMRI and EEG. We focus on clinical guidelines, professional society scientific statements, and neuroethical analyses pertaining to the implementation of advanced neurotechnologies in the ICU to detect covert consciousness., Data Extraction and Data Synthesis: We extracted study results, guideline recommendations, and society scientific statement recommendations regarding the diagnostic, prognostic, and therapeutic relevance of covert consciousness to the clinical care of ICU patients with severe brain injuries., Conclusions: Emerging evidence indicates that covert consciousness is present in approximately 15-20% of ICU patients who appear unresponsive on behavioral examination. Covert consciousness may be detected in patients with traumatic and nontraumatic brain injuries, including patients whose behavioral examination suggests a comatose state. The presence of covert consciousness in the ICU may predict the pace and extent of long-term functional recovery. Professional society guidelines now recommend assessment of covert consciousness using task-based fMRI and EEG. However, the clinical criteria for patient selection for such investigations are uncertain and global access to advanced neurotechnologies is limited., (Copyright © 2024 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Background: Cognitive motor dissociation (CMD) occurs when patients with severe brain injury follow commands on task-based functional MRI or EEG assessment despite demonstrating no behavioral evidence of language function. Recognizing the value of identifying patients with CMD, evidence-based guidelines published in the United States and Europe now recommend that these assessments are conducted as part of clinical care for select patients., Recent Findings: We describe our institutionally supported approach for clinical assessment of CMD and report lessons learned so that other centers can more easily implement these evaluations. Among the key lessons are the need to consider ethical implications of CMD assessment; establish standardized local protocols for patient selection, data acquisition, analysis, and interpretation; and develop effective strategies for communication of test results., Implications for Practice: Independent validation of methods to assess CMD is not available. Our approach for clinical CMD assessment is intended to be flexible, allowing for iterative improvements as the evidence base grows., Competing Interests: Y.G. Bodien, M. Fecchio, H.J. Freeman, W.R. Sanders, A. Meydan, P.K. Lawrence, M.J. Young, B.L. Edlow were funded by the MGH Department of Neurology and NIH Director's Office (DP2 HD101400). B.L. Edlow was funded by the Chen Institute MGH Research Scholar Award. J.E. Kirsch, D. Fischer, J. Cohen, E. Rubin, J.H. He, P.W. Schaefer, J.T. Giacino, L.R. Hochberg, O. Rapalino, S.S. Cash have no disclosures related to this work. Full disclosure form information provided by the authors is available with the full text of this article at Neurology.org/cp., (© 2024 American Academy of Neurology.)

Surface-based cortical registration is an important topic in medical image analysis and facilitates many downstream applications. Current approaches for cortical registration are mainly driven by geometric features, such as sulcal depth and curvature, and often assume that registration of folding patterns leads to alignment of brain function. However, functional variability of anatomically corresponding areas across subjects has been widely reported, particularly in higher-order cognitive areas. In this work, we present JOSA, a novel cortical registration framework that jointly models the mismatch between geometry and function while simultaneously learning an unbiased population-specific atlas. Using a semi-supervised training strategy, JOSA achieves superior registration performance in both geometry and function to the state-of-the-art methods but without requiring functional data at inference. This learning framework can be extended to any auxiliary data to guide spherical registration that is available during training but is difficult or impossible to obtain during inference, such as parcellations, architectonic identity, transcriptomic information, and molecular profiles. By recognizing the mismatch between geometry and function, JOSA provides new insights into the future development of registration methods using joint analysis of brain structure and function., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: GT was financially supported by the Amazon Fellowship from the Science Hub, administered by the MIT Schwarzman College of Computing, and the International Doctoral Fellowship from the American Association of University Women. EF, BLE, and BF report financial support was provided by National Institutes of Health. EF reports additional financial support from the McGovern Institute for Brain Research, the Brain and Cognitive Sciences Department, the Simons Center for the Social Brain and MIT’s Quest for Intelligence. BLE reports additional financial support from the James S. McDonnell Foundation and the Chen Institute MGH Research Scholar Award. BF is an advisor to DeepHealth, a company whose medical pursuits focus on medical imaging and measurement technologies. BF’s interests were reviewed and are managed by Massachusetts General Hospital and Partners HealthCare in accordance with their conflict of interest policies., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Patients with brain injury who are unresponsive to commands may perform cognitive tasks that are detected on functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). This phenomenon, known as cognitive motor dissociation, has not been systematically studied in a large cohort of persons with disorders of consciousness., Methods: In this prospective cohort study conducted at six international centers, we collected clinical, behavioral, and task-based fMRI and EEG data from a convenience sample of 353 adults with disorders of consciousness. We assessed the response to commands on task-based fMRI or EEG in participants without an observable response to verbal commands (i.e., those with a behavioral diagnosis of coma, vegetative state, or minimally conscious state-minus) and in participants with an observable response to verbal commands. The presence or absence of an observable response to commands was assessed with the use of the Coma Recovery Scale-Revised (CRS-R)., Results: Data from fMRI only or EEG only were available for 65% of the participants, and data from both fMRI and EEG were available for 35%. The median age of the participants was 37.9 years, the median time between brain injury and assessment with the CRS-R was 7.9 months (25% of the participants were assessed with the CRS-R within 28 days after injury), and brain trauma was an etiologic factor in 50%. We detected cognitive motor dissociation in 60 of the 241 participants (25%) without an observable response to commands, of whom 11 had been assessed with the use of fMRI only, 13 with the use of EEG only, and 36 with the use of both techniques. Cognitive motor dissociation was associated with younger age, longer time since injury, and brain trauma as an etiologic factor. In contrast, responses on task-based fMRI or EEG occurred in 43 of 112 participants (38%) with an observable response to verbal commands., Conclusions: Approximately one in four participants without an observable response to commands performed a cognitive task on fMRI or EEG as compared with one in three participants with an observable response to commands. (Funded by the James S. McDonnell Foundation and others.)., (Copyright © 2024 Massachusetts Medical Society.)

The accurate measurement of three-dimensional (3D) fiber orientation in the brain is crucial for reconstructing fiber pathways and studying their involvement in neurological diseases. Comprehensive reconstruction of axonal tracts and small fascicles requires high-resolution technology beyond the ability of current in vivo imaging (e.g. diffusion magnetic resonance imaging). Optical imaging methods such as polarization-sensitive optical coherence tomography (PS-OCT) and polarization microscopy can quantify fiber orientation at micrometer resolution but have been limited to two-dimensional in-plane orientation or thin slices, preventing the comprehensive study of connectivity in 3D. In this work we present a novel method to quantify volumetric 3D orientation in full angular space with PS-OCT. We measure the polarization contrasts of the brain sample from two illumination angles of 0 and 15 degrees and apply a computational method that yields the 3D optic axis orientation and true birefringence. We further present 3D fiber orientation maps of entire coronal cerebrum sections and brainstem with 10 μm in-plane resolution, revealing unprecedented details of fiber configurations. We envision that our method will open a promising avenue towards large-scale 3D fiber axis mapping in the human brain as well as other complex fibrous tissues at microscopic level., Competing Interests: Disclosures B.F. is a medical advisor to DeepHealth, a company whose medical pursuits focus on imaging and measurement technologies. B.F.’s interests were reviewed and are managed by MGH and Partners HealthCare in accordance with their conflict-of-interest policies. Additional Declarations: Competing interest reported. B.F. is a medical advisor to DeepHealth, a company whose medical pursuits focus on imaging and measurement technologies. B.F.’s interests were reviewed and are managed by MGH and Partners HealthCare in accordance with their conflict-of-interest policies.

For the human brain to operate, populations of neurons across anatomical structures must coordinate their activity within milliseconds. To date, our understanding of such interactions has remained limited. We recorded directly from the hippocampus (HPC), posteromedial cortex (PMC), ventromedial/orbital prefrontal cortex (OFC), and the anterior nuclei of the thalamus (ANT) during two experiments of autobiographical memory processing that are known from decades of neuroimaging work to coactivate these regions. In 31 patients implanted with intracranial electrodes, we found that the presentation of memory retrieval cues elicited a significant increase of low frequency (LF < 6 Hz) activity followed by cross-regional phase coherence of this LF activity before select populations of neurons within each of the four regions increased high-frequency (HF > 70 Hz) activity. The power of HF activity was modulated by memory content, and its onset followed a specific temporal order of ANT→HPC/PMC→OFC. Further, we probed cross-regional causal effective interactions with repeated electrical pulses and found that HPC stimulations cause the greatest increase in LF-phase coherence across all regions, whereas the stimulation of any region caused the greatest LF-phase coherence between that particular region and ANT. These observations support the role of the ANT in gating, and the HPC in synchronizing, the activity of cortical midline structures when humans retrieve self-relevant memories of their past. Our findings offer a fresh perspective, with high temporal fidelity, about the dynamic signaling and underlying causal connections among distant regions when the brain is actively involved in retrieving self-referential memories from the past., Competing Interests: Competing interests statement:The authors declare no competing interest.

Importance: Because withdrawal of life-sustaining therapy based on perceived poor prognosis is the most common cause of death after moderate or severe traumatic brain injury (TBI), the accuracy of clinical prognoses is directly associated with mortality. Although the location of brain injury is known to be important for determining recovery potential after TBI, the best available prognostic models, such as the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) score, do not currently incorporate brain injury location., Objective: To test whether automated measurement of cerebral hemorrhagic contusion size and location is associated with improved prognostic performance of the IMPACT score., Design, Setting, and Participants: This prognostic cohort study was performed in 18 US level 1 trauma centers between February 26, 2014, and August 8, 2018. Adult participants aged 17 years or older from the US-based Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) study with moderate or severe TBI (Glasgow Coma Scale score 3-12) and contusions detected on brain computed tomography (CT) scans were included. The data analysis was performed between January 2023 and February 2024., Exposures: Labeled contusions detected on CT scans using Brain Lesion Analysis and Segmentation Tool for Computed Tomography (BLAST-CT), a validated artificial intelligence algorithm., Main Outcome and Measure: The primary outcome was a Glasgow Outcome Scale-Extended (GOSE) score of 4 or less at 6 months after injury. Whether frontal or temporal lobe contusion volumes improved the performance of the IMPACT score was tested using logistic regression and area under the receiver operating characteristic curve comparisons. Sparse canonical correlation analysis was used to generate a disability heat map to visualize the strongest brainwide associations with outcomes., Results: The cohort included 291 patients with moderate or severe TBI and contusions (mean [SD] age, 42 [18] years; 221 [76%] male; median [IQR] emergency department arrival Glasgow Coma Scale score, 5 [3-10]). Only temporal contusion volumes improved the discrimination of the IMPACT score (area under the receiver operating characteristic curve, 0.86 vs 0.84; P = .03). The data-derived disability heat map of contusion locations showed that the strongest association with unfavorable outcomes was within the bilateral temporal and medial frontal lobes., Conclusions and Relevance: These findings suggest that CT-based automated contusion measurement may be an immediately translatable strategy for improving TBI prognostic models.

Advances over the past two decades in functional neuroimaging have provided new diagnostic and prognostic tools for patients with severe brain injury. Some of the most pertinent developments in this area involve the assessment of residual brain function in patients in the intensive care unit during the acute phase of severe injury, when they are at their most vulnerable and prognosis is uncertain. Advanced neuroimaging techniques, such as functional MRI and EEG, have now been used to identify preserved cognitive processing, including covert conscious awareness, and to relate them to outcome in patients who are behaviourally unresponsive. Yet, technical and logistical challenges to clinical integration of these advanced neuroimaging techniques remain, such as the need for specialised expertise to acquire, analyse, and interpret data and to determine the appropriate timing for such assessments. Once these barriers are overcome, advanced functional neuroimaging technologies could improve diagnosis and prognosis for millions of patients worldwide., Competing Interests: Declaration of interests KK and BLE declare no conflicts of interest. AMO is the Chief Scientific Officer of Creyos, a company that provides online neuropsychological assessments for various conditions such as Parkinson's disease, Alzheimer's disease, and amyotrophic lateral sclerosis. The activities of the company have no overlap whatsoever with the content of this Personal View., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

Background: We developed a gap analysis that examines the role of brain-computer interfaces (BCI) in patients with disorders of consciousness (DoC), focusing on their assessment, establishment of communication, and engagement with their environment., Methods: The Curing Coma Campaign convened a Coma Science work group that included 16 clinicians and neuroscientists with expertise in DoC. The work group met online biweekly and performed a gap analysis of the primary question., Results: We outline a roadmap for assessing BCI readiness in patients with DoC and for advancing the use of BCI devices in patients with DoC. Additionally, we discuss preliminary studies that inform development of BCI solutions for communication and assessment of readiness for use of BCIs in DoC study participants. Special emphasis is placed on the challenges posed by the complex pathophysiologies caused by heterogeneous brain injuries and their impact on neuronal signaling. The differences between one-way and two-way communication are specifically considered. Possible implanted and noninvasive BCI solutions for acute and chronic DoC in adult and pediatric populations are also addressed., Conclusions: We identify clinical and technical gaps hindering the use of BCI in patients with DoC in each of these contexts and provide a roadmap for research aimed at improving communication for adults and children with DoC, spanning the clinical spectrum from intensive care unit to chronic care., (© 2024. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

Severe brain injury impairs consciousness by disrupting a broad spectrum of neurotransmitter systems. Emerging evidence suggests that pharmacologic modulation of specific neurotransmitter systems, such as dopamine, promotes recovery of consciousness. Clinical guidelines now endorse the use of amantadine in individuals with traumatic disorders of consciousness (DoC) based on level 1 evidence, and multiple neurostimulants are used off-label in clinical practice, including methylphenidate, modafinil, bromocriptine, levodopa, and zolpidem. However, the relative contributions of monoaminergic, glutamatergic, cholinergic, GABAergic, and orexinergic neurotransmitter systems to recovery of consciousness after severe brain injury are unknown, and personalized approaches to targeted therapy have yet to be developed. This review summarizes the state-of-the-science in the neurochemistry and neurobiology of neurotransmitter systems involved in conscious behaviors, followed by a discussion of how pharmacologic therapies may be used to modulate these neurotransmitter systems and promote recovery of consciousness. We consider pharmacologic modulation of consciousness at the synapse, circuit, and network levels, with a focus on the mesocircuit model that has been proposed to explain the consciousness-promoting effects of various monoaminergic, glutamatergic, and paradoxically, GABAergic therapies. Though fundamental questions remain about neurotransmitter mechanisms, target engagement and optimal therapy selection for individual patients, we propose that pharmacologic therapies hold great promise to promote recovery and improve quality of life for patients with severe brain injuries., 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 © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Transcranial focused ultrasound (tFUS) neuromodulation has shown promise in animals but is challenging to translate to humans because of the thicker skull that heavily scatters ultrasound waves., Objective: We develop and disseminate a model-based navigation (MBN) tool for acoustic dose delivery in the presence of skull aberrations that is easy to use by non-specialists., Methods: We pre-compute acoustic beams for thousands of virtual transducer locations on the scalp of the subject under study. We use the hybrid angular spectrum solver mSOUND, which runs in ∼4 s per solve per CPU yielding pre-computation times under 1 h for scalp meshes with up to 4000 faces and a parallelization factor of 5. We combine this pre-computed set of beam solutions with optical tracking, thus allowing real-time display of the tFUS beam as the operator freely navigates the transducer around the subject' scalp. We assess the impact of MBN versus line-of-sight targeting (LOST) positioning in simulations of 13 subjects., Results: Our navigation tool has a display refresh rate of ∼10 Hz. In our simulations, MBN increased the acoustic dose in the thalamus and amygdala by 8-67 % compared to LOST and avoided complete target misses that affected 10-20 % of LOST cases. MBN also yielded a lower variability of the deposited dose across subjects than LOST., Conclusions: MBN may yield greater and more consistent (less variable) ultrasound dose deposition than transducer placement with line-of-sight targeting, and thus could become a helpful tool to improve the efficacy of tFUS neuromodulation., Competing Interests: Declaration of Competing interest none., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Traumatic brain injury (TBI) is a risk factor for neurodegeneration and cognitive decline, yet the underlying pathophysiologic mechanisms are incompletely understood. This gap in knowledge is in part related to the lack of analytic methods to account for cortical lesions in prior neuroimaging studies. The objective of this study was to develop a lesion detection tool and apply it to an investigation of longitudinal changes in brain structure among individuals with chronic TBI. We identified 24 individuals with chronic moderate-to-severe TBI enrolled in the Late Effects of TBI (LETBI) study who had cortical lesions detected by T1-weighted MRI at two time points. Initial MRI scans were performed more than 1-year post-injury and follow-up scans were performed 3.1 (IQR=1.7) years later. We leveraged FreeSurfer parcellations of T1-weighted MRI volumes and a recently developed super-resolution technique, SynthSR, to identify cortical lesions in this longitudinal dataset. Trained raters received the data in a randomized order and manually corrected the automated lesion segmentation, yielding a final lesion mask for each scan at each timepoint. Lesion volume significantly increased between the two time points with a median volume change of 3.2 (IQR=5.9) mL (p<0.001), and the increases significantly exceeded the possible variance in lesion volume changes due to manual tracing errors (p < 0.001). Lesion volume significantly expanded longitudinally in 23 of 24 subjects, with all FDR corrected p-values ≤ 0.02. Inter-scan duration was not associated with the magnitude of lesion growth. We also demonstrated that the semi-automated tool showed a high level of accuracy compared to "ground truth" manual lesion segmentation. Semi-automated lesion segmentation is feasible in TBI studies and creates opportunities to elucidate mechanisms of post-traumatic neurodegeneration.

Objectives: Accurate classification of disorders of consciousness (DoC) is key in developing rehabilitation plans after brain injury. The Coma Recovery Scale-Revised (CRS-R) is a sensitive measure of consciousness validated in the rehabilitation phase of care. We tested the feasibility, safety, and impact of CRS-R-guided rehabilitation in the ICU for patients with DoC after acute hemorrhagic stroke., Design: Retrospective cohort study., Setting: This single-center study was conducted in the neurocritical care unit at the University of Maryland Medical Center., Patients: We analyzed records from consecutive patients with subarachnoid hemorrhage (SAH) or intracerebral hemorrhage (ICH), who underwent serial CRS-R assessments during ICU admission from April 1, 2018, to December 31, 2021, where CRS-R less than 8 is vegetative state/unresponsive wakefulness syndrome (VS/UWS); CRS-R greater than or equal to 8 is a minimally conscious state (MCS)., Interventions: None., Measurements and Main Results: Outcomes included adverse events during CRS-R evaluations and associations between CRS-R and discharge disposition, therapy-based function, and mobility. We examined the utility of CRS-R compared with other therapist clinical assessment tools in predicting discharge disposition. Seventy-six patients (22 SAH, 54 ICH, median age = 59, 50% female) underwent 276 CRS-R sessions without adverse events. Discharge to acute rehabilitation occurred in 4.4% versus 41.9% of patients with a final CRS-R less than 8 and CRS-R greater than or equal to 8, respectively (odds ratio [OR] 13.4; 95% CI, 2.7-66.1; p < 0.001). Patients with MCS on final CRS-R completed more therapy sessions during hospitalization and had improved mobility and functional performance. Compared with other therapy assessment tools, the CRS-R had the best performance in predicting discharge disposition (area under the curve: 0.83; 95% CI, 0.72-0.94; p < 0.0001)., Conclusions: Early neurorehabilitation guided by CRS-R appears to be feasible and safe in the ICU following hemorrhagic stroke complicated by DoC and may enhance access to inpatient rehabilitation, with the potential for lasting benefit on recovery. Further research is needed to assess generalizability and understand the impact on long-term outcomes., Competing Interests: Drs. Woodward, Ahmed, Edlow, Braun, and Parikh received support for article research from the National Institutes of Health. Dr. Woodward’s institution received funding from the Institute for Clinical and Translational Research (ICTR) (5TL1TR003100-04). Dr. Morris received funding from the National Institute of Neurological Disorders and Stroke (1R01NS131606); he disclosed he serves on the editorial board of Neurology. Dr. Ciryam’s institution received funding from GEn1E Lifesciences, the Henry M. Jackson Foundation, and the Passano Foundation. Dr. Braun’s institution received funding from the National Center for Medical Rehabilitation Research (R03) and the National Institutes on Aging; they disclosed they are a University of Maryland Rehabilitation Institute–Medical Executive Committee member. Dr. Parihk received funding from the University of Maryland Baltimore, the ICTR, the National Center for Advancing Translational Sciences (1UL1TR003098), and the Korean Neurocritical Care Society. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.)

The advent of neurotechnologies including advanced functional magnetic resonance imaging and electroencephalography to detect states of awareness not detectable by traditional bedside neurobehavioral techniques (i.e., covert consciousness) promises to transform neuroscience research and clinical practice for patients with brain injury. As these interventions progress from research tools into actionable, guideline-endorsed clinical tests, ethical guidance for clinicians on how to responsibly communicate the sensitive results they yield is crucial yet remains underdeveloped. Drawing on insights from empirical and theoretical neuroethics research and our clinical experience with advanced neurotechnologies to detect consciousness in behaviorally unresponsive patients, we critically evaluate ethical promises and perils associated with disclosing the results of clinical covert consciousness assessments and describe a semistructured approach to responsible data sharing to mitigate potential risks., (© 2024. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

United States (US) Special Operations Forces (SOF) are frequently exposed to explosive blasts in training and combat, but the effects of repeated blast exposure (RBE) on SOF brain health are incompletely understood. Furthermore, there is no diagnostic test to detect brain injury from RBE. As a result, SOF personnel may experience cognitive, physical, and psychological symptoms for which the cause is never identified, and they may return to training or combat during a period of brain vulnerability. In 30 active-duty US SOF, we assessed the relationship between cumulative blast exposure and cognitive performance, psychological health, physical symptoms, blood proteomics, and neuroimaging measures (Connectome structural and diffusion MRI, 7 Tesla functional MRI, [ 11 C]PBR28 translocator protein [TSPO] positron emission tomography [PET]-MRI, and [ 18 F]MK6240 tau PET-MRI), adjusting for age, combat exposure, and blunt head trauma. Higher blast exposure was associated with increased cortical thickness in the left rostral anterior cingulate cortex (rACC), a finding that remained significant after multiple comparison correction. In uncorrected analyses, higher blast exposure was associated with worse health-related quality of life, decreased functional connectivity in the executive control network, decreased TSPO signal in the right rACC, and increased cortical thickness in the right rACC, right insula, and right medial orbitofrontal cortex-nodes of the executive control, salience, and default mode networks. These observations suggest that the rACC may be susceptible to blast overpressure and that a multimodal, network-based diagnostic approach has the potential to detect brain injury associated with RBE in active-duty SOF., Competing Interests: Competing interests statement:The authors declare no competing interest.

Consciousness is composed of arousal (i.e., wakefulness) and awareness. Substantial progress has been made in mapping the cortical networks that underlie awareness in the human brain, but knowledge about the subcortical networks that sustain arousal in humans is incomplete. Here, we aimed to map the connectivity of a proposed subcortical arousal network that sustains wakefulness in the human brain, analogous to the cortical default mode network (DMN) that has been shown to contribute to awareness. We integrated data from ex vivo diffusion magnetic resonance imaging (MRI) of three human brains, obtained at autopsy from neurologically normal individuals, with immunohistochemical staining of subcortical brain sections. We identified nodes of the proposed default ascending arousal network (dAAN) in the brainstem, hypothalamus, thalamus, and basal forebrain. Deterministic and probabilistic tractography analyses of the ex vivo diffusion MRI data revealed projection, association, and commissural pathways linking dAAN nodes with one another and with DMN nodes. Complementary analyses of in vivo 7-tesla resting-state functional MRI data from the Human Connectome Project identified the dopaminergic ventral tegmental area in the midbrain as a widely connected hub node at the nexus of the subcortical arousal and cortical awareness networks. Our network-based autopsy methods and connectivity data provide a putative neuroanatomic architecture for the integration of arousal and awareness in human consciousness.

Background: Coma is an unresponsive state of disordered consciousness characterized by impaired arousal and awareness. The epidemiology and pathophysiology of coma in ischemic stroke has been underexplored. We sought to characterize the incidence and clinical features of coma as a presentation of large vessel occlusion (LVO) stroke., Methods: Individuals who presented with LVO were retrospectively identified from July 2018 to December 2020. Coma was defined as an unresponsive state of impaired arousal and awareness, operationalized as a score of 3 on NIHSS item 1a., Results: 28/637 (4.4%) patients with LVO stroke were identified as presenting with coma. The median NIHSS was 32 (IQR 29-34) for those with coma versus 11 (5-18) for those without (p < 0.0001). In coma, occlusion locations included basilar (13), vertebral (2), internal carotid (5), and middle cerebral (9) arteries. 8/28 were treated with endovascular thrombectomy (EVT), and 20/28 died during the admission. 65% of patients not treated with EVT had delayed presentations or large established infarcts. In models accounting for pre-stroke mRS, basilar occlusion location, intravenous thrombolysis, and EVT, coma independently increased the odds of transitioning to comfort care during admission (aOR 6.75; 95% CI 2.87,15.84; p < 0.001) and decreased the odds of 90-day mRS 0-2 (aOR 0.12; 95% CI 0.03,0.55; p = 0.007)., Conclusions: It is not uncommon for patients with LVO to present with coma, and delayed recognition of LVO can lead to poor outcomes, emphasizing the need for maintaining a high index of suspicion. While more commonly thought to result from posterior LVO, coma in our cohort was similarly likely to result from anterior LVO. Efforts to improve early diagnosis and care of patients with LVO presenting with coma are crucial., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.)

Importance: Among the most impactful neurologic assessments is that of neuroprognostication, defined here as the prediction of neurologic recovery from disorders of consciousness caused by severe, acute brain injury. Across a range of brain injury etiologies, these determinations often dictate whether life-sustaining treatment is continued or withdrawn; thus, they have major implications for morbidity, mortality, and health care costs. Neuroprognostication relies on a diverse array of tests, including behavioral, radiologic, physiological, and serologic markers, that evaluate the brain's functional and structural integrity., Observations: Prognostic markers, such as the neurologic examination, electroencephalography, and conventional computed tomography and magnetic resonance imaging (MRI), have been foundational in assessing a patient's current level of consciousness and capacity for recovery. Emerging techniques, such as functional MRI, diffusion MRI, and advanced forms of electroencephalography, provide new ways of evaluating the brain, leading to evolving schemes for characterizing neurologic function and novel methods for predicting recovery., Conclusions and Relevance: Neuroprognostic markers are rapidly evolving as new ways of assessing the brain's structural and functional integrity after brain injury are discovered. Many of these techniques remain in development, and further research is needed to optimize their prognostic utility. However, even as such efforts are underway, a series of promising findings coupled with the imperfect predictive value of conventional prognostic markers and the high stakes of these assessments have prompted clinical guidelines to endorse emerging techniques for neuroprognostication. Thus, clinicians have been thrust into an uncertain predicament in which emerging techniques are not yet perfected but too promising to ignore. This review illustrates the current, and likely future, landscapes of prognostic markers. No matter how much prognostic markers evolve and improve, these assessments must be approached with humility and individualized to reflect each patient's values.

The clinical assessment of patients with disorders of consciousness (DoC) relies on the observation of behavioural responses to standardised sensory stimulation. However, several medical comorbidities may directly impair the production of reproducible and appropriate responses, thus reducing the sensitivity of behaviour-based diagnoses. One such comorbidity is akinetic mutism (AM), a rare neurological syndrome characterised by the inability to initiate volitional motor responses, sometimes associated with clinical presentations that overlap with those of DoC. In this paper, we describe the case of a patient with large bilateral mesial frontal lesions, showing prolonged behavioural unresponsiveness and severe disorganisation of electroencephalographic (EEG) background, compatible with a vegetative state/unresponsive wakefulness syndrome (VS/UWS). By applying an unprecedented multimodal battery of advanced imaging and electrophysiology-based techniques (AIE) encompassing spontaneous EEG, evoked potentials, event-related potentials, transcranial magnetic stimulation combined with EEG and structural and functional MRI, we provide the following: (i) a demonstration of the preservation of consciousness despite unresponsiveness in the context of AM, (ii) a plausible neurophysiological explanation for behavioural unresponsiveness and its subsequent recovery during rehabilitation stay and (iii) novel insights into the relationships between DoC, AM and parkinsonism. The present case offers proof-of-principle evidence supporting the clinical utility of a multimodal hierarchical workflow that combines AIEs to detect covert signs of consciousness in unresponsive patients., (© 2023 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Historically, clinical evaluation of unresponsive patients following brain injury has relied principally on serial behavioral examination to search for emerging signs of consciousness and track recovery. Advances in neuroimaging and electrophysiologic techniques now enable clinicians to peer into residual brain functions even in the absence of overt behavioral signs. These advances have expanded clinicians' ability to sub-stratify behaviorally unresponsive and seemingly unaware patients following brain injury by querying and classifying covert brain activity made evident through active or passive neuroimaging or electrophysiologic techniques, including functional MRI, electroencephalography (EEG), transcranial magnetic stimulation-EEG, and positron emission tomography. Clinical research has thus reciprocally influenced clinical practice, giving rise to new diagnostic categories including cognitive-motor dissociation (i.e. 'covert consciousness') and covert cortical processing (CCP). While covert consciousness has received extensive attention and study, CCP is relatively less understood. We describe that CCP is an emerging and clinically relevant state of consciousness marked by the presence of intact association cortex responses to environmental stimuli in the absence of behavioral evidence of stimulus processing. CCP is not a monotonic state but rather encapsulates a spectrum of possible association cortex responses from rudimentary to complex and to a range of possible stimuli. In constructing a roadmap for this evolving field, we emphasize that efforts to inform clinicians, philosophers, and researchers of this condition are crucial. Along with strategies to sensitize diagnostic criteria and disorders of consciousness nosology to these vital discoveries, democratizing access to the resources necessary for clinical identification of CCP is an emerging clinical and ethical imperative., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press.)

Background: Patients with disorders of consciousness who are behaviorally unresponsive may demonstrate volitional brain responses to motor imagery or motor commands detectable on functional magnetic resonance imaging or electroencephalography. This state of cognitive motor dissociation (CMD) may have prognostic significance., Methods: The Neurocritical Care Society's Curing Coma Campaign identified an international group of experts who convened in a series of monthly online meetings between September 2021 and April 2023 to examine the science of CMD and identify key knowledge gaps and unmet needs., Results: The group identified major knowledge gaps in CMD research: (1) lack of information about patient experiences and caregiver accounts of CMD, (2) limited epidemiological data on CMD, (3) uncertainty about underlying mechanisms of CMD, (4) methodological variability that limits testing of CMD as a biomarker for prognostication and treatment trials, (5) educational gaps for health care personnel about the incidence and potential prognostic relevance of CMD, and (6) challenges related to identification of patients with CMD who may be able to communicate using brain-computer interfaces., Conclusions: To improve the management of patients with disorders of consciousness, research efforts should address these mechanistic, epidemiological, bioengineering, and educational gaps to enable large-scale implementation of CMD assessment in clinical practice., (© 2023. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

We examined whether females with a history of traumatic brain injury (TBI) and intimate partner violence (IPV) have greater exposure to lifetime trauma relative to females with TBI but no IPV history. Further, we assessed the effects of lifetime trauma on psychological outcomes after TBI. Female participants ( n  = 70; age M [standard deviation-SD] = 50.5 [15.2] years) with TBI (time since injury median [interquartile range -IQR] = 10.2 [5.3-17.8] years) completed a structured assessment of lifetime history of TBI, including an IPV module to query head injuries from physical violence by an intimate partner. We characterized lifetime trauma exposure with the Adverse Childhood Experiences (ACEs) questionnaire and Survey of Exposure to Community Violence (CV). We evaluated psychological functioning with self-report questionnaires of post-traumatic stress disorder (PTSD), depression, and anxiety symptoms. Compared with those with no IPV history ( n  = 51), participants reporting IPV-related head injuries ( n  = 19; 27.1%) reported more ACEs (M[SD] IPV: 4.5[2.9]; No IPV: 1.6[1.8], p  < 0.001, d  = 1.08) and greater CV (IPV: 17.5[8.4]; No IPV: 7.6[6.1], p  < .0001, d  = 1.26). Within the full sample, ACEs (β = 0.21, 95% confidence interval [CI] = 0.04-0.39) and CV (β = 0.07, 95% CI = 0.01-0.13) predicted worse PTSD symptoms, while IPV alone did not. Exposure to all three sources of trauma (ACEs, CV, and IPV) was associated with worse PTSD symptoms relative to fewer traumas. The results highlight the scope of traumatic exposures among TBI survivors and the importance of considering IPV and other lifetime trauma exposure in assessing and managing TBI. Trauma-informed interventions that are modified for TBI-related impairment may offer improved outcomes in managing psychological symptoms.

Purpose: To investigate whether spatiotemporal magnetic field monitoring can correct pronounced eddy current-induced artifacts incurred by strong diffusion-sensitizing gradients up to 300 mT/m used in high b-value diffusion-weighted (DW) EPI., Methods: A dynamic field camera equipped with 16 1 H NMR field probes was first used to characterize field perturbations caused by residual eddy currents from diffusion gradients waveforms in a 3D multi-shot EPI sequence on a 3T Connectom scanner for different gradient strengths (up to 300 mT/m), diffusion directions, and shots. The efficacy of dynamic field monitoring-based image reconstruction was demonstrated on high-gradient strength, submillimeter resolution whole-brain ex vivo diffusion MRI. A 3D multi-shot image reconstruction framework was developed that incorporated the nonlinear phase evolution measured with the dynamic field camera., Results: Phase perturbations in the readout induced by residual eddy currents from strong diffusion gradients are highly nonlinear in space and time, vary among diffusion directions, and interfere significantly with the image encoding gradients, changing the k-space trajectory. During the readout, phase modulations between odd and even EPI echoes become non-static and diffusion encoding direction-dependent. Superior reduction of ghosting and geometric distortion was achieved with dynamic field monitoring compared to ghosting reduction approaches such as navigator- and structured low-rank-based methods or MUSE followed by image-based distortion correction with the FSL tool "eddy.", Conclusion: Strong eddy current artifacts characteristic of high-gradient strength DW-EPI can be well corrected with dynamic field monitoring-based image reconstruction., (© 2023 International Society for Magnetic Resonance in Medicine.)

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.

Covert consciousness is a state of residual awareness following severe brain injury or neurological disorder that evades routine bedside behavioral detection. Patients with covert consciousness have preserved awareness but are incapable of self-expression through ordinary means of behavior or communication. Growing recognition of the limitations of bedside neurobehavioral examination in reliably detecting consciousness, along with advances in neurotechnologies capable of detecting brain states or subtle signs indicative of consciousness not discernible by routine examination, carry promise to transform approaches to classifying, diagnosing, prognosticating and treating disorders of consciousness. Here we describe and critically evaluate the evolving clinical category of covert consciousness, including approaches to its diagnosis through neuroimaging, electrophysiology, and novel behavioral tools, its prognostic relevance, and open questions pertaining to optimal clinical management of patients with covert consciousness recovering from severe brain injury.

United States Special Operations Forces (SOF) personnel are frequently exposed to explosive blasts in training and combat. However, the effects of repeated blast exposure on the human brain are incompletely understood. Moreover, there is currently no diagnostic test to detect repeated blast brain injury (rBBI). In this "Human Performance Optimization" article, we discuss how the development and implementation of a reliable diagnostic test for rBBI has the potential to promote SOF brain health, combat readiness, and quality of life., (2023.)

This scientific commentary refers to 'Functional hub disruption emphasizes consciousness recovery in severe traumatic brain injury', by Oujamaa et al . (https://doi.org/10.1093/braincomms/fcad319)., Competing Interests: M.M. is cofounder and shareholder of Intrinsic Powers., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Objective: It is not currently possible to predict long-term functional dependency in patients with disorders of consciousness (DoC) after traumatic brain injury (TBI). Our objective was to fit and externally validate a prediction model for 1-year dependency in patients with DoC ≥ 2 weeks after TBI., Methods: We included adults with TBI enrolled in TBI Model Systems (TBI-MS) or Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) studies who were not following commands at rehabilitation admission or 2 weeks post-injury, respectively. We fit a logistic regression model in TBI-MS and validated it in TRACK-TBI. The primary outcome was death or dependency at 1 year post-injury, defined using the Disability Rating Scale., Results: In the TBI-MS Discovery Sample, 1,960 participants (mean age 40 [18] years, 76% male, 68% white) met inclusion criteria, and 406 (27%) were dependent 1 year post-injury. In a TBI-MS held out cohort, the dependency prediction model's area under the receiver operating characteristic curve was 0.79 (95% CI 0.74-0.85), positive predictive value was 53% and negative predictive value was 86%. In the TRACK-TBI external validation (n = 124, age 40 [16] years, 77% male, 81% white), the area under the receiver operating characteristic curve was 0.66 (0.53, 0.79), equivalent to the standard IMPACT core + CT score (p = 0.8)., Interpretation: We developed a 1-year dependency prediction model using the largest existing cohort of patients with DoC after TBI. The sensitivity and negative predictive values were greater than specificity and positive predictive values. Accuracy was diminished in an external sample, but equivalent to the IMPACT model. Further research is needed to improve dependency prediction in patients with DoC after TBI. ANN NEUROL 2023;94:1008-1023., (© 2023 American Neurological Association.)

Background: Over the past 5 decades, advances in neuroimaging have yielded insights into the pathophysiologic mechanisms that cause disorders of consciousness (DoC) in patients with severe brain injuries. Structural, functional, metabolic, and perfusion imaging studies have revealed specific neuroanatomic regions, such as the brainstem tegmentum, thalamus, posterior cingulate cortex, medial prefrontal cortex, and occipital cortex, where lesions correlate with the current or future state of consciousness. Advanced imaging modalities, such as diffusion tensor imaging, resting-state functional magnetic resonance imaging (fMRI), and task-based fMRI, have been used to improve the accuracy of diagnosis and long-term prognosis, culminating in the endorsement of fMRI for the clinical evaluation of patients with DoC in the 2018 US (task-based fMRI) and 2020 European (task-based and resting-state fMRI) guidelines. As diverse neuroimaging techniques are increasingly used for patients with DoC in research and clinical settings, the need for a standardized approach to reporting results is clear. The success of future multicenter collaborations and international trials fundamentally depends on the implementation of a shared nomenclature and infrastructure., Methods: To address this need, the Neurocritical Care Society's Curing Coma Campaign convened an international panel of DoC neuroimaging experts to propose common data elements (CDEs) for data collection and reporting in this field., Results: We report the recommendations of this CDE development panel and disseminate CDEs to be used in neuroimaging studies of patients with DoC., Conclusions: These CDEs will support progress in the field of DoC neuroimaging and facilitate international collaboration., (© 2023. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

We developed and validated an abbreviated version of the Coma Recovery Scale-Revised (CRS-R), the CRS-R For Accelerated Standardized Testing (CRSR-FAST), to detect conscious awareness in patients with severe traumatic brain injury in the intensive care unit. In 45 consecutively enrolled patients, CRSR-FAST administration time was approximately one-third of the full-length CRS-R (mean [SD] 6.5 [3.3] vs 20.1 [7.2] minutes, p < 0.0001). Concurrent validity (simple kappa 0.68), test-retest (Mak's ρ = 0.76), and interrater (Mak's ρ = 0.91) reliability were substantial. Sensitivity, specificity, and accuracy for detecting consciousness were 81%, 89%, and 84%, respectively. The CRSR-FAST facilitates serial assessment of consciousness, which is essential for diagnostic and prognostic accuracy. ANN NEUROL 2023;94:919-924., (© 2023 American Neurological Association.)