Brain Metabolism but Not Gray Matter Volume Underlies the Presence of Language Function in the Minimally Conscious State (MCS): MCS+ Versus MCS- Neuroimaging Differences

A pilot human study using ketamine to treat disorders of consciousness

Post-comatose disorders of consciousness (DoC) represent persistent neurological conditions with limited therapeutic options and a poor prognosis. Recent works advocate for exploring the effects of psychedelics to enhance brain complexity in DoC and ameliorate their consciousness. We investigated sub-anesthetic concentration of the atypical psychedelic ketamine for treating post-comatose prolonged DoC through a double-blind, placebo-controlled, cross-over trial involving three adult patients. Incremental concentrations of intravenous ketamine and saline were administered, alongside continuous electroencephalogram (EEG) recording and assessments of conscious behaviors and spastic paresis. Brain complexity, measured by Lempel-Ziv complexity (LZC) and explainable consciousness indicator (ECI), revealed increased LZC during ketamine infusion but no change in ECI. Patients exhibited reduced spastic paresis and increased arousal as time spent with eyes open but no positive change in diagnosis. No adverse effects were noted. This study contributes to understanding the relationship between consciousness and brain complexity and suggests a potential therapeutic role for ketamine in DoC.

The role of conscious attention in auditory statistical learning: Evidence from patients with impaired consciousness

The need for attention to enable statistical learning is debated. Testing individuals with impaired consciousness offers valuable insight, but very few studies have been conducted due to the difficulties inherent in such studies. Here, we examined the ability of patients with varying levels of disorders of consciousness (DOC) to extract statistical regularities from an artificial language composed of randomly concatenated pseudowords by measuring frequency tagging in EEG. The objectives were firstly, to assess the automaticity of the segmentation process and the correlations between the level of covert consciousness and statistical learning capacities; secondly, to identify potential new diagnostic indicators. We observed that segmentation abilities were preserved in some minimally conscious patients, suggesting that auditory statistical learning is an inherently automatic low-level process. Due to significant inter-individual variability, word segmentation might not be robust enough for clinical use. In contrast, temporal accuracy of auditory syllable responses correlates strongly with coma severity.

Lateral frontoparietal effective connectivity differentiates and predicts state of consciousness in a cohort of patients with traumatic disorders of consciousness

Neuroimaging studies have suggested an important role for the default mode network (DMN) in disorders of consciousness (DoC). However, the extent to which DMN connectivity can discriminate DoC states-unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS)-is less evident. Particularly, it is unclear whether effective DMN connectivity, as measured indirectly with dynamic causal modelling (DCM) of resting EEG can disentangle UWS from healthy controls and from patients considered conscious (MCS+). Crucially, this extends to UWS patients with potentially "covert" awareness (minimally conscious star, MCS*) indexed by voluntary brain activity in conjunction with partially preserved frontoparietal metabolism as measured with positron emission tomography (PET+ diagnosis; in contrast to PET- diagnosis with complete frontoparietal hypometabolism). Here, we address this gap by using DCM of EEG data acquired from patients with traumatic brain injury in 11 UWS (6 PET- and 5 PET+) and in 12 MCS+ (11 PET+ and 1 PET-), alongside with 11 healthy controls. We provide evidence for a key difference in left frontoparietal connectivity when contrasting UWS PET- with MCS+ patients and healthy controls. Next, in a leave-one-subject-out cross-validation, we tested the classification performance of the DCM models demonstrating that connectivity between medial prefrontal and left parietal sources reliably discriminates UWS PET- from MCS+ patients and controls. Finally, we illustrate that these models generalize to an unseen dataset: models trained to discriminate UWS PET- from MCS+ and controls, classify MCS* patients as conscious subjects with high posterior probability (pp > .92). These results identify specific alterations in the DMN after severe brain injury and highlight the clinical utility of EEG-based effective connectivity for identifying patients with potential covert awareness.

Low-density EEG-based Functional Connectivity Discriminates Minimally Conscious State plus from minus

OBJECTIVE

Within the continuum of consciousness, patients in a Minimally Conscious State (MCS) may exhibit high-level behavioral responses (MCS+) or may not (MCS-). The evaluation of residual consciousness and related classification is crucial to propose tailored rehabilitation and pharmacological treatments, considering the inherent differences among groups in diagnosis and prognosis. Currently, differential diagnosis relies on behavioral assessments posing a relevant risk of misdiagnosis. In this context, EEG offers a non-invasive approach to model the brain as a complex network. The search for discriminating features could reveal whether behavioral responses in post-comatose patients have a defined physiological background. Additionally, it is essential to determine whether the standard behavioral assessment for quantifying responsiveness holds physiological significance.

METHODS

In this prospective observational study, we investigated whether low-density EEG-based graph metrics could discriminate MCS+/- patients by enrolling 57 MCS patients (MCS-: 30; males: 28). At admission to intensive rehabilitation, 30 min resting-state closed-eyes EEG recordings were performed together with consciousness diagnosis following international guidelines. After EEG preprocessing, graphs' metrics were estimated using different connectivity measures, at multiple connection densities and frequency bands (α,θ,δ). Metrics were also provided to cross-validated Machine Learning (ML) models with outcome MCS+/-.

RESULTS

A lower level of brain activity integration was found in the MCS- group in the α band. Instead, in the δ band MCS- group presented an higher level of clustering (weighted clustering coefficient) respect to MCS+. The best-performing solution in discriminating MCS+/- through the use of ML was an Elastic-Net regularized logistic regression with a cross-validation accuracy of 79% (sensitivity and specificity of 74% and 85% respectively).

CONCLUSION

Despite tackling the MCS+/- differential diagnosis is highly challenging, a daily-routine low-density EEG might allow to differentiate across these differently responsive brain networks.

SIGNIFICANCE

Graph-theoretical features are shown to discriminate between these two neurophysiologically similar conditions, and may thus support the clinical diagnosis.

Multimodal approaches supporting the diagnosis, prognosis and investigation of neural correlates of disorders of consciousness: A systematic review

The limits of the standard, behaviour-based clinical assessment of patients with disorders of consciousness (DoC) prompted the employment of functional neuroimaging, neurometabolic, neurophysiological and neurostimulation techniques, to detect brain-based covert markers of awareness. However, uni-modal approaches, consisting in employing just one of those techniques, are usually not sufficient to provide an exhaustive exploration of the neural underpinnings of residual awareness. This systematic review aimed at collecting the evidence from studies employing a multimodal approach, that is, combining more instruments to complement DoC diagnosis, prognosis and better investigating their neural correlates. Following the PRISMA guidelines, records from PubMed, EMBASE and Scopus were screened to select peer-review original articles in which a multi-modal approach was used for the assessment of adult patients with a diagnosis of DoC. Ninety-two observational studies and 32 case reports or case series met the inclusion criteria. Results highlighted a diagnostic and prognostic advantage of multi-modal approaches that involve electroencephalography-based (EEG-based) measurements together with neuroimaging or neurometabolic data or with neurostimulation. Multimodal assessment deepened the knowledge on the neural networks underlying consciousness, by showing correlations between the integrity of the default mode network and the different clinical diagnosis of DoC. However, except for studies using transcranial magnetic stimulation combined with electroencephalography, the integration of more than one technique in most of the cases occurs without an a priori-designed multi-modal diagnostic approach. Our review supports the feasibility and underlines the advantages of a multimodal approach for the diagnosis, prognosis and for the investigation of neural correlates of DoCs.

Neuroimaging in Disorders of Consciousness and Recovery

There is a clinical need for more accurate diagnosis and prognostication in patients with disorders of consciousness (DoC). There are several neuroimaging modalities that enable detailed, quantitative assessment of structural and functional brain injury, with demonstrated diagnostic and prognostic value. Additionally, longitudinal neuroimaging studies have hinted at quantifiable structural and functional neuroimaging biomarkers of recovery, with potential implications for the management of DoC.

Assessing consciousness and cognition in disorders of consciousness

Detecting willful cognition in these patients is known to be challenging due to the patients' motor disabilities and high vigilance fluctuations but also due to the lack of expertise and use of adequate tools to assess these patients in specific settings. This review will discuss the main disorders of consciousness after severe brain injury, how to assess consciousness and cognition in these patients, as well as the challenges and tools available to overcome these challenges and reach an accurate diagnosis.

Brain microstate spatio-temporal dynamics as a candidate endotype of consciousness

Consciousness can be defined as a phenomenological experience continuously evolving. Current research showed how conscious mental activity can be subdivided into a series of atomic brain states converging to a discrete spatiotemporal pattern of global neuronal firing. Using the high temporal resolution of EEG recordings in patients with a severe Acquired Brain Injury (sABI) admitted to an Intensive Rehabilitation Unit (IRU), we detected a novel endotype of consciousness from the spatiotemporal brain dynamics identified via microstate analysis. Also, we investigated whether microstate features were associated with common neurophysiological alterations. Finally, the prognostic information comprised in such descriptors was analysed in a sub-cohort of patients with prolonged Disorder of Consciousness (pDoC). Occurrence of frontally-oriented microstates (C microstate), likelihood of maintaining such brain state or transitioning to the C topography and complexity were found to be indicators of consciousness presence and levels. Features of left-right asymmetric microstates and transitions toward them were found to be negatively correlated with antero-posterior brain reorganization and EEG symmetry. Substantial differences in microstates' sequence complexity and presence of C topography were found between groups of patients with alpha dominant background, cortical reactivity and antero-posterior gradient. Also, transitioning from left-right to antero-posterior microstates was found to be an independent predictor of consciousness recovery, stronger than consciousness levels at IRU's admission. In conclusions, global brain dynamics measured with scale-free estimators can be considered an indicator of consciousness presence and a candidate marker of short-term recovery in patients with a pDoC.

Evaluation of consciousness rehabilitation via neuroimaging methods

Accurate evaluation of patients with disorders of consciousness (DoC) is crucial for personalized treatment. However, misdiagnosis remains a serious issue. Neuroimaging methods could observe the conscious activity in patients who have no evidence of consciousness in behavior, and provide objective and quantitative indexes to assist doctors in their diagnosis. In the review, we discussed the current research based on the evaluation of consciousness rehabilitation after DoC using EEG, fMRI, PET, and fNIRS, as well as the advantages and limitations of each method. Nowadays single-modal neuroimaging can no longer meet the researchers` demand. Considering both spatial and temporal resolution, recent studies have attempted to focus on the multi-modal method which can enhance the capability of neuroimaging methods in the evaluation of DoC. As neuroimaging devices become wireless, integrated, and portable, multi-modal neuroimaging methods will drive new advancements in brain science research.

EEG fractal dimensions predict high-level behavioral responses in minimally conscious patients

Objective.Brain-injured patients may enter a state of minimal or inconsistent awareness termed minimally conscious state (MCS). Such patient may (MCS+) or may not (MCS-) exhibit high-level behavioral responses, and the two groups retain two inherently different rehabilitative paths and expected outcomes. We hypothesized that brain complexity may be treated as a proxy of high-level cognition and thus could be used as a neural correlate of consciousness.Approach.In this prospective observational study, 68 MCS patients (MCS-: 30; women: 31) were included (median [IQR] age 69 [20]; time post-onset 83 [28]). At admission to intensive rehabilitation, 30 min resting-state closed-eyes recordings were performed together with consciousness diagnosis following international guidelines. The width of the multifractal singularity spectrum (MSS) was computed for each channel time series and entered nested cross-validated interpretable machine learning models targeting the differential diagnosis of MCS±.Main results.Frontal MSS widths (p< 0.05), as well as the ones deriving from the left centro-temporal network (C3:p= 0.018, T3:p= 0.017; T5:p= 0.003) were found to be significantly higher in the MCS+ cohort. The best performing solution was found to be the K-nearest neighbor model with an aggregated test accuracy of 75.5% (median [IQR] AuROC for 100 executions 0.88 [0.02]). Coherently, the electrodes with highest Shapley values were found to be Fz and Cz, with four out the first five ranked features belonging to the fronto-central network.Significance.MCS+ is a frequent condition associated with a notably better prognosis than the MCS-. High fractality in the left centro-temporal network results coherent with neurological networks involved in the language function, proper of MCS+ patients. Using EEG-based interpretable algorithm to complement differential diagnosis of consciousness may improve rehabilitation pathways and communications with caregivers.

The current and future contribution of neuroimaging to the understanding of disorders of consciousness

Patients with disorders of consciousness (DoC) represent a group of severely brain-injured patients with varying capacities for consciousness in terms of both wakefulness and awareness. The current state-of-the-art for assessing these patients is through standardised behavioural examinations, but inaccuracies are commonplace. Neuroimaging and electrophysiological techniques have revealed vast insights into the relationships between neural alterations, andcognitive and behavioural features of consciousness in patients with DoC. This has led to the establishment of neuroimaging paradigms for the clinical assessment of DoC patients. Here, we review selected neuroimaging findings on the DoC population, outlining key findings of the dysfunction underlying DoC and presenting the current clinical utility of neuroimaging tools. We discuss that whilst individual brain areas play instrumental roles in generating and supporting consciousness, activation of these areas alone is not sufficient for conscious experience. Instead, for consciousness to arise, we need preserved thalamo-cortical circuits, in addition to sufficient connectivity between distinctly differentiated brain networks, underlined by connectivity both within, and between such brain networks. Finally, we present recent advances and future perspectives in computational methodologies applied to DoC, supporting the notion that progress in the science of DoC will be driven by a symbiosis of these data-driven analyses, and theory-driven research. Both perspectives will work in tandem to provide mechanistic insights contextualised within theoretical frameworks which ultimately inform the practice of clinical neurology.

Prognosis of consciousness disorders in the intensive care unit

Assessments of consciousness are a critical part of prognostic algorithms for critically ill patients suffering from severe brain injuries. There have been significant advances in the field of coma science over the past two decades, providing clinicians with more advanced and precise tools for diagnosing and prognosticating disorders of consciousness (DoC). Advanced neuroimaging and electrophysiological techniques have vastly expanded our understanding of the biological mechanisms underlying consciousness, and have helped identify new states of consciousness. One of these, termed cognitive motor dissociation, can predict functional recovery at 1 year post brain injury, and is present in up to 15-20% of patients with DoC. In this chapter, we review several tools that are used to predict DoC, describing their strengths and limitations, from the neurological examination to advanced imaging and electrophysiologic techniques. We also describe multimodal assessment paradigms that can be used to identify covert consciousness and thus help recognize patients with the potential for future recovery and improve our prognostication practices.

Opioid-induced short-term consciousness improvement in patients with disorders of consciousness

Introduction

Effective treatment to facilitate recovery from prolonged disorders of consciousness is a complex topic for the medical community. In clinical practice, we have found that a subset of patients has a short-term improvement of consciousness after general anesthesia.

Methods

To determine the clinical factors responsible for the consciousness improvement, we enrolled 50 patients with disorders of consciousness who underwent surgery from October 2021 to June 2022. Their states of consciousness were evaluated before surgery, within 48 h after surgery, and 3 months after surgery. Clinical-related factors and intraoperative anesthetic drug doses were collected and compared between patients with and without consciousness improvement. Independent associations between selected factors and postoperative improvement were assessed using multivariate logistical regression analyses.

Results

Postoperative short-term consciousness improvement was found in 44% (22/50) of patients, with significantly increased scores of auditory and visual subscales. Patients with traumatic etiology, a preoperative diagnosis of minimally conscious state, and higher scores in the auditory, visual, and motor subscales were more likely to have postoperative improvement. This short-term increase in consciousness after surgery correlated with patients' abilities to communicate in the long term. Furthermore, the amount of opioid analgesic used was significantly different between the improved and non-improved groups. Finally, analgesic dose, etiology, and preoperative diagnosis were independently associated with postoperative consciousness improvement.

Discussion

In conclusion, postoperative consciousness improvement is related to the residual consciousness of the patient and can be used to evaluate prognosis. Administration of opioids may be responsible for this short-term improvement in consciousness, providing a potential therapeutic approach for disorders of consciousness.

Transauricular vagus nerve stimulation for patients with disorders of consciousness: A randomized controlled clinical trial

Introduction

Disorders of consciousness (DoCs) are a frequent complication of brain injury disease, and effective treatments are currently lacking. Transauricular vagus nerve stimulation (tVNS) has been proposed as a promising therapeutic method for neurological disorders such as epilepsy and depression. In our previous study, we demonstrated that vagus nerve stimulation promoted recovery in rats with DoCs caused by traumatic brain injury. However, the clinical effect of vagus nerve stimulation on consciousness disorders is unclear. We aimed to investigate the therapeutic efficacy and safety of tVNS in patients with DoCs.

Methods

We conducted a randomized, double-blinded, sham-controlled trial. Patients (N = 60) with DoCs, including minimally conscious state (MCS) and vegetative state/unresponsive wakefulness syndrome, were enrolled and randomized to groups receiving either active or sham tVNS. A frequency of 20 Hz and pulse wave of 200 us was used in the active-tVNS protocol, which was performed in the auricular branch of the vagus nerve in the left outer ear. The sham-tVNS protocol was the same as the active-tVNS protocol although without current input. Both groups of patients also received conventional treatments. Consciousness was evaluated according to the Coma Recovery Scale-Revised before and after the 4-week intervention. We also recorded the type and number of behavioral responses. Safety was primarily assessed according to the incidence of treatment-emergent adverse events. Each patient's heart rate and blood pressure were monitored during all treatment sessions.

Results

Ultimately, 57 patients completed the study: 28 patients underwent active tVNS and 29 patients underwent sham tVNS. No significant differences were observed in Coma Recovery Scale-Revised scores between the active- and sham-tVNS groups before the tVNS sessions. Compared with patients in the sham-tVNS group (9.28 ± 4.38), patients with DoCs treated with active tVNS showed improved consciousness (10.93 ± 4.99), although not statistically significant. Further analysis revealed obvious differences between patients with MCS receiving active and sham tVNS, but no significant difference in patients with vegetative state/unresponsive wakefulness syndrome in both groups. All side effects were considered common medical conditions with no obvious correlation to tVNS.

Conclusion

These preliminary data provide early evidence that tVNS may be an effective and safe approach for promoting the recovery of consciousness, especially in patients with MCS.

Clinical trial registration

https://www.chictr.org.cn/edit.aspx?pid=175938&htm=4, identifier: ChiCTR2200066629.

Clinical Decision on Disorders of Consciousness After Acquired Brain Injury: Stepping Forward

Major advances have been made over the past few decades in identifying and managing disorders of consciousness (DOC) in patients with acquired brain injury (ABI), bringing the transformation from a conceptualized definition to a complex clinical scenario worthy of scientific exploration. Given the continuously-evolving framework of precision medicine that integrates valuable behavioral assessment tools, sophisticated neuroimaging, and electrophysiological techniques, a considerably higher diagnostic accuracy rate of DOC may now be reached. During the treatment of patients with DOC, a variety of intervention methods are available, including amantadine and transcranial direct current stimulation, which have both provided class II evidence, zolpidem, which is also of high quality, and non-invasive stimulation, which appears to be more encouraging than pharmacological therapy. However, heterogeneity is profoundly ingrained in study designs, and only rare schemes have been recommended by authoritative institutions. There is still a lack of an effective clinical protocol for managing patients with DOC following ABI. To advance future clinical studies on DOC, we present a comprehensive review of the progress in clinical identification and management as well as some challenges in the pathophysiology of DOC. We propose a preliminary clinical decision protocol, which could serve as an ideal reference tool for many medical institutions.

Relationship between consciousness level and perfusion computed tomography in patients with prolonged disorders of consciousness

PURPOSE

We assessed the relationship between consciousness level and values of cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and time to peak (TTP) obtained by whole-brain perfusion computed tomography (pCT) in patients with prolonged disorders of consciousness (pDOC).

METHODS

This study included 29 patients in vegetative state (VS), 34 with minimally consciousness state minus (MCS-), and 13 with minimally consciousness state plus (MCS+). All patients were evaluated using the Coma Recovery Scale-Revised (CRS-R), the Glasgow Coma Scale (GCS), and the Full Outline of UnResponsiveness (FOUR). The values of CBF, CBV, MTT, and TTP were obtained from patients who underwent pCT. Differences in CBF, CBV, MTT, and TTP were compared between the three types of pDOC. Correlations between the CRS-R, GCS, and FOUR scores and the pCT results were analyzed.

RESULTS

Among the three groups, patients in VS showed a significantly decreased CBF in the bilateral frontal lobe, thalamus, temporal lobe, occipital lobe, brainstem, and damaged part. CBV was significantly reduced in patients with VS in the bilateral frontal lobe, thalamus, temporal lobe, brainstem, and damaged part. The total CRS-R, GCS, and FOUR scores were positively correlated with CBF, CBV, and TTP in almost all regions of interest.

CONCLUSION

Reductions in CBF and CBV calculated with pCT are associated with impaired consciousness and perfusion CT could be a promising tool in evaluating the conscious level in patients with pDOC.

EEG-based methods for recovery prognosis of patients with disorders of consciousness: A systematic review

OBJECTIVE

Disorders of consciousness (DoC) are acquired conditions of severely altered consciousness. Electroencephalography (EEG)-derived biomarkers have been studied as clinical predictors of consciousness recovery. Therefore, this study aimed to systematically review the methods, features, and models used to derive prognostic EEG markers in patients with DoC in a rehabilitation setting.

METHODS

We conducted a systematic literature search of EEG-based strategies for consciousness recovery prognosis in five electronic databases.

RESULTS

The search resulted in 2964 papers. After screening, 15 studies were included in the review. Our analyses revealed that simpler experimental settings and similar filtering cut-off frequencies are preferred. The results of studies were categorised by extracting qualitative and quantitative features. The quantitative features were further classified into evoked/event-related potentials, spectral measures, entropy measures, and graph-theory measures. Despite the variety of methods, features from all categories, including qualitative ones, exhibited significant correlations with DoC prognosis. Moreover, no agreement was found on the optimal set of EEG-based features for the multivariate prognosis of patients with DoC, which limits the computational methods applied for outcome prediction and correlation analysis to classical ones. Nevertheless, alpha power, reactivity, and higher complexity metrics were often found to be predictive of consciousness recovery.

CONCLUSIONS

This study's findings confirm the essential role of qualitative EEG and suggest an important role for quantitative EEG. Their joint use could compensate for their reciprocal limitations.

SIGNIFICANCE

This study emphasises the need for further efforts toward guidelines on standardised EEG analysis pipeline, given the already proven role of EEG markers in the recovery prognosis of patients with DoC.

Effectiveness of transcranial direct current stimulation over dorsolateral prefrontal cortex in patients with prolonged disorders of consciousness: A systematic review and meta-analysis

Background

Transcranial direct current stimulation (tDCS) has been widely studied for treatment of patients with prolonged disorders of consciousness (PDOC). The dorsolateral prefrontal cortex (DLPFC) is a hot target for intervention, but some controversies remain.

Purpose

This review aimed to systematically investigate the therapeutic effects of DLPFC-anodal-tDCS for patients with PDOC through a meta-analysis approach.

Data sources

Searches for relevant articles available in English were conducted using EMBASE, Medline, Web of Science, EBSCO, and Cochrane Central Register of Controlled Trials from inception until March 26, 2022.

Study selection

All randomized parallel or cross-over controlled trials comparing the effect of intervention with active-tDCS and Sham-tDCS on Coma Recovery Scale Revised (CRS-R) score in individuals with PDOC were included.

Data extraction

Two authors independently extracted data, assessed the methodological quality, and rated each study.

Data synthesis

Ten randomized parallel or cross-over controlled trials were eligible for systematic review, and eight of the studies involving 165 individuals were identified as eligible for meta-analysis. Compared with Sham-tDCS, the use of anode-tDCS over DLPFC improved the CRS-R score (SMD = 0.71; 95% CI: 0.47–0.95, I² = 10%). Patients with PDOC classified as MCS and clinically diagnosed as CVA or TBI may benefit from anode-tDCS.

Limitations

Failure to evaluate the long-term effects and lack of quantitative analysis of neurological examination are the main limitations for the application of anode-tDCS.

Conclusions

Anodal-tDCS over the left DLPFC may be advantageous to the recovery of patients with MCS and clinically diagnosed with CVA or TBI. There is a lack of evidence to support the duration of the disease course will limit the performance of the treatment. Further studies are needed to explore the diversity of stimulation targets and help to improve the mesocircuit model.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=279391, identifier: CRD42022279391.

Language Assessment in Patients with Disorders of Consciousness

The assessment of residual language abilities in patients with disorders of consciousness (DoC) after severe brain injury is particularly challenging due to their limited behavioral repertoire. Moreover, associated language impairment such as receptive aphasia may lead to an underestimation of actual consciousness levels. In this review, we examine past research on the assessment of residual language processing in DoC patients, and we discuss currently available tools for identifying language-specific abilities and their prognostic value. We first highlight the need for validated and sensitive bedside behavioral assessment tools for residual language abilities in DoC patients. As regards neuroimaging and electrophysiological methods, the tasks involving higher level linguistic commands appear to be the most informative about level of consciousness and have the best prognostic value. Neuroimaging methods should be combined with the most appropriate behavioral tools in multimodal assessment protocols to assess receptive language abilities in DoC patients in the most complete and sensitive manner.

Prognostication, Ethical Issues, and Palliative Care in Disorders of Consciousness

Research advances in recent years have shown that some individuals with vegetative state or minimally conscious state can emerge to higher states of consciousness even years after injury. A minority of behaviorally unresponsive patients with vegetative state have also been shown to follow commands, or even communicate, using neuroimaging or electrophysiological techniques. These advances raise ethical questions that have important implications for clinical care. In this article, the authors argue that adopting a neuropalliative care approach can help clinicians provide ethical, compassionate care to these patients and their caregivers.

Residual implicit and explicit language abilities in patients with disorders of consciousness: A systematic review

Language assessment in post-comatose patients is difficult due to their limited behavioral repertoire; yet associated language deficits might lead to an underestimation of consciousness levels in unresponsive wakefulness syndrome (UWS) or minimally conscious state (MCS; -/+) diagnoses. We present a systematic review of studies from 2002 assessing residual language abilities with neuroimaging, electrophysiological or behavioral measures in patients with severe brain injury. Eighty-five articles including a total of 2278 patients were assessed for quality. The median percentages of patients showing residual implicit language abilities (i.e., cortical responses to specific words/sentences) were 33 % for UWS, 50 % for MCS- and 78 % for MCS + patients, whereas explicit language abilities (i.e., command-following using brain-computer interfaces) were reported in 20 % of UWS, 33 % of MCS- and 50 % of MCS + patients. Cortical responses to verbal stimuli increased along with consciousness levels and the progressive recovery of consciousness after a coma was paralleled by the reappearance of both implicit and explicit language processing. This review highlights the importance of language assessment in patients with disorders of consciousness.

Update on neuroimaging in disorders of consciousness

PURPOSE OF REVIEW

Neuroimaging has acquired a prominent place in the assessment of disorders of consciousness (DoC). Rapidly evolving technologies combined with state-of-the-art data analyses open new horizons to probe brain activity, but selecting appropriate imaging modalities from the plethora of available techniques can be challenging for clinicians. This update reviews selected advances in neuroimaging that demonstrate clinical relevance and translational potential in the assessment of severely brain-injured patients with DoC.

RECENT FINDINGS

Magnetic resonance imaging and high-density electroencephalography provide measurements of brain connectivity between functional networks, assessments of language function, detection of covert consciousness, and prognostic markers of recovery. Positron emission tomography can identify patients with preserved brain metabolism despite clinical unresponsiveness and can measure glucose consumption rates in targeted brain regions. Transcranial magnetic stimulation and near-infrared spectroscopy are noninvasive and practical tools with promising clinical applications.

SUMMARY

Each neuroimaging technique conveys advantages and pitfalls to assess consciousness. We recommend a multimodal approach in which complementary techniques provide diagnostic and prognostic information about brain function. Patients demonstrating neuroimaging evidence of covert consciousness may benefit from early adapted rehabilitation. Translating methodological advances to clinical care will require the implementation of recently published international guidelines and the integration of neuroimaging techniques into patient-centered decision-making algorithms.

The Brief Evaluation of Receptive Aphasia test for the detection of language impairment in patients with severe brain injury

PRIMARY OBJECTIVE

The assessment of language in patients post-comatose patients is limited by their reduced behavioral repertoire. We developed the Brief Evaluation of Receptive Aphasia (BERA) tool for assessing phonological, semantic and morphosyntactic abilities in patients with severe brain injury based on visual fixation responses.

RESEARCH DESIGN

Prospective cross-sectional study and case reports.

METHODS AND PROCEDURE

The BERA and Language Screening Test were first administered to 52 conscious patients with aphasia on two consecutive days in order to determine the validity and reliability of the BERA. Four post-comatose patients were further examined with the BERA, the Coma Recovery Scale-Revised (CRS-R), positron emission tomography and structural magnetic resonance imaging.

MAIN OUTCOME AND RESULTS

The BERA showed satisfactory intra- and inter-rater reliability, as well as internal and concurrent validity in patients with aphasia. The BERA scores indicated selective receptive difficulties for phonological, semantic and particularly morphosyntactic abilities in post-comatose patients. These results were in line with the cortical distribution of brain lesions.

CONCLUSIONS

The BERA may complement the widely used CRS-R for assessing and diagnosing patients with disorders of consciousness by providing a systematic and detailed characterization of residual language abilities.

Covert Cognition in Disorders of Consciousness: A Meta-Analysis

Covert cognition in patients with disorders of consciousness represents a real diagnostic conundrum for clinicians. In this meta-analysis, our main objective was to identify clinical and demographic variables that are more likely to be associated with responding to an active paradigm. Among 2018 citations found on PubMed, 60 observational studies were found relevant. Based on the QUADAS-2, 49 studies were considered. Data from 25 publications were extracted and included in the meta-analysis. Most of these studies used electrophysiology as well as counting tasks or mental imagery. According to our statistical analysis, patients clinically diagnosed as being in a vegetative state and in a minimally conscious state minus (MCS-) show similar likelihood in responding to active paradigm and responders are most likely suffering from a traumatic brain injury. In the future, multi-centric studies should be performed in order to increase sample size, with similar methodologies and include structural and functional neuroimaging in order to identify cerebral markers related to such a challenging diagnosis.

Update on diagnosis in disorders of consciousness

INTRODUCTION

New guidelines regarding the diagnosis of disorders of consciousness (DOC) (such as vegetative state and minimally conscious state) have recently been published by the American Academy of Neurology and the European Academy of Neurology. This follows an impressive number of prospective studies performed on DOC and recent multi-centric studies with larger sample size, which have gathered precious information on the recovery of cohort of patients through years and which now call for a better management of patients with DOC.

AREAS COVERED

This review will discuss recent updates on the clinical entities of DOC, the challenges for an accurate diagnosis and the last developments in diagnostic tools.

EXPERT OPINION

The authors will also discuss the impact of the new guidelines on their way of diagnosing patients and how diagnosis will most likely change in a near future.