Resting-State fMRI in Chronic Patients with Disorders of Consciousness: The Role of Lower-Order Networks for Clinical Assessment

Differential brain activity in patients with disorders of consciousness: a 3-month rs-fMRI study using amplitude of low-frequency fluctuation

Introduction

Disorders of consciousness (DoC) from severe brain injuries have significant impacts. However, further research on nuanced biomarkers is needed to fully understand the condition. This study employed resting-state functional MRI (rs-fMRI) and the amplitude of low-frequency fluctuation (ALFF) to investigate differential brain activity in patients with DoC following spinal cord stimulation (SCS) therapy. It also assessed the predictive value of rs-fMRI and ALFF in determining the consciousness levels at 3 months post-therapy.

Methods

We analyzed rs-fMRI data from 31 patients with traumatic brain injury (TBI) and 22 with non-traumatic brain injury (non-TBI) diagnosed with DoC. ALFF was measured before SCS therapy, and clinical outcomes were assessed 3 months later using the Coma Recovery Scale-Revised.

Results

Patients with TBI showed increased ALFF in the thalamus and anterior cingulate cortex, whereas the middle occipital lobe showed decreased ALFF. In the non-TBI group, a higher ALFF was noted in the precuneus, with a reduced ALFF in the occipital and temporal lobes. Patients with improved consciousness post-SCS exhibited distinct ALFF patterns compared with those with unchanged consciousness, particularly in the posterior cingulate and occipital regions.

Conclusion

The application of ALFF in rs-fMRI may be a predictive tool for post-treatment outcomes in patients with DoC of varying etiologies. Differential ALFF in specific brain regions could indicate the likelihood of improvement in consciousness following SCS therapy.

Clinical trial registration

https://www.chictr.org.cn/, Identifier ChiCTR2300069756.

Functional brain alterations in COVID-19 patients using resting-state fMRI: a systematic review

This study systematically reviews the available evidence on resting-state functional magnetic resonance imaging (rs-fMRI) related to neurological symptoms and cognitive declines in COVID-19 patients. We followed PRISMA guidelines and looked up the PubMed, and Scopus databases for articles search on COVID-19 patients with neurological impairments, and functional connectivity alteration using rs-fMRI technique. Articles published between January 1, 2020, and May 31, 2024, are included in this study. The Quality Assessment Tool for Observational Prospective and Cross-Sectional Studies from the National Heart, Lung, and Blood Institute (NHLBI) was used to assess the quality of papers. A total of 15 articles met the inclusion criteria. The result reveals that the most prevalent neurological impairment associated with COVID-19 was cognitive decline, encompassing issues in attention, memory, processing speed, executive functions, language, and visuospatial ability. The brain connectivity results reveal that two brain areas were functionally altered; the prefrontal cortex and parahippocampus. The functional connectivity mainly increased in the frontal, temporal, and anterior piriform cortex, and reduced in the cerebellum, superior orbitofrontal cortex, and middle temporal gyrus, which also correlated with cognitive decline. The findings of neurological symptoms indicate one study reported a Disorder of Consciousness (DoC), and four studies reported COVID-19 patients with olfactory dysfunction. The present study concludes that COVID-19 can alter brain functional connectivity and offers significant insight into how COVID-19 affects the neuronal foundation of cognitive decline and other neurological impairments.

Neuroimaging biomarkers for the diagnosis and prognosis of patients with disorders of consciousness

The progress in neuroimaging and electrophysiological techniques has shown substantial promise in improving the clinical assessment of disorders of consciousness (DOC). Through the examination of both stimulus-induced and spontaneous brain activity, numerous comprehensive investigations have explored variations in brain activity patterns among patients with DOC, yielding valuable insights for clinical diagnosis and prognostic purposes. Nonetheless, reaching a consensus on precise neuroimaging biomarkers for patients with DOC remains a challenge. Therefore, in this review, we begin by summarizing the empirical evidence related to neuroimaging biomarkers for DOC using various paradigms, including active, passive, and resting-state approaches, by employing task-based fMRI, resting-state fMRI (rs-fMRI), electroencephalography (EEG), and positron emission tomography (PET) techniques. Subsequently, we conducted a review of studies examining the neural correlates of consciousness in patients with DOC, with the findings holding potential value for the clinical application of DOC. Notably, previous research indicates that neuroimaging techniques have the potential to unveil covert awareness that conventional behavioral assessments might overlook. Furthermore, when integrated with various task paradigms or analytical approaches, this combination has the potential to significantly enhance the accuracy of both diagnosis and prognosis in DOC patients. Nonetheless, the stability of these neural biomarkers still needs additional validation, and future directions may entail integrating diagnostic and prognostic methods with big data and deep learning approaches.

Prognostic Evaluation of Disorders of Consciousness by Using Resting-State fMRI: A Systematic Review

Background: This review focuses on the prognostic role of resting-state functional magnetic resonance imaging (fMRI) in disorders of consciousness (DOCs). Several studies were conducted to determine the diagnostic accuracy in DOC patients to identify prognostic markers and to understand the neural correlates of consciousness. A correct diagnosis of consciousness in unresponsive or minimally responsive patients is important for prognostic and therapeutic management. Functional connectivity is considered as an important tool for the formulation of cerebral networks; it takes into account the primary sensorimotor, language, visual and central executive areas, where fMRI studies show damage in brain connectivity in the areas of frontoparietal networks in DOC patients. Methods: The integration of neuroimaging or neurophysiological methods could improve our knowledge of the neural correlates of clinical response after an acquired brain injury. The use of MRI is widely reported in the literature in different neurological diseases. In particular, fMRI is the most widely used brain-imaging technique to investigate the neural mechanisms underlying cognition and motor function. We carried out a detailed literature search following the relevant guidelines (PRISMA), where we collected data and results on patients with disorders of consciousness from the studies performed. Results: In this review, 12 studies were selected, which showed the importance of the prognostic role of fMRI for DOCs. Conclusions: Currently there are still few studies on this topic. Future studies using fMRI are to be considered an added value for the prognosis and management of DOCs.

Re-awakening the brain: Forcing transitions in disorders of consciousness by external in silico perturbation

A fundamental challenge in neuroscience is accurately defining brain states and predicting how and where to perturb the brain to force a transition. Here, we investigated resting-state fMRI data of patients suffering from disorders of consciousness (DoC) after coma (minimally conscious and unresponsive wakefulness states) and healthy controls. We applied model-free and model-based approaches to help elucidate the underlying brain mechanisms of patients with DoC. The model-free approach allowed us to characterize brain states in DoC and healthy controls as a probabilistic metastable substate (PMS) space. The PMS of each group was defined by a repertoire of unique patterns (i.e., metastable substates) with different probabilities of occurrence. In the model-based approach, we adjusted the PMS of each DoC group to a causal whole-brain model. This allowed us to explore optimal strategies for promoting transitions by applying off-line in silico probing. Furthermore, this approach enabled us to evaluate the impact of local perturbations in terms of their global effects and sensitivity to stimulation, which is a model-based biomarker providing a deeper understanding of the mechanisms underlying DoC. Our results show that transitions were obtained in a synchronous protocol, in which the somatomotor network, thalamus, precuneus and insula were the most sensitive areas to perturbation. This motivates further work to continue understanding brain function and treatments of disorders of consciousness.

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.

Disorder of consciousness: Structural integrity of brain networks for the clinical assessment

AIM

When studying brain networks in patients with Disorders of Consciousness (DoC), it is important to evaluate the structural integrity of networks in addition to their functional activity. Here, we investigated whether structural MRI, together with clinical variables, can be useful for diagnostic purposes and whether a quantitative analysis is feasible in a group of chronic DoC patients.

METHODS

We studied 109 chronic patients with DoC and emerged from DoC with structural MRI: 65 in vegetative state/unresponsive wakefulness state (VS/UWS), 34 in minimally conscious state (MCS), and 10 with severe disability. MRI data were analyzed through qualitative and quantitative approaches.

RESULTS

The qualitative MRI analysis outperformed the quantitative one, which resulted to be hardly feasible in chronic DoC patients. The results of the qualitative approach showed that the structural integrity of HighOrder networks, altogether, had better diagnostic accuracy than LowOrder networks, particularly when the model included clinical variables (AUC = 0.83). Diagnostic differences between VS/UWS and MCS were stronger in anoxic etiology than vascular and traumatic etiology. MRI data of all LowOrder and HighOrder networks correlated with the clinical score. The integrity of the left hemisphere was associated with a better clinical status.

CONCLUSIONS

Structural integrity of brain networks is sensitive to clinical severity. When patients are chronic, the qualitative analysis of MRI data is indicated.

Functional networks in prolonged disorders of consciousness

Prolonged disorders of consciousness (DoC) are characterized by extended disruptions of brain activities that sustain wakefulness and awareness and are caused by various etiologies. During the past decades, neuroimaging has been a practical method of investigation in basic and clinical research to identify how brain properties interact in different levels of consciousness. Resting-state functional connectivity within and between canonical cortical networks correlates with consciousness by a calculation of the associated temporal blood oxygen level-dependent (BOLD) signal process during functional MRI (fMRI) and reveals the brain function of patients with prolonged DoC. There are certain brain networks including the default mode, dorsal attention, executive control, salience, auditory, visual, and sensorimotor networks that have been reported to be altered in low-level states of consciousness under either pathological or physiological states. Analysis of brain network connections based on functional imaging contributes to more accurate judgments of consciousness level and prognosis at the brain level. In this review, neurobehavioral evaluation of prolonged DoC and the functional connectivity within brain networks based on resting-state fMRI were reviewed to provide reference values for clinical diagnosis and prognostic evaluation.