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Threlkeld ZD, Bodien YG, Edlow BL. A scientific approach to diagnosis of disorders of consciousness. HANDBOOK OF CLINICAL NEUROLOGY 2025; 207:49-66. [PMID: 39986727 DOI: 10.1016/b978-0-443-13408-1.00003-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/24/2025]
Abstract
Disorder of consciousness (DoC) are the shared clinical manifestation of severe brain injuries resulting from a variety of etiologies. The nosology of DoC, as well as the armamentarium of methods available to diagnose it, has rapidly evolved. As a result, the diagnosis of DoC is complex and dynamic. We offer an evidence-based approach to DoC diagnosis, highlighting the challenges and pitfalls therein. Accordingly, we summarize the contemporary taxonomy of DoC and its development. We discuss the standardized behavioral diagnostic tools that form the foundation of DoC diagnosis, the evidence for their use, and their limitations. We also highlight recent advances in functional MRI (fMRI) and electroencephalography (EEG) techniques to increase the sensitivity and specificity of DoC diagnosis. We discuss the concept of covert consciousness (i.e., cognitive motor dissociation) as a discrete diagnostic category of DoC, as well as its diagnostic implications. Finally, we underscore issues of neuroethics and equity raised by contemporary models of DoC.
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Affiliation(s)
- Zachary D Threlkeld
- Department of Neurology, Stanford School of Medicine, Stanford, CA, United States.
| | - Yelena G Bodien
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Charlestown, MA, United States
| | - Brian L Edlow
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
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Boerwinkle VL, Nowlen MA, Vazquez JE, Arhin MA, Reuther WR, Cediel EG, McCarty PJ, Manjón I, Jubran JH, Guest AC, Gillette KD, Nowlen FM, Pines AR, Kazemi MH, Qaqish BF. Resting-state fMRI seizure onset localization meta-analysis: comparing rs-fMRI to other modalities including surgical outcomes. FRONTIERS IN NEUROIMAGING 2024; 3:1481858. [PMID: 39742390 PMCID: PMC11685199 DOI: 10.3389/fnimg.2024.1481858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2024] [Accepted: 11/13/2024] [Indexed: 01/03/2025]
Abstract
Objective Resting-state functional MRI (rs-fMRI) may localize the seizure onset zone (SOZ) for epilepsy surgery, when compared to intracranial EEG and surgical outcomes, per a prior meta-analysis. Our goals were to further characterize this agreement, by broadening the queried rs-fMRI analysis subtypes, comparative modalities, and same-modality comparisons, hypothesizing SOZ-signal strength may overcome this heterogeneity. Methods PubMed, Embase, Scopus, Web of Science, and Google Scholar between April 2010 and April 2020 via PRISMA guidelines for SOZ-to-established-modalities were screened. Odd ratios measured agreement between SOZ and other modalities. Fixed- and random-effects analyses evaluated heterogeneity of odd ratios, with the former evaluating differences in agreement across modalities and same-modality studies. Results In total, 9,550 of 14,384 were non-duplicative articles and 25 met inclusion criteria. Comparative modalities were EEG 7, surgical outcome 6, intracranial EEG 5, anatomical MRI 4, EEG-fMRI 2, and magnetoencephalography 1. Independent component analysis 9 and seed-based analysis 8 were top rs-fMRI methods. Study-level odds ratio heterogeneity in both the fixed- and random-effects analysis was significant (p < 0.001). Marked cross-modality and same-modality systematic differences in agreement between rs-fMRI and the comparator were present (p = 0.005 and p = 0.002), respectively, with surgical outcomes having higher agreement than EEG (p = 0.002) and iEEG (p = 0.007). The estimated population mean sensitivity and specificity were 0.91 and 0.09, with predicted values across studies ranging from 0.44 to 0.96 and 0.02 to 0.67, respectively. Significance We evaluated centrality and heterogeneity in SOZ agreement between rs-fMRI and comparative modalities using a wider variety of rs-fMRI analyzing subtypes and comparative modalities, compared to prior. Strong evidence for between-study differences in the agreement odds ratio was shown by both the fixed- and the random-effects analyses, attributed to rs-fMRI analysis variability. Agreement with rs-fMRI differed by modality type, with surgical outcomes having higher agreement than EEG and iEEG. Overall, sensitivity was high, but specificity was low, which may be attributed in part to differences between other modalities.
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Affiliation(s)
- Varina L. Boerwinkle
- Division of Child Neurology, University of North Carolina, School of Medicine, Chapel Hill, NC, United States
| | - Mary A. Nowlen
- Department of Obstetrics and Gynecology, Banner University Medical Center, Phoenix, AZ, United States
| | - Jesus E. Vazquez
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Martin A. Arhin
- University of North Carolina, School of Medicine, Chapel Hill, NC, United States
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
| | - William R. Reuther
- Division of Child Neurology, University of North Carolina, School of Medicine, Chapel Hill, NC, United States
| | - Emilio G. Cediel
- Division of Child Neurology, University of North Carolina, School of Medicine, Chapel Hill, NC, United States
| | | | - Iliana Manjón
- Department of Psychiatry, University of Arizona College of Medicine, Phoenix, AZ, United States
| | - Jubran H. Jubran
- Department of Neurosurgery, University of California, San Diego, San Diego, CA, United States
| | - Ashley C. Guest
- University of Arizona College of Medicine, Phoenix, AZ, United States
| | - Kirsten D. Gillette
- Division of Child Neurology, University of North Carolina, School of Medicine, Chapel Hill, NC, United States
| | | | - Andrew R Pines
- Department of Psychiatry, Brigham & Women’s Hospital, Boston, MA, United States
| | - Meitra H. Kazemi
- Division of Child Neurology, University of North Carolina, School of Medicine, Chapel Hill, NC, United States
| | - Bahjat F. Qaqish
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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Edlow BL, Menon DK. Covert Consciousness in the ICU. Crit Care Med 2024; 52:1414-1426. [PMID: 39145701 DOI: 10.1097/ccm.0000000000006372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
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.
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Affiliation(s)
- Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA
| | - David K Menon
- University Division of Anaesthesia, University of Cambridge, Addenbrooke's Hospital Cambridge, Cambridge, United Kingdom
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Young MJ, Kazazian K, Fischer D, Lissak IA, Bodien YG, Edlow BL. Disclosing Results of Tests for Covert Consciousness: A Framework for Ethical Translation. Neurocrit Care 2024; 40:865-878. [PMID: 38243150 PMCID: PMC11147696 DOI: 10.1007/s12028-023-01899-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 11/22/2023] [Indexed: 01/21/2024]
Abstract
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.
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Affiliation(s)
- Michael J Young
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 101 Merrimac Street, Suite 310, Boston, MA, 02114, USA.
| | - Karnig Kazazian
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 101 Merrimac Street, Suite 310, Boston, MA, 02114, USA
- Western Institute of Neuroscience, Western University, London, ON, Canada
| | - David Fischer
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - India A Lissak
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 101 Merrimac Street, Suite 310, Boston, MA, 02114, USA
| | - Yelena G Bodien
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 101 Merrimac Street, Suite 310, Boston, MA, 02114, USA
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 101 Merrimac Street, Suite 310, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
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Edlow BL, Boerwinkle VL, Annen J, Boly M, Gosseries O, Laureys S, Mukherjee P, Puybasset L, Stevens RD, Threlkeld ZD, Newcombe VFJ, Fernandez-Espejo D. Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Neuroimaging. Neurocrit Care 2023; 39:611-617. [PMID: 37552410 DOI: 10.1007/s12028-023-01794-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 06/22/2023] [Indexed: 08/09/2023]
Abstract
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.
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Affiliation(s)
- Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.
| | - Varina L Boerwinkle
- Clinical Resting-State Functional Magnetic Resonance Imaging Laboratory and Service, Department of Neurology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Jitka Annen
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre de Cerveau2, University Hospital of Liège, Liège, Belgium
| | - Melanie Boly
- Department of Neurology, University of Wisconsin, Madison, WI, USA
- Department of Psychiatry, Wisconsin Institute for Sleep and Consciousness, University of Wisconsin, Madison, WI, USA
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre de Cerveau2, University Hospital of Liège, Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre de Cerveau2, University Hospital of Liège, Liège, Belgium
- CERVO Research Institute, Laval University, Quebec, Canada
| | - Pratik Mukherjee
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Louis Puybasset
- Department of Anesthesiology and Intensive Care, Groupe Hospitalier Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Robert D Stevens
- Departments of Anesthesiology and Critical Care Medicine, Neurology, Radiology, and Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zachary D Threlkeld
- Department of Neurology, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Davinia Fernandez-Espejo
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, UK
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Lissak IA, Edlow BL, Rosenthal E, Young MJ. Ethical Considerations in Neuroprognostication Following Acute Brain Injury. Semin Neurol 2023; 43:758-767. [PMID: 37802121 DOI: 10.1055/s-0043-1775597] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/08/2023]
Abstract
Neuroprognostication following acute brain injury (ABI) is a complex process that involves integrating vast amounts of information to predict a patient's likely trajectory of neurologic recovery. In this setting, critically evaluating salient ethical questions is imperative, and the implications often inform high-stakes conversations about the continuation, limitation, or withdrawal of life-sustaining therapy. While neuroprognostication is central to these clinical "life-or-death" decisions, the ethical underpinnings of neuroprognostication itself have been underexplored for patients with ABI. In this article, we discuss the ethical challenges of individualized neuroprognostication including parsing and communicating its inherent uncertainty to surrogate decision-makers. We also explore the population-based ethical considerations that arise in the context of heterogenous prognostication practices. Finally, we examine the emergence of artificial intelligence-aided neuroprognostication, proposing an ethical framework relevant to both modern and longstanding prognostic tools.
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Affiliation(s)
- India A Lissak
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Brian L Edlow
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Eric Rosenthal
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Michael J Young
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
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Boerwinkle VL, Gillette K, Rubinos CA, Broman-Fulks J, Aseem F, DeHoff GK, Arhin M, Cediel E, Strohm T. Functional MRI for Acute Covert Consciousness: Emerging Data and Implementation Case Series. Semin Neurol 2023; 43:712-734. [PMID: 37788679 DOI: 10.1055/s-0043-1775845] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Although research studies have begun to demonstrate relationships between disorders of consciousness and brain network biomarkers, there are limited data on the practical aspects of obtaining such network biomarkers to potentially guide care. As the state of knowledge continues to evolve, guidelines from professional societies such as the American and European Academies of Neurology and many experts have advocated that the risk-benefit ratio for the assessment of network biomarkers has begun to favor their application toward potentially detecting covert consciousness. Given the lack of detailed operationalization guidance and the context of the ethical implications, herein we offer a roadmap based on local institutional experience with the implementation of functional MRI in the neonatal, pediatric, and adult intensive care units of our local government-supported health system. We provide a case-based demonstrative approach intended to review the current literature and to assist with the initiation of such services at other facilities.
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Affiliation(s)
- Varina L Boerwinkle
- Division of Child Neurology, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Kirsten Gillette
- Division of Child Neurology, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Clio A Rubinos
- Division of Neurocritical Care, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Jordan Broman-Fulks
- Division of Child Neurology, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Fazila Aseem
- Division of Neurocritical Care, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Grace K DeHoff
- Division of Neurocritical Care, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Martin Arhin
- Division of Child Neurology, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Emilio Cediel
- Division of Child Neurology, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Tamara Strohm
- Division of Neurocritical Care, University of North Carolina School of Medicine, Chapel Hill, North Carolina
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Boerwinkle VL, Sussman BL, Broman-Fulks J, Garzon-Cediel E, Gillette K, Reuther WR, Scher MS. Treatable brain network biomarkers in children in coma using task and resting-state functional MRI: a case series. Front Neurol 2023; 14:1227195. [PMID: 37638177 PMCID: PMC10448513 DOI: 10.3389/fneur.2023.1227195] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 07/20/2023] [Indexed: 08/29/2023] Open
Abstract
The withdrawal of life-sustaining therapies is frequently considered for pediatric patients with severe acute brain injuries who are admitted to the intensive care unit. However, it is worth noting that some children with a resultant poor neurological status may ultimately survive and achieve a positive neurological outcome. Evidence suggests that adults with hidden consciousness may have a more favorable prognosis compared to those without it. Currently, no treatable network disorders have been identified in cases of severe acute brain injury, aside from seizures detectable through an electroencephalogram (EEG) and neurostimulation via amantadine. In this report, we present three cases in which multimodal brain network evaluation played a helpful role in patient care. This evaluation encompassed various assessments such as continuous video EEG, visual-evoked potentials, somatosensory-evoked potentials, auditory brainstem-evoked responses, resting-state functional MRI (rs-fMRI), and passive-based and command-based task-based fMRI. It is worth noting that the latter three evaluations are unique as they have not yet been established as part of the standard care protocol for assessing acute brain injuries in children with suppressed consciousness. The first patient underwent serial fMRIs after experiencing a coma induced by trauma. Subsequently, the patient displayed improvement following the administration of antiseizure medication to address abnormal signals. In the second case, a multimodal brain network evaluation uncovered covert consciousness, a previously undetected condition in a pediatric patient with acute brain injury. In both patients, this discovery potentially influenced decisions concerning the withdrawal of life support. Finally, the third patient serves as a comparative control case, demonstrating the absence of detectable networks. Notably, this patient underwent the first fMRI prior to experiencing brain death as a pediatric patient. Consequently, this case series illustrates the clinical feasibility of employing multimodal brain network evaluation in pediatric patients. This approach holds potential for clinical interventions and may significantly enhance prognostic capabilities beyond what can be achieved through standard testing methods alone.
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Affiliation(s)
- Varina L. Boerwinkle
- Division of Pediatric Neurology, Department of Neurology, University of North Carolina, Chapel Hill, NC, United States
| | - Bethany L. Sussman
- Neuroscience Research, Barrow Neurological Institute at Phoenix Children's Hospital, Phoenix, AZ, United States
| | - Jordan Broman-Fulks
- Division of Pediatric Neurology, Department of Neurology, University of North Carolina, Chapel Hill, NC, United States
| | - Emilio Garzon-Cediel
- Division of Pediatric Neurology, Department of Neurology, University of North Carolina, Chapel Hill, NC, United States
| | - Kirsten Gillette
- Division of Pediatric Neurology, Department of Neurology, University of North Carolina, Chapel Hill, NC, United States
| | - William R. Reuther
- Division of Pediatric Neurology, Department of Neurology, University of North Carolina, Chapel Hill, NC, United States
| | - Mark S. Scher
- Division of Pediatric Neurology, Emeritus Scholar Tenured Full Professor Case Western Reserve University School of Medicine Department of Pediatrics, Rainbow Babies and Children's Hospital/University Hospitals Cleveland Medical Center, Cleveland, OH, United States
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Edlow BL, Fecchio M, Bodien YG, Comanducci A, Rosanova M, Casarotto S, Young MJ, Li J, Dougherty DD, Koch C, Tononi G, Massimini M, Boly M. Measuring Consciousness in the Intensive Care Unit. Neurocrit Care 2023; 38:584-590. [PMID: 37029315 PMCID: PMC11421303 DOI: 10.1007/s12028-023-01706-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 02/23/2023] [Indexed: 04/09/2023]
Abstract
Early reemergence of consciousness predicts long-term functional recovery for patients with severe brain injury. However, tools to reliably detect consciousness in the intensive care unit are lacking. Transcranial magnetic stimulation electroencephalography has the potential to detect consciousness in the intensive care unit, predict recovery, and prevent premature withdrawal of life-sustaining therapy.
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Affiliation(s)
- Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.
| | - Matteo Fecchio
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Yelena G Bodien
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Angela Comanducci
- IRCCS Fondazione Don Carlo Gnocchi Onlus, Milan, Italy
- Università Campus Bio-Medico di Roma, Rome, Italy
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Silvia Casarotto
- IRCCS Fondazione Don Carlo Gnocchi Onlus, Milan, Italy
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Michael J Young
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jian Li
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Darin D Dougherty
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Christof Koch
- MindScope Program, Allen Institute, Seattle, WA, USA
- Tiny Blue Dot Foundation, Santa Monica, CA, USA
| | - Giulio Tononi
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Marcello Massimini
- IRCCS Fondazione Don Carlo Gnocchi Onlus, Milan, Italy
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Melanie Boly
- Department of Neurology, University of Wisconsin-Madison, Madison, WI, USA
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