1
|
Mathur R, Meyfroidt G, Robba C, Stevens RD. Neuromonitoring in the ICU - what, how and why? Curr Opin Crit Care 2024; 30:99-105. [PMID: 38441121 DOI: 10.1097/mcc.0000000000001138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
PURPOSE OF REVIEW We selectively review emerging noninvasive neuromonitoring techniques and the evidence that supports their use in the ICU setting. The focus is on neuromonitoring research in patients with acute brain injury. RECENT FINDINGS Noninvasive intracranial pressure evaluation with optic nerve sheath diameter measurements, transcranial Doppler waveform analysis, or skull mechanical extensometer waveform recordings have potential safety and resource-intensity advantages when compared to standard invasive monitors, however each of these techniques has limitations. Quantitative electroencephalography can be applied for detection of cerebral ischemia and states of covert consciousness. Near-infrared spectroscopy may be leveraged for cerebral oxygenation and autoregulation computation. Automated quantitative pupillometry and heart rate variability analysis have been shown to have diagnostic and/or prognostic significance in selected subtypes of acute brain injury. Finally, artificial intelligence is likely to transform interpretation and deployment of neuromonitoring paradigms individually and when integrated in multimodal paradigms. SUMMARY The ability to detect brain dysfunction and injury in critically ill patients is being enriched thanks to remarkable advances in neuromonitoring data acquisition and analysis. Studies are needed to validate the accuracy and reliability of these new approaches, and their feasibility and implementation within existing intensive care workflows.
Collapse
Affiliation(s)
- Rohan Mathur
- Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Geert Meyfroidt
- Department of Intensive Care Medicine, University Hospitals Leuven, Belgium and Laboratory of Intensive Care Medicine, Department of Cellular and Molecular Medicine, KU Leuven, Belgium
| | - Chiara Robba
- IRCCS Ospedale Policlinico San Martino, Genova, Italy
- Dipartimento di Scienze Chirurgiche e Diagnostiche Integrate, Università degli Studi di Genova, Genova, Italy
| | - Robert D Stevens
- Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore MD, USA
| |
Collapse
|
2
|
Fischer D, Edlow BL. Coma Prognostication After Acute Brain Injury: A Review. JAMA Neurol 2024:2815829. [PMID: 38436946 DOI: 10.1001/jamaneurol.2023.5634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2024]
Abstract
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.
Collapse
Affiliation(s)
- David Fischer
- Division of Neurocritical Care, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown
| |
Collapse
|
3
|
Casarotto S, Hassan G, Rosanova M, Sarasso S, Derchi CC, Trimarchi PD, Viganò A, Russo S, Fecchio M, Devalle G, Navarro J, Massimini M, Comanducci A. Dissociations between spontaneous electroencephalographic features and the perturbational complexity index in the minimally conscious state. Eur J Neurosci 2024; 59:934-947. [PMID: 38440949 DOI: 10.1111/ejn.16299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 12/21/2023] [Accepted: 02/13/2024] [Indexed: 03/06/2024]
Abstract
The analysis of spontaneous electroencephalogram (EEG) is a cornerstone in the assessment of patients with disorders of consciousness (DoC). Although preserved EEG patterns are highly suggestive of consciousness even in unresponsive patients, moderately or severely abnormal patterns are difficult to interpret. Indeed, growing evidence shows that consciousness can be present despite either large delta or reduced alpha activity in spontaneous EEG. Quantifying the complexity of EEG responses to direct cortical perturbations (perturbational complexity index [PCI]) may complement the observational approach and provide a reliable assessment of consciousness even when spontaneous EEG features are inconclusive. To seek empirical evidence of this hypothesis, we compared PCI with EEG spectral measures in the same population of minimally conscious state (MCS) patients (n = 40) hospitalized in rehabilitation facilities. We found a remarkable variability in spontaneous EEG features across MCS patients as compared with healthy controls: in particular, a pattern of predominant delta and highly reduced alpha power-more often observed in vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients-was found in a non-negligible number of MCS patients. Conversely, PCI values invariably fell above an externally validated empirical cutoff for consciousness in all MCS patients, consistent with the presence of clearly discernible, albeit fleeting, behavioural signs of awareness. These results confirm that, in some MCS patients, spontaneous EEG rhythms may be inconclusive about the actual capacity for consciousness and suggest that a perturbational approach can effectively compensate for this pitfall with practical implications for the individual patient's stratification and tailored rehabilitation.
Collapse
Affiliation(s)
- Silvia Casarotto
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Gabriel Hassan
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Simone Sarasso
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | | | | | | | - Simone Russo
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Matteo Fecchio
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Guya Devalle
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Jorge Navarro
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Marcello Massimini
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Angela Comanducci
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
- Università Campus Bio-Medico di Roma, Rome, Italy
| |
Collapse
|
4
|
Schiff ND, Diringer M, Diserens K, Edlow BL, Gosseries O, Hill NJ, Hochberg LR, Ismail FY, Meyer IA, Mikell CB, Mofakham S, Molteni E, Polizzotto L, Shah SA, Stevens RD, Thengone D. Brain-Computer Interfaces for Communication in Patients with Disorders of Consciousness: A Gap Analysis and Scientific Roadmap. Neurocrit Care 2024:10.1007/s12028-023-01924-w. [PMID: 38286946 DOI: 10.1007/s12028-023-01924-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 12/14/2023] [Indexed: 01/31/2024]
Abstract
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.
Collapse
Affiliation(s)
- Nicholas D Schiff
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY, USA.
| | - Michael Diringer
- Departments of Neurology and Neurosurgery, Washington University in St. Louis, St. Louis, MO, USA
| | - Karin Diserens
- Neurology and Acute Neurorehabilitation Unit, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Olivia Gosseries
- Coma Science Group, GIGA-Consciousness, Centre du Cerveau, University Hospital of Liège, University of Liège & Centre du Cerveau, Liège, Belgium
| | - N Jeremy Hill
- National Center for Adaptive Neurotechnologies, Stratton VA Medical Center, Albany, NY, USA
- Electrical & Computer Engineering Department, State University of New York at Albany, Albany, NY, USA
| | - Leigh R Hochberg
- Veterans Affairs Rehabilitation Research & Development Center for Neurorestoration and Neurotechnology, Rehabilitation Research & Development Service, Providence VA Medical Center, Providence, RI, USA
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Fatima Y Ismail
- Department of Pediatrics, United Arab Emirates University, Al Ain, United Arab Emirates
- Department of Neurology, Adjunct Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ivo A Meyer
- Neurology and Acute Neurorehabilitation Unit, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Centre for Advanced Research in Sleep Medicine and Integrated Trauma Centre, Integrated University Health and Social Services Centre (CIUSSS) du Nord-de-L'Île-de-Montréal, Montreal, QC, Canada
| | - Charles B Mikell
- Department of Neurosurgery, Stony Brook University Hospital, Stony Brook, NY, USA
| | - Sima Mofakham
- Department of Neurosurgery, Stony Brook University Hospital, Stony Brook, NY, USA
- Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Erika Molteni
- School of Biomedical Engineering and Imaging Sciences, and Centre for Medical Engineering, King's College London, London, UK
| | - Leonard Polizzotto
- Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA, USA
| | - Sudhin A Shah
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
| | - Robert D Stevens
- Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | | |
Collapse
|
5
|
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 2024:10.1007/s12028-023-01899-8. [PMID: 38243150 DOI: 10.1007/s12028-023-01899-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [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.
Collapse
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
| |
Collapse
|