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Roquet D, Foucher JR, Froehlig P, Renard F, Pottecher J, Besancenot H, Schneider F, Schenck M, Kremer S. Resting-state networks distinguish locked-in from vegetative state patients. Neuroimage Clin 2016; 12:16-22. [PMID: 27330978 PMCID: PMC4913176 DOI: 10.1016/j.nicl.2016.06.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2015] [Revised: 02/29/2016] [Accepted: 06/05/2016] [Indexed: 02/06/2023]
Abstract
PURPOSE Locked-in syndrome and vegetative state are distinct outcomes from coma. Despite their differences, they are clinically difficult to distinguish at the early stage and current diagnostic tools remain insufficient. Since some brain functions are preserved in locked-in syndrome, we postulated that networks of spontaneously co-activated brain areas might be present in locked-in patients, similar to healthy controls, but not in patients in a vegetative state. METHODS Five patients with locked-in syndrome, 12 patients in a vegetative state and 19 healthy controls underwent a resting-state fMRI scan. Individual spatial independent component analysis was used to separate spontaneous brain co-activations from noise. These co-activity maps were selected and then classified by two raters as either one of eight resting-state networks commonly shared across subjects or as specific to a subject. RESULTS The numbers of spontaneous co-activity maps, total resting-state networks, and resting-state networks underlying high-level cognitive activity were shown to differentiate controls and locked-in patients from patients in a vegetative state. Analyses of each common resting-state network revealed that the default mode network accurately distinguished locked-in from vegetative-state patients. The frontoparietal network also had maximum specificity but more limited sensitivity. CONCLUSIONS This study reinforces previous reports on the preservation of the default mode network in locked-in syndrome in contrast to vegetative state but extends them by suggesting that other networks might be relevant to the diagnosis of locked-in syndrome. The aforementioned analysis of fMRI brain activity at rest might be a step in the development of a diagnostic biomarker to distinguish locked-in syndrome from vegetative state.
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Affiliation(s)
- Daniel Roquet
- ICube, UMR 7357, UdS, CNRS, Fédération de médecine translationnelle de Strasbourg (FMTS), Université de Strasbourg, Strasbourg, France
- Université de Strasbourg, Fédération de Médecine Translationnelle de Strasbourg (FMTS), France
| | - Jack R. Foucher
- ICube, UMR 7357, UdS, CNRS, Fédération de médecine translationnelle de Strasbourg (FMTS), Université de Strasbourg, Strasbourg, France
- Université de Strasbourg, Fédération de Médecine Translationnelle de Strasbourg (FMTS), France
- Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | | | - Félix Renard
- FRE AGEIS, Université Grenoble Alpes, Grenoble, France
| | - Julien Pottecher
- Université de Strasbourg, Fédération de Médecine Translationnelle de Strasbourg (FMTS), France
- Hôpitaux Universitaires de Strasbourg, Strasbourg, France
- Institut de Physiologie, Equipe d'Accueil EA3072 “Mitochondrie, stress oxydant et protection musculaire”, Strasbourg, France
| | - Hortense Besancenot
- Université de Strasbourg, Fédération de Médecine Translationnelle de Strasbourg (FMTS), France
- Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Francis Schneider
- Université de Strasbourg, Fédération de Médecine Translationnelle de Strasbourg (FMTS), France
- Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Maleka Schenck
- Université de Strasbourg, Fédération de Médecine Translationnelle de Strasbourg (FMTS), France
- Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Stéphane Kremer
- ICube, UMR 7357, UdS, CNRS, Fédération de médecine translationnelle de Strasbourg (FMTS), Université de Strasbourg, Strasbourg, France
- Université de Strasbourg, Fédération de Médecine Translationnelle de Strasbourg (FMTS), France
- Hôpitaux Universitaires de Strasbourg, Strasbourg, France
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