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See detailWhite Matter Changes in Comatose Survivors of Anoxic Ischemic Encephalopathy and Traumatic Brain Injury: Comparative Diffusion-Tensor Imaging Study
Van Der Eerden, Anke; Khalilzadeh, Omid; Perlbarg, Vincent et al

in Radiology (2014), 270

Purpose:To analyze white matter pathologic abnormalities by using diffusion-tensor (DT) imaging in a multicenter prospective cohort of comatose patients following cardiac arrest or traumatic brain injury ... [more ▼]

Purpose:To analyze white matter pathologic abnormalities by using diffusion-tensor (DT) imaging in a multicenter prospective cohort of comatose patients following cardiac arrest or traumatic brain injury (TBI). Materials and Methods: Institutional review board approval and informed consent from proxies and control subjects were obtained. DT imaging was performed 5–57 days after insult in 49 cardiac arrest and 40 TBI patients. To control for DT imaging–processing variability, patients’ values were normalized to those of 111 control subjects. Automated segmentation software calculated normalized axial diffusivity (λ1) and radial diffusivity (λ) in 19 predefined white matter regions of interest (ROIs). DT imaging variables were compared by using general linear modeling, and side-to-side Pearson correlation coefficients were calculated. P values were corrected for multiple testing (Bonferroni). Results:In central white matter, λ1 differed from that in control subjects in six of seven TBI ROIs and five of seven cardiac arrest ROIs (all P < .01). The λ differed from that in control subjects in all ROIs in both patient groups (P < .01). In hemispheres, λ1 was decreased compared with that in control subjects in three of 12 TBI ROIs (P < .05) and nine of 12 cardiac arrest ROIs (P < .01). The λ was increased in all TBI ROIs (P < .01) and in seven of 12 cardiac arrest ROIs (P < .05). Cerebral hemisphere λ1 was lower in cardiac arrest than in TBI in six of 12 ROIs (P < .01), while λ was higher in TBI than in cardiac arrest in eight of 12 ROIs (P < .01). Diffusivity values were symmetrically distributed in cardiac arrest (P < .001 for side-to-side correlation) but not in TBI patients. Conclusion:DT imaging findings are consistent with the known predominance of cerebral hemisphere axonal injury in cardiac arrest and chiefly central myelin injury in TBI. This consistency supports the validity of DT imaging for differentiating axon and myelin damage in vivo in humans. [less ▲]

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See detailAssessment of White Matter Injury and Outcome in Severe Brain Trauma: A Prospective Multicenter Cohort
Galanaud, Damien; Perlbarg, Vincent; Gupta, Rajiv et al

in Anesthesiology (2012), 117(6), 1300-1310

BACKGROUND:: Existing methods to predict recovery after severe traumatic brain injury lack accuracy. The aim of this study is to determine the prognostic value of quantitative diffusion tensor imaging ... [more ▼]

BACKGROUND:: Existing methods to predict recovery after severe traumatic brain injury lack accuracy. The aim of this study is to determine the prognostic value of quantitative diffusion tensor imaging (DTI). METHODS:: In a multicenter study, the authors prospectively enrolled 105 patients who remained comatose at least 7 days after traumatic brain injury. Patients underwent brain magnetic resonance imaging, including DTI in 20 preselected white matter tracts. Patients were evaluated at 1 yr with a modified Glasgow Outcome Scale. A composite DTI score was constructed for outcome prognostication on this training database and then validated on an independent database (n = 38). DTI score was compared with the International Mission for Prognosis and Analysis of Clinical Trials Score. RESULTS:: Using the DTI score for prediction of unfavorable outcome on the training database, the area under the receiver operating characteristic curve was 0.84 (95% CI: 0.75-0.91). The DTI score had a sensitivity of 64% and a specificity of 95% for the prediction of unfavorable outcome. On the validation-independent database, the area under the receiver operating characteristic curve was 0.80 (95% CI: 0.54-0.94). On the training database, reclassification methods showed significant improvement of classification accuracy (P < 0.05) compared with the International Mission for Prognosis and Analysis of Clinical Trials score. Similar results were observed on the validation database. CONCLUSIONS:: White matter assessment with quantitative DTI increases the accuracy of long-term outcome prediction compared with the available clinical/radiographic prognostic score. [less ▲]

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See detailSleep Spindles Predict Neural and Behavioral Changes in Motor Sequence Consolidation
Barakat, Marc; Carrier, Julie; Debas, Karen et al

in Human Brain Mapping (2012), Epub ahead of print

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See detailDiffusion Tensor Imaging to Predict Long-term Outcome after Cardiac Arrest. A Bicentric Pilot Study
Luyt, Charles-Edouard; Galanaud, Damien; Perlbarg, Vincent et al

in Anesthesiology (2012), 117(6), 1311-1321

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See detailDiffusion Tensor Imaging to Predict Long-term Outcome after Cardiac Arrest: A Bicentric Pilot Study.
Luyt, Charles-Edouard; Galanaud, Damien; Perlbarg, Vincent et al

in Anesthesiology (2012), 117(6), 1311-1321

BACKGROUND:: Prognostication in comatose survivors of cardiac arrest is a major clinical challenge. The authors' objective was to determine whether an assessment with diffusion tensor imaging, a brain ... [more ▼]

BACKGROUND:: Prognostication in comatose survivors of cardiac arrest is a major clinical challenge. The authors' objective was to determine whether an assessment with diffusion tensor imaging, a brain magnetic resonance imaging sequence, increases the accuracy of 1 yr functional outcome prediction in cardiac arrest survivors. METHODS:: Prospective, observational study in two intensive care units. Fifty-seven comatose survivors of cardiac arrest underwent brain magnetic resonance imaging. Fractional anisotropy (FA), a diffusion tensor imaging value, was measured in predefined white matter regions, and apparent diffusion coefficient was assessed in predefined grey matter regions. Prediction of unfavorable outcome at 1 yr was compared using four prognostic models: FA global, FA selected, apparent diffusion coefficient, and clinical classifiers. RESULTS:: Of the 57 patients included in the study, 49 had an unfavorable outcome at 12 months. Areas under the receiver operating characteristic curve (95% CI) to predict unfavorable outcome for the FA global, FA selected, clinical, and apparent diffusion coefficient models were 0.92 (0.82-0.98), 0.96 (0.87-0.99), 0.78 (0.65-0.88), and 0.86 (0.74-0.94), respectively. The FA selected model had the best overall accuracy for predicting outcome, with a score above 0.44 having 94% (95% CI, 83-99%) sensitivity and 100% (95% CI, 63-100%) specificity for the prediction of unfavorable outcome. CONCLUSION:: Quantitative diffusion tensor imaging indicates that white matter damage is widespread after cardiac arrest. A prognostic model based on FA values in selected white matter tracts seems to predict accurately 1 yr functional outcome. These preliminary results need to be confirmed in a larger population. [less ▲]

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See detailBrain functional integration decreases during propofol-induced loss of consciousness.
Schrouff, Jessica ULg; Perlbarg, Vincent; Boly, Mélanie ULg et al

in NeuroImage (2011), 57(1), 198-205

Consciousness has been related to the amount of integrated information that the brain is able to generate. In this paper, we tested the hypothesis that the loss of consciousness caused by propofol ... [more ▼]

Consciousness has been related to the amount of integrated information that the brain is able to generate. In this paper, we tested the hypothesis that the loss of consciousness caused by propofol anesthesia is associated with a significant reduction in the capacity of the brain to integrate information. To assess the functional structure of the whole brain, functional integration and partial correlations were computed from fMRI data acquired from 18 healthy volunteers during resting wakefulness and propofol-induced deep sedation. Total integration was significantly reduced from wakefulness to deep sedation in the whole brain as well as within and between its constituent networks (or systems). Integration was systematically reduced within each system (i.e., brain or networks), as well as between networks. However, the ventral attentional network maintained interactions with most other networks during deep sedation. Partial correlations further suggested that functional connectivity was particularly affected between parietal areas and frontal or temporal regions during deep sedation. Our findings suggest that the breakdown in brain integration is the neural correlate of the loss of consciousness induced by propofol. They stress the important role played by parietal and frontal areas in the generation of consciousness. [less ▲]

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See detailChanges in functional interactions during anaesthesia-induced loss of consciousness
Schrouff, Jessica ULg; Perlbarg, Vincent; Boly, Mélanie ULg et al

Poster (2010, December 12)

Consciousness has been related to the amount of integrated information that the brain is able to generate. In this paper, we tested the hypothesis that the loss of consciousness caused by propofol ... [more ▼]

Consciousness has been related to the amount of integrated information that the brain is able to generate. In this paper, we tested the hypothesis that the loss of consciousness caused by propofol anesthesia is associated with a significant reduction in the capacity of the brain to integrate information. To assess the functional structure of the whole brain, functional integration and partial correlations were computed from fMRI data acquired from 18 healthy volunteers during resting wakefulness and propofol-induced deep sedation. Total integration was significantly reduced from wakefulness to deep sedation in the whole brain as well as within and between its constituent networks (or systems). Integration was systematically reduced within each system (i.e., brain or networks), as well as between networks. However, the ventral attentional network maintained interactions with most other networks during deep sedation. Partial correlations further suggested that functional connectivity was particularly affected between parietal areas and frontal or temporal regions during deep sedation. Our findings suggest that the breakdown in brain integration is the neural correlate of the loss of consciousness induced by propofol. They stress the important role played by parietal and frontal areas in the generation of consciousness. [less ▲]

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See detailNeural correlates mediating the consolidation of visuomotor adapted actions : A study on the role of night sleep versus the passage of daytime
Debas, Karen; Carrier, Julie; Orban, Pierre et al

in NeuroImage (2009), 45(Suppl. 1),

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See detailStriatal Contribution to sleep-dependent motor consolidation
Debas, Karen; Carrier, Julie; Orban, Pierre et al

in NeuroImage (2008), 41(Suppl. 1),

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