Dataset Information

Multimodal FDG-PET and EEG assessment improves diagnosis and prognostication of disorders of consciousness.

ABSTRACT:

Introduction

Functional brain-imaging techniques have revealed that clinical examination of disorders of consciousness (DoC) can underestimate the conscious level of patients. FDG-PET metabolic index of the best preserved hemisphere (MIBH) has been reported as a promising measure of consciousness but has never been externally validated and compared with other brain-imaging diagnostic procedures such as quantitative EEG.

Methods

FDG-PET, quantitative EEG and cognitive evoked potential using an auditory oddball paradigm were performed in minimally conscious state (MCS) and vegetative state (VS) patient. We compared out-sample diagnostic and prognostic performances of PET-MIBH and EEG-based classification of conscious state to the current behavioral gold-standard, the Coma Recovery Scale - revised (CRS-R).

Results

Between January 2016 and October 2019, 52 patients were included: 21 VS and 31 MCS. PET-MIBH had an AUC of 0.821 [0.694-0.930], sensitivity of 79% [62-91] and specificity of 78% [56-93], not significantly different from EEG (p = 0.628). Their combination accurately identified almost all MCS patients with a sensitivity of 94% [79-99%] and specificity of 67% [43-85]. Multimodal assessment also identified VS patients with neural correlate of consciousness (4/7 (57%) vs. 1/14 (7%), p = 0.025) and patients with 6-month recovery of command-following (9/24 (38%) vs. 0/16 (0%), p = 0.006), outperforming each technique taken in isolation.

Conclusion

FDG-PET MIBH is an accurate and robust procedure across sites to diagnose MCS. Its combination with EEG-based classification of conscious state not only optimizes diagnostic performances but also allows to detect covert cognition and to predict 6-month command-following recovery demonstrating the added value of multimodal assessment of DoC.

SUBMITTER: Hermann B

PROVIDER: S-EPMC7921007 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Multimodal FDG-PET and EEG assessment improves diagnosis and prognostication of disorders of consciousness.

Hermann Bertrand B Stender Johan J Habert Marie-Odile MO Kas Aurélie A Denis-Valente Mélanie M Raimondo Federico F Pérez Pauline P Rohaut Benjamin B Sitt Jacobo Diego JD Naccache Lionel L

NeuroImage. Clinical 20210223

<h4>Introduction</h4>Functional brain-imaging techniques have revealed that clinical examination of disorders of consciousness (DoC) can underestimate the conscious level of patients. FDG-PET metabolic index of the best preserved hemisphere (MIBH) has been reported as a promising measure of consciousness but has never been externally validated and compared with other brain-imaging diagnostic procedures such as quantitative EEG.<h4>Methods</h4>FDG-PET, quantitative EEG and cognitive evoked potent ...[more]

PMID: 33652375

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Project description:IntroductionAssessing the awareness level in patients with disorders of consciousness (DOC) is made on the basis of exhibited behaviors. However, since motor signs of awareness (i.e., non-reflex motor responses) can be very subtle, differentiating the vegetative from minimally conscious states (which is in itself not clear-cut) is often challenging. Even the careful clinician relying on standardized scales may arrive at a wrong diagnosis.AimTo report our experience in tackling this problem by using two in-house use assessment procedures developed at Reuth Rehabilitation Hospital, and demonstrate their clinical significance by reviewing two cases.Methods(1) Reuth DOC Response Assessment (RDOC-RA) -administered in addition to the standardized tools, and emphasizes the importance of assessing a wide range of motor responses. In our experience, in some patients the only evidence for awareness may be a private specific movement that is not assessed by standard assessment tools. (2) Reuth DOC Periodic Intervention Model (RDOC-PIM) - current literature regarding assessment and diagnosis in DOC refers mostly to the acute phase of up to 1 year post injury. However, we have found major changes in responsiveness occurring 1 year or more post-injury in many patients. Therefore, we conduct periodic assessments at predetermined times points to ensure patients are not misdiagnosed or neurological changes overlooked.ResultsIn the first case the RDOC-RA promoted a more accurate diagnosis than that based on standardized scales alone. The second case shows how the RDOC-PIM allowed us to recognize late recovery and promoted reinstatement of treatment with good results.ConclusionAdding a detailed periodic assessment of DOC patients to existing scales can yield critical information, promoting better diagnosis, treatment, and clinical outcomes. We discuss the implications of this observation for the future development and validation of assessment tools in DOC patients.

Project description:Background/objectiveBehavioral examinations may fail to detect language function in patients with severe traumatic brain injury (TBI) due to confounds such as having an endotracheal tube. We investigated whether resting and stimulus-evoked electroencephalography (EEG) methods detect the presence of language function in patients with severe TBI.MethodsFour EEG measures were assessed: (1) resting background (applying Forgacs' criteria), (2) reactivity to speech, (3) background and reactivity (applying Synek's criteria); and (4) an automated support vector machine (classifier for speech versus rest). Cohen's kappa measured agreement between the four EEG measures and evidence of language function on a behavioral coma recovery scale-revised (CRS-R) and composite (CRS-R or functional MRI) reference standard. Sensitivity and specificity of each EEG measure were calculated against the reference standards.ResultsWe enrolled 17 adult patients with severe TBI (mean ± SD age 27.0 ± 7.0 years; median [range] 11.5 [2-1173] days post-injury) and 16 healthy subjects (age 28.5 ± 7.8 years). The classifier, followed by Forgacs' criteria for resting background, demonstrated the highest agreement with the behavioral reference standard. Only Synek's criteria for background and reactivity showed significant agreement with the composite reference standard. The classifier and resting background showed balanced sensitivity and specificity for behavioral (sensitivity = 84.6% and 80.8%; specificity = 57.1% for both) and composite reference standards (sensitivity = 79.3% and 75.9%, specificity = 50% for both).ConclusionsMethods applying an automated classifier, resting background, or resting background with reactivity may identify severe TBI patients with preserved language function. Automated classifier methods may enable unbiased and efficient assessment of larger populations or serial timepoints, while qualitative visual methods may be practical in community settings.

Dataset Information

Multimodal FDG-PET and EEG assessment improves diagnosis and prognostication of disorders of consciousness.

Introduction

Methods

Results

Conclusion

Publications

Multimodal FDG-PET and EEG assessment improves diagnosis and prognostication of disorders of consciousness.

Similar Datasets

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