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

• Published in: NeuroImage clinical Vol. 30; p. 102601
• Main Authors: Hermann, Bertrand, Stender, Johan, Habert, Marie-Odile, Kas, Aurélie, Denis-Valente, Mélanie, Raimondo, Federico, Pérez, Pauline, Rohaut, Benjamin, Sitt, Jacobo Diego, Naccache, Lionel
• Format: Journal Article Web Resource
• Language: English
• Published: Netherlands Elsevier Inc 01.01.2021; Elsevier
• Subjects: Cognitive Neuroscience; Cognitive-motor dissociation; Consciousness; Consciousness Disorders; Consciousness Disorders/diagnostic imaging; Diagnosis; Disorders of consciousness; Electroencephalography; Fluorodeoxyglucose F18; Human health sciences; Humans; Life Sciences; Neurologie; Neurology; Neurology (clinical); Neurosciences & behavior; Neurosciences & comportement; Persistent Vegetative State; Persistent Vegetative State/diagnostic imaging; Positron emission tomography; Radiology; Radiology, Nuclear Medicine and Imaging; Regular; Sciences de la santé humaine; Sciences sociales & comportementales, psychologie; Social & behavioral sciences, psychology; Electroencephalography; Cognitive-motor dissociation; Diagnosis; Positron emission tomography; Disorders of consciousness
• ISSN: 2213-1582; 2213-1582
• DOI: 10.1016/j.nicl.2021.102601

•FDG-PET metabolic index of the best hemisphere is robust to diagnose MCS.•FDG-PET slightly outperforms EEG-based automatic classification of conscious state.•Optimal diagnostic performances are obtained by combining PET and EEG.•PET and EEG combination identifies cortical activation suggestive of residual consciousness.•PET and EEG combination also predict patients 6-month command-following. 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. 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). 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. 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.