Correlation between resting state fMRI total neuronal activity and PET metabolism in healthy controls and patients with disorders of consciousness. Issue 1 (29th December 2015)

• Record Type: Journal Article
• Authors: Soddu, Andrea; Gómez, Francisco; Heine, Lizette; Di Perri, Carol; Bahri, Mohamed Ali; Voss, Henning U.; Bruno, Marie‐Aurélie; Vanhaudenhuyse, Audrey; Phillips, Christophe; Demertzi, Athena; Chatelle, Camille; Schrouff, Jessica; Thibaut, Aurore; Charland‐Verville, Vanessa; Noirhomme, Quentin; Salmon, Eric; Tshibanda, Jean‐Flory Luaba; Schiff, Nicholas D.; Laureys, Steven
• Is Part Of: Brain and behavior. Volume 6:Issue 1(2016)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2015-12-29
• Subjects: Disorders of consciousness -- FDG‐PET -- fMRI -- ICA -- metabolism -- resting state; Neurology -- Periodicals; Neurosciences -- Periodicals; Psychology -- Periodicals; Psychiatry -- Periodicals; 616.8005
• DOI: 10.1002/brb3.424
• Languages: English
• ISSNs: 2162-3279

Abstract

Abstract: Introduction: The mildly invasive 18F‐fluorodeoxyglucose positron emission tomography (FDG‐PET) is a well‐established imaging technique to measure 'resting state' cerebral metabolism. This technique made it possible to assess changes in metabolic activity in clinical applications, such as the study of severe brain injury and disorders of consciousness. Objective: We assessed the possibility of creating functional MRI activity maps, which could estimate the relative levels of activity in FDG‐PET cerebral metabolic maps. If no metabolic absolute measures can be extracted, our approach may still be of clinical use in centers without access to FDG‐PET. It also overcomes the problem of recognizing individual networks of independent component selection in functional magnetic resonance imaging (fMRI) resting state analysis. Methods: We extracted resting state fMRI functional connectivity maps using independent component analysis and combined only components of neuronal origin. To assess neuronality of components a classification based on support vector machine (SVM) was used. We compared the generated maps with the FDG‐PET maps in 16 healthy controls, 11 vegetative state/unresponsive wakefulness syndrome patients and four locked‐in patients. Results: The results show a significant similarity with ρ = 0.75 ± 0.05 for healthy controls and ρ = 0.58 ± 0.09 for vegetative state/unresponsive wakefulness syndrome patients between the FDG‐PET and the fMRI based maps. FDG‐PET, fMRI neuronal maps, and the conjunction analysis show decreases in frontoparietal and medial regions in vegetative patients with respect to controls. Subsequent analysis in locked‐in syndrome patients produced also consistent maps with healthy controls. Conclusions: The constructed resting state fMRI functional connectivity map points toward the possibility for fMRI resting state to estimate relative levels of activity in a metabolic map. Abstract : We assessed the possibility of creating functional MRI activity maps comparable to FDG‐PET cerebral metabolism maps. This may be of clinical use in centers without access to FDG‐PET. It also overcomes the problem of recognizing individual networks of independent component selection in fMRI resting state analysis.