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Correlation between resting state fMRI total neuronal activity and PET metabolism in healthy controls and patients with disorders of consciousness.

Soddu A, Gómez F, Heine L, Di Perri C, Bahri MA, Voss HU, Bruno MA, Vanhaudenhuyse A, Phillips C, Demertzi A, Chatelle C, Schrouff J, Thibaut A, Charland-Verville V, Noirhomme Q, Salmon E, Tshibanda JF, Schiff ND, Laureys S - Brain Behav (2015)

Bottom Line: The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure 'resting state' cerebral metabolism.It also overcomes the problem of recognizing individual networks of independent component selection in functional magnetic resonance imaging (fMRI) resting state analysis.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics & Astronomy, Brain and Mind Institute Western University London Ontario Canada.

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.

No MeSH data available.


Related in: MedlinePlus

Pictorial description of the methodology used to construct the fMRI total neuronal scalar map starting from automatically selected neuronal independent components. Neuronal independent components were selected based on their fingerprint, which describes for each component, spatial properties of the distribution of the Z scores as extracted from the spatial map and temporal properties as extracted from the corresponding time course. The green line on the fingerprint represent the mean values obtained from an independent group of normal volunteers, the red line represents the values observed in the assessed subject.
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brb3424-fig-0001: Pictorial description of the methodology used to construct the fMRI total neuronal scalar map starting from automatically selected neuronal independent components. Neuronal independent components were selected based on their fingerprint, which describes for each component, spatial properties of the distribution of the Z scores as extracted from the spatial map and temporal properties as extracted from the corresponding time course. The green line on the fingerprint represent the mean values obtained from an independent group of normal volunteers, the red line represents the values observed in the assessed subject.

Mentions: The area under the Receiver Operating Curve (ROC) was used as performance measurement for the parameter selection (Bradley 1997). The classifier with highest overall classification rate was selected and subsequently used to label neuronal components on the fMRI dataset of the current study. Once the neuronal components were selected, we built a single scalar map for each of the subjects (11 VS/UWS, 4 LIS, and 16 controls) summing voxel by voxel the square root of the absolute value of the z maps over the neuronal components (Eq. (1), and described in Fig. 1):


Correlation between resting state fMRI total neuronal activity and PET metabolism in healthy controls and patients with disorders of consciousness.

Soddu A, Gómez F, Heine L, Di Perri C, Bahri MA, Voss HU, Bruno MA, Vanhaudenhuyse A, Phillips C, Demertzi A, Chatelle C, Schrouff J, Thibaut A, Charland-Verville V, Noirhomme Q, Salmon E, Tshibanda JF, Schiff ND, Laureys S - Brain Behav (2015)

Pictorial description of the methodology used to construct the fMRI total neuronal scalar map starting from automatically selected neuronal independent components. Neuronal independent components were selected based on their fingerprint, which describes for each component, spatial properties of the distribution of the Z scores as extracted from the spatial map and temporal properties as extracted from the corresponding time course. The green line on the fingerprint represent the mean values obtained from an independent group of normal volunteers, the red line represents the values observed in the assessed subject.
© Copyright Policy - creativeCommonsBy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4834945&req=5

brb3424-fig-0001: Pictorial description of the methodology used to construct the fMRI total neuronal scalar map starting from automatically selected neuronal independent components. Neuronal independent components were selected based on their fingerprint, which describes for each component, spatial properties of the distribution of the Z scores as extracted from the spatial map and temporal properties as extracted from the corresponding time course. The green line on the fingerprint represent the mean values obtained from an independent group of normal volunteers, the red line represents the values observed in the assessed subject.
Mentions: The area under the Receiver Operating Curve (ROC) was used as performance measurement for the parameter selection (Bradley 1997). The classifier with highest overall classification rate was selected and subsequently used to label neuronal components on the fMRI dataset of the current study. Once the neuronal components were selected, we built a single scalar map for each of the subjects (11 VS/UWS, 4 LIS, and 16 controls) summing voxel by voxel the square root of the absolute value of the z maps over the neuronal components (Eq. (1), and described in Fig. 1):

Bottom Line: The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure 'resting state' cerebral metabolism.It also overcomes the problem of recognizing individual networks of independent component selection in functional magnetic resonance imaging (fMRI) resting state analysis.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics & Astronomy, Brain and Mind Institute Western University London Ontario Canada.

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.

No MeSH data available.


Related in: MedlinePlus