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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

Voxel‐based between‐group analysis for (A) FDG‐PET describing regions (in orange) with higher metabolic activity in healthy controls (CTR) with respect to vegetative state/unresponsive wakefulness syndrome patients (VS/UWS), and regions preserved in vegetative state/unresponsive wakefulness syndrome patients (P < 0.05 FDR corrected). (B) fMRI total neuronal activity as for A. (C) conjunction of FDG‐PET and fMRI total neuronal as for a. In green regions with a higher decrease in FDG‐PET with respect to fMRI total neuronal and in red with a higher decrease in fMRI total neuronal with respect to FDG‐PET (for the contrast healthy controls more than vegetative state/unresponsive wakefulness syndrome patients). FDG‐PET was partial volume corrected.
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brb3424-fig-0004: Voxel‐based between‐group analysis for (A) FDG‐PET describing regions (in orange) with higher metabolic activity in healthy controls (CTR) with respect to vegetative state/unresponsive wakefulness syndrome patients (VS/UWS), and regions preserved in vegetative state/unresponsive wakefulness syndrome patients (P < 0.05 FDR corrected). (B) fMRI total neuronal activity as for A. (C) conjunction of FDG‐PET and fMRI total neuronal as for a. In green regions with a higher decrease in FDG‐PET with respect to fMRI total neuronal and in red with a higher decrease in fMRI total neuronal with respect to FDG‐PET (for the contrast healthy controls more than vegetative state/unresponsive wakefulness syndrome patients). FDG‐PET was partial volume corrected.

Mentions: When contrasting FDG‐PET metabolic activity proportionally scaled by the global signal in healthy controls versus VS/UWS patients (Fig. 4A), we found that the fronto‐parietal and medial networks (precuneus, medial‐frontal, bilateral posterior parietal, superior temporal, and dorsolateral prefrontal cortices) together with bilateral caudate and thalami appeared as the regions with a significant hypometabolism in VS/UWS patients with respect to healthy controls (P < 0.05 FDR corrected; see Table 3). The opposite contrast giving us the regions with preserved FDG‐PET metabolic activity in VS/UWS patients identified the brainstem. When contrasting the fMRI total neuronal activity proportionally scaled by the global signal in healthy controls versus VS/UWS patients (Fig. 4B and Table 3), we also found that regions of the lateral and medial fronto‐parietal networks showed a significant decrease in VS/UWS patients with respect to healthy controls. Intra‐parietal, temporal, and medial orbito‐frontal cortices were the regions showing the most significant decrease. The caudate and thalamus did not show a significant decrease. The hypothalamus appeared as a region with preserved fMRI total neuronal activity in VS/UWS patients. The conjunction analysis of the FDG‐PET metabolic and fMRI total neuronal activities (Fig. 4C and Table 3), when contrasting healthy controls versus VS/UWS patients, confirmed a significant decrease in the fronto‐parietal and medial networks regions (precuneus, medial prefrontal cortex, temporo‐parietal junction, inferior frontal, and medial frontal gyrus). Finally when contrasting the decrease in VS/UWS patients in FDG‐PET with respect to fMRI total neuronal activity (Fig. 4D and Table 3), a significant higher decrease in FDG‐PET with respect to fMRI total neuronal activity was observed in the precuneus, cuneus, insula, caudate, and thalamus. A significant higher decrease was observed in fMRI total neuronal with respect to FDG‐PET metabolic activity in the medial prefrontal cortex and amigdala. The brainstem also appeared in this last contrast being more preserved for VS/UWS patients in FDG‐PET than in fMRI total neuronal. Resting state data of four LIS patients were analyzed even if not included in the group analysis. Figure 5 shows the conjunction analysis of both fMRI and PET for healthy controls, VS/UWS, and LIS patients. Activity of VS/UWS patients was consistently smaller compared to both controls and LIS patients, while LIS patients were comparable to healthy controls. For fMRI, we also calculated two motion parameters (Soddu et al. 2012) measuring average displacement and average speed during the full acquisition time window. We obtained, respectively, a displacement of 0.43 ± 0.25 and a speed of 0.12 ± 0.05 for healthy controls. For VS/UWS patients we found a displacement of 0.60 ± 0.37 (P = 0.16 as compared to controls) and a speed of 0.26 ± 0.17 (P = 0.006 as compared to controls), while for LIS patients we found a displacement of 0.93 ± 0.46 (P = 0.007 as compared to controls, and P = 0.17 as compared to VS/UWS) and a speed of 0.10 ± 0.04 (P = 0.42 as compared to controls and P = 0.09 as compared to VS/UWS). Finally, we plotted the mean value of the fMRI total neuronal versus the total number of neuronal components, Figure 6 considering all the subjects (healthy controls, VS/UVS and LIS patients). The correlation was highly significant with a value ρ = 0.97 and a P < 0.001. In Figure S3 we also plotted the correlation between FDG‐PET and fMRI total neuronal versus the total number of neuronal components in each subject. The correlation was not significant with a value ρ = 0.32 and a P = 0.089.


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)

Voxel‐based between‐group analysis for (A) FDG‐PET describing regions (in orange) with higher metabolic activity in healthy controls (CTR) with respect to vegetative state/unresponsive wakefulness syndrome patients (VS/UWS), and regions preserved in vegetative state/unresponsive wakefulness syndrome patients (P < 0.05 FDR corrected). (B) fMRI total neuronal activity as for A. (C) conjunction of FDG‐PET and fMRI total neuronal as for a. In green regions with a higher decrease in FDG‐PET with respect to fMRI total neuronal and in red with a higher decrease in fMRI total neuronal with respect to FDG‐PET (for the contrast healthy controls more than vegetative state/unresponsive wakefulness syndrome patients). FDG‐PET was partial volume corrected.
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brb3424-fig-0004: Voxel‐based between‐group analysis for (A) FDG‐PET describing regions (in orange) with higher metabolic activity in healthy controls (CTR) with respect to vegetative state/unresponsive wakefulness syndrome patients (VS/UWS), and regions preserved in vegetative state/unresponsive wakefulness syndrome patients (P < 0.05 FDR corrected). (B) fMRI total neuronal activity as for A. (C) conjunction of FDG‐PET and fMRI total neuronal as for a. In green regions with a higher decrease in FDG‐PET with respect to fMRI total neuronal and in red with a higher decrease in fMRI total neuronal with respect to FDG‐PET (for the contrast healthy controls more than vegetative state/unresponsive wakefulness syndrome patients). FDG‐PET was partial volume corrected.
Mentions: When contrasting FDG‐PET metabolic activity proportionally scaled by the global signal in healthy controls versus VS/UWS patients (Fig. 4A), we found that the fronto‐parietal and medial networks (precuneus, medial‐frontal, bilateral posterior parietal, superior temporal, and dorsolateral prefrontal cortices) together with bilateral caudate and thalami appeared as the regions with a significant hypometabolism in VS/UWS patients with respect to healthy controls (P < 0.05 FDR corrected; see Table 3). The opposite contrast giving us the regions with preserved FDG‐PET metabolic activity in VS/UWS patients identified the brainstem. When contrasting the fMRI total neuronal activity proportionally scaled by the global signal in healthy controls versus VS/UWS patients (Fig. 4B and Table 3), we also found that regions of the lateral and medial fronto‐parietal networks showed a significant decrease in VS/UWS patients with respect to healthy controls. Intra‐parietal, temporal, and medial orbito‐frontal cortices were the regions showing the most significant decrease. The caudate and thalamus did not show a significant decrease. The hypothalamus appeared as a region with preserved fMRI total neuronal activity in VS/UWS patients. The conjunction analysis of the FDG‐PET metabolic and fMRI total neuronal activities (Fig. 4C and Table 3), when contrasting healthy controls versus VS/UWS patients, confirmed a significant decrease in the fronto‐parietal and medial networks regions (precuneus, medial prefrontal cortex, temporo‐parietal junction, inferior frontal, and medial frontal gyrus). Finally when contrasting the decrease in VS/UWS patients in FDG‐PET with respect to fMRI total neuronal activity (Fig. 4D and Table 3), a significant higher decrease in FDG‐PET with respect to fMRI total neuronal activity was observed in the precuneus, cuneus, insula, caudate, and thalamus. A significant higher decrease was observed in fMRI total neuronal with respect to FDG‐PET metabolic activity in the medial prefrontal cortex and amigdala. The brainstem also appeared in this last contrast being more preserved for VS/UWS patients in FDG‐PET than in fMRI total neuronal. Resting state data of four LIS patients were analyzed even if not included in the group analysis. Figure 5 shows the conjunction analysis of both fMRI and PET for healthy controls, VS/UWS, and LIS patients. Activity of VS/UWS patients was consistently smaller compared to both controls and LIS patients, while LIS patients were comparable to healthy controls. For fMRI, we also calculated two motion parameters (Soddu et al. 2012) measuring average displacement and average speed during the full acquisition time window. We obtained, respectively, a displacement of 0.43 ± 0.25 and a speed of 0.12 ± 0.05 for healthy controls. For VS/UWS patients we found a displacement of 0.60 ± 0.37 (P = 0.16 as compared to controls) and a speed of 0.26 ± 0.17 (P = 0.006 as compared to controls), while for LIS patients we found a displacement of 0.93 ± 0.46 (P = 0.007 as compared to controls, and P = 0.17 as compared to VS/UWS) and a speed of 0.10 ± 0.04 (P = 0.42 as compared to controls and P = 0.09 as compared to VS/UWS). Finally, we plotted the mean value of the fMRI total neuronal versus the total number of neuronal components, Figure 6 considering all the subjects (healthy controls, VS/UVS and LIS patients). The correlation was highly significant with a value ρ = 0.97 and a P < 0.001. In Figure S3 we also plotted the correlation between FDG‐PET and fMRI total neuronal versus the total number of neuronal components in each subject. The correlation was not significant with a value ρ = 0.32 and a P = 0.089.

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