Global glucose metabolism rate as diagnostic marker for disorder of consciousness of patients: quantitative FDG-PET study
ObjectiveThis study was to employ 18F-flurodeoxyglucose (FDG-PET) to evaluate the resting-state brain glucose metabolism in a sample of 46 patients diagnosed with disorders of consciousness (DoC). The aim was to identify objective quantitative metabolic indicators and predictors that could potential...
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| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Neurology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fneur.2024.1425271/full |
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| Summary: | ObjectiveThis study was to employ 18F-flurodeoxyglucose (FDG-PET) to evaluate the resting-state brain glucose metabolism in a sample of 46 patients diagnosed with disorders of consciousness (DoC). The aim was to identify objective quantitative metabolic indicators and predictors that could potentially indicate the level of awareness in these patients.MethodsA cohort of 46 patients underwent Coma Recovery Scale-Revised (CRS-R) assessments in order to distinguish between the minimally conscious state (MCS) and the unresponsive wakefulness syndrome (UWS). Additionally, resting-state FDG-PET data were acquired from both the patient group and a control group consisting of 10 healthy individuals. The FDG-PET data underwent reorientation, spatial normalization to a stereotaxic space, and smoothing. The normalization procedure utilized a customized template following the methodology outlined by Phillips et al. Mean cortical metabolism of the overall sample was utilized for distinguishing between UWS and MCS, as well as for predicting the outcome at a 1-year follow-up through the application of receiver operating characteristic (ROC) analysis.ResultsWe used Global Glucose Metabolism as the Diagnostic Marker. A one-way ANOVA revealed that there was a statistically significant difference in cortical metabolic index between two groups (F(2, 53) = 7.26, p < 0.001). Multiple comparisons found that the mean of cortical metabolic index was significantly different between MCS (M = 4.19, SD = 0.64) and UWS group (M = 2.74, SD = 0.94,p < 0.001). Also, the mean of cortical metabolic index was significantly different between MCS and healthy group (M = 7.88, SD = 0.80,p < 0.001). Using the above diagnostic criterion, the diagnostic accuracy yielded an area under the curve (AUC) of 0.89 across the pooled cohort (95%CI 0.79–0.99). There was an 85% correct classification between MCS and UWS, with 88% sensitivity and 81% specificity for MCS. The best classification rate in the derivation cohort was achieved at a metabolic index of 3.32 (41% of the mean cortical metabolic index in healthy controls).ConclusionOur findings demonstrate that conscious awareness requires a minimum of 41% of normal cortical activity, as indicated by metabolic rates. |
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| ISSN: | 1664-2295 |