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ORIGINAL RESEARCH article
Front. Neurol.
Sec. Neurological Biomarkers
Volume 15 - 2024 |
doi: 10.3389/fneur.2024.1425271
Global Glucose Metabolism Rate as Diagnostic Marker for Disorder of Consciousness of Patients: Quantitative FDG-PET Study
Provisionally accepted- 1 Department of Neurosurgery, Aviation General Hospital, Beijing, China, Beijing, China
- 2 Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- 3 National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, Beijing Municipality, China
Objective: This 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. Methods: A 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. Results: We 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). Conclusion: Our findings demonstrate that conscious awareness requires a minimum of 41% of normal cortical activity, as indicated by metabolic rates.
Keywords: FDG-PET, disorders of consciousness, global glucose metabolism rate, Diagnostic marker, CRS-R
Received: 01 May 2024; Accepted: 26 Nov 2024.
Copyright: © 2024 Liu, Wang, Song, Chai, He, Cao, Kong, Song, Zhang, Liu, Wang, Chen, YANG and Zhao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Tianqing Cao, Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
Dawei Kong, Department of Neurosurgery, Aviation General Hospital, Beijing, China, Beijing, China
Guangming Zhang, Department of Neurosurgery, Aviation General Hospital, Beijing, China, Beijing, China
Lei Liu, Department of Neurosurgery, Aviation General Hospital, Beijing, China, Beijing, China
Xiaosong Wang, Department of Neurosurgery, Aviation General Hospital, Beijing, China, Beijing, China
Guoqiang Chen, Department of Neurosurgery, Aviation General Hospital, Beijing, China, Beijing, China
YI YANG, Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
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