Liu Dongsheng, Wang Nan, Song Ming, Chai Xiaoke, He Qiheng, Cao Tianqing, Kong Dawei, Song Zhuhuan, Zhang Guangming, Liu Lei, Wang Xiaosong, Chen Guoqiang, Yin Shaoya, Yang Yi, Zhao Jizong
Clinical College of Neurology, Neurosurgery and Neurorehabilitation, Tianjin Medical University, Tianjin, China.
Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin, China.
Front Neurol. 2025 Jan 3;15:1425271. doi: 10.3389/fneur.2024.1425271. eCollection 2024.
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.
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.
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 ((2, 53) = 7.26, < 0.001). Multiple comparisons found that the mean of cortical metabolic index was significantly different between MCS ( = 4.19, = 0.64) and UWS group ( = 2.74, = 0.94 < 0.001). Also, the mean of cortical metabolic index was significantly different between MCS and healthy group ( = 7.88, = 0.80, < 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).
Our findings demonstrate that conscious awareness requires a minimum of 41% of normal cortical activity, as indicated by metabolic rates.
本研究旨在采用18F-氟脱氧葡萄糖（FDG-PET）评估46例被诊断为意识障碍（DoC）患者的静息态脑葡萄糖代谢。目的是确定能够潜在指示这些患者意识水平的客观定量代谢指标和预测指标。
46例患者队列接受了昏迷恢复量表修订版（CRS-R）评估，以区分最低意识状态（MCS）和无反应觉醒综合征（UWS）。此外，从患者组和由10名健康个体组成的对照组获取静息态FDG-PET数据。FDG-PET数据进行了重新定向、立体定向空间的空间归一化和平滑处理。归一化程序按照Phillips等人概述的方法使用定制模板。利用总体样本的平均皮质代谢来区分UWS和MCS，以及通过应用受试者操作特征（ROC）分析预测1年随访结果。
我们使用全脑葡萄糖代谢作为诊断标志物。单因素方差分析显示两组之间皮质代谢指数存在统计学显著差异（(2, 53) = 7.26, < 0.001）。多重比较发现MCS组（ = 4.19, = 0.64）和UWS组（ = 2.74, = 0.94 < 0.001）之间皮质代谢指数均值存在显著差异。此外，MCS组与健康组之间皮质代谢指数均值也存在显著差异（ = 7.88, = 0.80, < 0.001）。使用上述诊断标准，在合并队列中诊断准确性的曲线下面积（AUC）为0.89（95%CI 0.79 - 0.99）。MCS和UWS之间的正确分类率为85%，MCS的敏感性为88%，特异性为81%。在推导队列中，代谢指数为3.32时达到最佳分类率（健康对照中平均皮质代谢指数的41%）。
我们的研究结果表明，如代谢率所示，意识清醒需要至少41%的正常皮质活动。
