Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
CNS Neurosci Ther. 2024 Nov;30(11):e70108. doi: 10.1111/cns.70108.
There is limited research on predicting the recovery of consciousness in patients with acute disorders of consciousness (aDOC). The purpose of this study is to investigate the altered characteristics of the local neuronal activity indicated by the amplitude of low-frequency fluctuations (ALFF) and functional connectivity (FC) of the hippocampus network in patients with aDOC caused by neurological injury and to explore whether these characteristics can predict the recovery of consciousness.
Thirty-seven patients with aDOC were included, all of whom completed resting-state functional magnetic resonance imaging (rsfMRI) scans. The patients were divided into two groups based on prognosis of consciousness recovery, 24 patients were in prolonged disorders of consciousness (pDOC) and 13 in emergence from minimally conscious state (eMCS) at 3 months after neurological injury. Univariable and multivariate logistic regression analyses were used to investigate the clinical indicators affecting patients' recovery of consciousness. The ALFF values and FC of the hippocampal network were compared between patients with pDOC and those with eMCS. Additionally, we employed the support vector machine (SVM) method to construct a predictive model for prognosis of consciousness based on the ALFF and FC values of the aforementioned differential brain regions. The accuracy (ACC), area under the curve (AUC), sensitivity, and specificity were used to evaluate the efficacy of the model.
The FOUR score at onset and the length of mechanical ventilation (MV) were found to be significant influential factors for patients who recovered to eMCS at 3 months after onset. Patients who improved to eMCS showed significantly increased ALFF values in the right calcarine gyrus, left lingual gyrus, right middle temporal gyrus, and right precuneus compared to patients in a state of pDOC. Furthermore, significant increases in FC values of the hippocampal network were observed in the eMCS group, primarily involving the right lingual gyrus and bilateral precuneus, compared to the pDOC group. The predictive model constructed using ALFF alone or ALFF combined with FC values from the aforementioned brain regions demonstrated high accuracies of 83.78% and 81.08%, respectively, with AUCs of 95% and 94%, sensitivities of 0.92 for both models, and specificities of 0.92 for both models in predicting the recovery of consciousness in patients with aDOC.
The present findings demonstrate significant differences in the local ALFF and FC values of the hippocampus network between different prognostic groups of patients with aDOC. The constructed predictive model, which incorporates ALFF and FC values, has the potential to provide valuable insights for clinical decision-making and identifying potential targets for early intervention.
目前关于预测急性意识障碍（aDOC）患者意识恢复的研究有限。本研究旨在探讨神经损伤引起的 aDOC 患者海马网络局部神经元活动振幅低频波动（ALFF）和功能连接（FC）改变的特征，并探讨这些特征是否可预测意识恢复。
纳入 37 例 aDOC 患者，均完成静息态功能磁共振成像（rsfMRI）扫描。根据意识恢复预后将患者分为两组，24 例为迁延性意识障碍（pDOC），13 例为最小意识状态（eMCS）在神经损伤后 3 个月。采用单变量和多变量逻辑回归分析探讨影响患者意识恢复的临床指标。比较 pDOC 患者和 eMCS 患者的 ALFF 值和海马网络 FC。此外，我们采用支持向量机（SVM）方法，根据上述差异脑区的 ALFF 和 FC 值构建意识预后预测模型。采用准确率（ACC）、曲线下面积（AUC）、灵敏度和特异度评价模型效能。
发现发病时 FOUR 评分和机械通气（MV）时间是患者发病后 3 个月恢复至 eMCS 的显著影响因素。与 pDOC 患者相比，恢复至 eMCS 的患者右侧距状回、左侧舌回、右侧颞中回和右侧楔前叶的 ALFF 值明显升高。此外，与 pDOC 组相比，eMCS 组海马网络 FC 值明显升高，主要涉及右侧舌回和双侧楔前叶。仅使用 ALFF 或 ALFF 联合上述脑区 FC 值构建的预测模型准确率分别为 83.78%和 81.08%，AUC 分别为 95%和 94%，灵敏度均为 0.92，特异度均为 0.92，可用于预测 aDOC 患者的意识恢复。
本研究结果表明，不同预后 aDOC 患者海马网络局部 ALFF 和 FC 值存在显著差异。所构建的预测模型，整合了 ALFF 和 FC 值，有可能为临床决策和识别早期干预的潜在靶点提供有价值的信息。
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