Chiarelli Antonio M, Perpetuini David, Croce Pierpaolo, Filippini Chiara, Cardone Daniela, Rotunno Ludovica, Anzoletti Nelson, Zito Michele, Zappasodi Filippo, Merla Arcangelo
Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, Faculty of Medicine, University G. D'Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy.
Department of Medicine and Science of Ageing, Faculty of Medicine, University G. d'Annunzio of Chieti-Pescara, Via Dei Vestini 31, 66100 Chieti, Italy.
Biomedicines. 2021 Mar 26;9(4):337. doi: 10.3390/biomedicines9040337.
Alzheimer's disease (AD) is associated with modifications in cerebral blood perfusion and autoregulation. Hence, neurovascular coupling (NC) alteration could become a biomarker of the disease. NC might be assessed in clinical settings through multimodal electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Multimodal EEG-fNIRS was recorded at rest in an ambulatory setting to assess NC and to evaluate the sensitivity and specificity of the methodology to AD. Global NC was evaluated with a general linear model (GLM) framework by regressing whole-head EEG power envelopes in three frequency bands (theta, alpha and beta) with average fNIRS oxy- and deoxy-hemoglobin concentration changes in the frontal and prefrontal cortices. NC was lower in AD compared to healthy controls (HC) with significant differences in the linkage of theta and alpha bands with oxy- and deoxy-hemoglobin, respectively ( = 0.028 and = 0.020). Importantly, standalone EEG and fNIRS metrics did not highlight differences between AD and HC. Furthermore, a multivariate data-driven analysis of NC between the three frequency bands and the two hemoglobin species delivered a cross-validated classification performance of AD and HC with an Area Under the Curve, AUC = 0.905 ( = 2.17 × 10). The findings demonstrate that EEG-fNIRS may indeed represent a powerful ecological tool for clinical evaluation of NC and early identification of AD.
阿尔茨海默病（AD）与脑血流灌注和自动调节的改变有关。因此，神经血管耦合（NC）改变可能成为该疾病的生物标志物。NC可在临床环境中通过多模态脑电图（EEG）和功能近红外光谱（fNIRS）进行评估。在动态环境中静息状态下记录多模态EEG-fNIRS，以评估NC并评估该方法对AD的敏感性和特异性。通过一般线性模型（GLM）框架，将三个频段（θ、α和β）的全脑EEG功率包络与额叶和前额叶皮质中平均fNIRS氧合血红蛋白和脱氧血红蛋白浓度变化进行回归，评估整体NC。与健康对照（HC）相比，AD患者的NC较低，θ和α频段分别与氧合血红蛋白和脱氧血红蛋白的联系存在显著差异（P = 0.028和P = 0.020）。重要的是，单独的EEG和fNIRS指标未突出显示AD和HC之间的差异。此外，对三个频段和两种血红蛋白之间的NC进行多变量数据驱动分析，得出AD和HC的交叉验证分类性能，曲线下面积AUC = 0.905（P = 2.17×10）。研究结果表明，EEG-fNIRS确实可能是用于临床评估NC和早期识别AD的强大生态学工具。
