Li Haoyu, Yang Xi, Gong Liang
Department of Neurology, Chengdu Medical College, Chengdu Second People's Hospital, Chengdu, China.
Department of Applied Psychology, Chengdu Medical College, Chengdu, China.
Front Neurol. 2025 Aug 29;16:1578375. doi: 10.3389/fneur.2025.1578375. eCollection 2025.
Functional Near-Infrared Spectroscopy (fNIRS) has been used to detect changes in haemodynamic response in patients with neurodegenerative diseases such as Alzheimer's disease (AD) and mild cognitive impairment (MCI). We aimed to evaluate the efficacy of fNIRS in identifying early dementia-related changes and distinguishing between MCI and AD.
A comprehensive literature search was conducted using PubMed and Web of Science, focusing on studies that employed fNIRS to measure cerebral hemodynamics in MCI and AD patients. The search included articles published up to February 2024. Studies were selected based on predefined criteria, including the use of fNIRS, inclusion of MCI or AD patients, and publication in English. Data extraction focused on study design, fNIRS device specifications, experimental paradigms, and diagnostic criteria.
A total of 58 studies were included in the review. Of these, 4 studies employed both resting-state and task-based paradigms, 11 studies focused on resting-state paradigms, and 43 studies utilized task-based paradigms. Resting-state studies revealed reduced brain activation in the frontal, temporal, and parietal lobes in AD and MCI patients, along with significant reductions in tissue oxygenation index (TOI) and functional connectivity (FC). Task-based studies demonstrated diminished activation across multiple brain regions during cognitive tasks, with reduced FC intensity and signal complexity in AD and MCI patients. Machine learning models applied to fNIRS data showed high accuracy in classifying MCI and AD, with some models achieving accuracy rates of up to 90%.
fNIRS is a promising tool for the diagnosis and monitoring of MCI and AD, and further research is needed to establish its full potential.
功能近红外光谱技术（fNIRS）已被用于检测神经退行性疾病（如阿尔茨海默病（AD）和轻度认知障碍（MCI））患者的血流动力学反应变化。我们旨在评估fNIRS在识别早期痴呆相关变化以及区分MCI和AD方面的功效。
使用PubMed和Web of Science进行了全面的文献检索，重点关注采用fNIRS测量MCI和AD患者脑血流动力学的研究。检索包括截至2024年2月发表的文章。根据预定义标准选择研究，包括使用fNIRS、纳入MCI或AD患者以及以英文发表。数据提取集中在研究设计、fNIRS设备规格、实验范式和诊断标准。
本综述共纳入58项研究。其中，4项研究采用了静息态和任务态范式，11项研究侧重于静息态范式，43项研究采用了任务态范式。静息态研究显示，AD和MCI患者的额叶、颞叶和顶叶脑激活减少，同时组织氧合指数（TOI）和功能连接性（FC）显著降低。基于任务的研究表明，在认知任务期间多个脑区的激活减弱，AD和MCI患者的FC强度和信号复杂性降低。应用于fNIRS数据的机器学习模型在分类MCI和AD方面显示出高准确性，一些模型的准确率高达90%。
fNIRS是诊断和监测MCI和AD的一种有前景的工具，需要进一步研究以充分发挥其潜力。
