Research on the application of functional near-infrared spectroscopy in differentiating subjective cognitive decline and mild cognitive impairment

Zheng Wang; Chaojie Niu; Yong Duan; Hao Yang; Jinpeng Mi; Chao Liu; Guodong Chen; Qihao Guo

doi:10.3389/fnagi.2024.1469620

Research on the application of functional near-infrared spectroscopy in differentiating subjective cognitive decline and mild cognitive impairment

Front Aging Neurosci. 2024 Dec 24:16:1469620. doi: 10.3389/fnagi.2024.1469620. eCollection 2024.

Authors

Zheng Wang^#¹, Chaojie Niu^#², Yong Duan^#², Hao Yang³, Jinpeng Mi⁴, Chao Liu², Guodong Chen², Qihao Guo¹

Affiliations

¹ Department of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
² Jiangsu Provincial Key Laboratory of Advanced Robotics, and Robotics and Microsystems Center, School of Mechanical and Electrical Engineering, Soochow University, Suzhou, China.
³ School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai, China.
⁴ Institute of Machine Intelligence (IMI), University of Shanghai for Science and Technology, Shanghai, China.

^# Contributed equally.

Abstract

Introduction: Alzheimer's disease (AD) is a common neurological disorder. Based on clinical characteristics, it can be categorized into normal cognition (NC), subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia (AD). Once the condition begins to progress, the process is usually irreversible. Therefore, early identification and intervention are crucial for patients. This study aims to explore the sensitivity of fNIRS in distinguishing between SCD and MCI.

Methods: An in-depth analysis of the Functional Connectivity (FC) and oxygenated hemoglobin (HbO) characteristics during resting state and different memory cognitive tasks is conducted on two patient groups to search for potential biomarkers. The 33 participants were divided into two groups: SCD and MCI.

Results: Functional connectivity strength during the resting state and hemodynamic changes during the execution of Verbal Fluency Tasks (VFT) and MemTrax tasks were measured using fNIRS. The results showed that compared to individuals with MCI, patients with SCD exhibited higher average FC levels between different channels in the frontal lobe during resting state, with two channels' FC demonstrating significant ability to distinguish between SCD and MCI. During the VFT task, the overall average HbO concentration in the frontal lobe of SCD patients was higher than that of MCI patients from 5 experimental paradigm. Receiver operating characteristic analysis indicated that the accuracy of the above features in distinguishing SCD from MCI was 78.8%, 72.7%, 75.8%, and 66.7%, respectively.

Discussion: fNIRS could potentially serve as a non-invasive biomarker for the early detection of dementia.

Keywords: Alzheimer’s disease; MCI; SCD; early diagnosis; functional near-infrared spectroscopy.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by National Key R&D Program of China grant #2022YFB4702202, Jiangsu Provincial Key Technology R&D Program grant #BE2021009-02, the National Natural Science Foundation of China (82171198), Shanghai Municipal Science Technology Major Project (2018SHZDZX01), and supported by Medicine-engineering Interdisciplinary Project set up by University of Shanghai for Science and Technology, project No. 2023JK-LLY34Y.