Cargando…

Early Detection of Alzheimer’s Disease Using Non-invasive Near-Infrared Spectroscopy

Mild cognitive impairment (MCI) is a cognitive disorder characterized by memory impairment, wherein patients have an increased likelihood of developing Alzheimer’s disease (AD). The classification of MCI and different AD stages is therefore fundamental for understanding and treating the disease. Thi...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Rihui, Rui, Guoxing, Chen, Wei, Li, Sheng, Schulz, Paul E., Zhang, Yingchun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6237862/
https://www.ncbi.nlm.nih.gov/pubmed/30473662
http://dx.doi.org/10.3389/fnagi.2018.00366
_version_ 1783371258111459328
author Li, Rihui
Rui, Guoxing
Chen, Wei
Li, Sheng
Schulz, Paul E.
Zhang, Yingchun
author_facet Li, Rihui
Rui, Guoxing
Chen, Wei
Li, Sheng
Schulz, Paul E.
Zhang, Yingchun
author_sort Li, Rihui
collection PubMed
description Mild cognitive impairment (MCI) is a cognitive disorder characterized by memory impairment, wherein patients have an increased likelihood of developing Alzheimer’s disease (AD). The classification of MCI and different AD stages is therefore fundamental for understanding and treating the disease. This study aimed to comprehensively investigate the hemodynamic response patterns among various subject groups. Functional near-infrared spectroscopy (fNIRS) was employed to measure signals from the frontal and bilateral parietal cortices of healthy controls (n = 8), patients with MCI (n = 9), mild (n = 6), and moderate/severe AD (n = 7) during a digit verbal span task (DVST). The concentration changes of oxygenated hemoglobin (HbO) in various subject groups were thoroughly explored and tested. Result revealed that abnormal patterns of hemodynamic response were observed across all subject groups. Greater and steeper reductions in HbO concentration were consistently observed across all regions of interest (ROIs) as disease severity developed from MCI to moderate/severe AD. Furthermore, all the fNIRS-derived indexes were found to be significantly and positively correlated to the clinical scores in all ROIs (R ≥ 0.4, P < 0.05). These findings demonstrate the feasibility of utilizing fNIRS for the early detection of AD, suggesting that fNIRS-based approaches hold great promise for exploring the mechanisms underlying the progression of AD.
format Online
Article
Text
id pubmed-6237862
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-62378622018-11-23 Early Detection of Alzheimer’s Disease Using Non-invasive Near-Infrared Spectroscopy Li, Rihui Rui, Guoxing Chen, Wei Li, Sheng Schulz, Paul E. Zhang, Yingchun Front Aging Neurosci Neuroscience Mild cognitive impairment (MCI) is a cognitive disorder characterized by memory impairment, wherein patients have an increased likelihood of developing Alzheimer’s disease (AD). The classification of MCI and different AD stages is therefore fundamental for understanding and treating the disease. This study aimed to comprehensively investigate the hemodynamic response patterns among various subject groups. Functional near-infrared spectroscopy (fNIRS) was employed to measure signals from the frontal and bilateral parietal cortices of healthy controls (n = 8), patients with MCI (n = 9), mild (n = 6), and moderate/severe AD (n = 7) during a digit verbal span task (DVST). The concentration changes of oxygenated hemoglobin (HbO) in various subject groups were thoroughly explored and tested. Result revealed that abnormal patterns of hemodynamic response were observed across all subject groups. Greater and steeper reductions in HbO concentration were consistently observed across all regions of interest (ROIs) as disease severity developed from MCI to moderate/severe AD. Furthermore, all the fNIRS-derived indexes were found to be significantly and positively correlated to the clinical scores in all ROIs (R ≥ 0.4, P < 0.05). These findings demonstrate the feasibility of utilizing fNIRS for the early detection of AD, suggesting that fNIRS-based approaches hold great promise for exploring the mechanisms underlying the progression of AD. Frontiers Media S.A. 2018-11-09 /pmc/articles/PMC6237862/ /pubmed/30473662 http://dx.doi.org/10.3389/fnagi.2018.00366 Text en Copyright © 2018 Li, Rui, Chen, Li, Schulz and Zhang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Li, Rihui
Rui, Guoxing
Chen, Wei
Li, Sheng
Schulz, Paul E.
Zhang, Yingchun
Early Detection of Alzheimer’s Disease Using Non-invasive Near-Infrared Spectroscopy
title Early Detection of Alzheimer’s Disease Using Non-invasive Near-Infrared Spectroscopy
title_full Early Detection of Alzheimer’s Disease Using Non-invasive Near-Infrared Spectroscopy
title_fullStr Early Detection of Alzheimer’s Disease Using Non-invasive Near-Infrared Spectroscopy
title_full_unstemmed Early Detection of Alzheimer’s Disease Using Non-invasive Near-Infrared Spectroscopy
title_short Early Detection of Alzheimer’s Disease Using Non-invasive Near-Infrared Spectroscopy
title_sort early detection of alzheimer’s disease using non-invasive near-infrared spectroscopy
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6237862/
https://www.ncbi.nlm.nih.gov/pubmed/30473662
http://dx.doi.org/10.3389/fnagi.2018.00366
work_keys_str_mv AT lirihui earlydetectionofalzheimersdiseaseusingnoninvasivenearinfraredspectroscopy
AT ruiguoxing earlydetectionofalzheimersdiseaseusingnoninvasivenearinfraredspectroscopy
AT chenwei earlydetectionofalzheimersdiseaseusingnoninvasivenearinfraredspectroscopy
AT lisheng earlydetectionofalzheimersdiseaseusingnoninvasivenearinfraredspectroscopy
AT schulzpaule earlydetectionofalzheimersdiseaseusingnoninvasivenearinfraredspectroscopy
AT zhangyingchun earlydetectionofalzheimersdiseaseusingnoninvasivenearinfraredspectroscopy