Near-Infrared Optical Spectroscopy In Vivo Distinguishes Subjects with Alzheimer's Disease from Age-Matched Controls

被引:3
|
作者
Greco, Frank A. [1 ]
McKee, Ann C. [1 ,2 ,3 ,4 ,5 ,6 ]
Kowall, Neil W. [2 ,3 ,4 ,5 ,6 ]
Hanlon, Eugene B. [1 ]
机构
[1] VA Bedford Healthcare Syst, Med Res & Dev Serv, Bedford, MA 01730 USA
[2] VA Boston Healthcare Syst, Neurol Serv, Boston, MA USA
[3] Boston Univ, Alzheimers Dis Ctr, Sch Med, Boston, MA USA
[4] Chron Traumat Encephalopathy Ctr, Boston, MA USA
[5] Boston Univ, Sch Med, Dept Pathol & Lab Med, Boston, MA USA
[6] Boston Univ, Dept Neurol, Boston, MA USA
基金
美国国家卫生研究院;
关键词
Alzheimer's disease; cognitive dysfunction; data analysis; mild cognitive impairment; near-infrared spectroscopy; ADULT HEAD MODEL; LIGHT-PROPAGATION; ABSORPTION SPECTROPHOTOMETRY; NEUROPATHOLOGIC ASSESSMENT; PERFORMANCE; NIRS; OXYGENATION; SCATTERING; THICKNESS; CRITERIA;
D O I
10.3233/JAD-201021
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Background: Medical imaging methods such as PET and MRI aid clinical assessment of Alzheimer's disease (AD). Less expensive, less technically demanding, and more widely deployable technologies are needed to expand objective screening for diagnosis, treatment, and research. We previously reported brain tissue near-infrared optical spectroscopy (NIR) in vitro indicating the potential to meet this need. Objective: To determine whether completely non-invasive, clinical, NIR in vivo can distinguish AD patients from age-matched controls and to show the potential of NIR as a clinical screen and monitor of therapeutic efficacy. Methods: NIR spectra were acquired in vivo. Three groups were studied: autopsy-confirmed AD, control and mild cognitive impairment (MCI). A feature selection approach using the first derivative of the intensity normalized spectra was used to discover spectral regions that best distinguished "AD-alone" (i.e., without other significant neuropathology) from controls. The approach was then applied to other autopsy-confirmed AD cases and to clinically diagnosed MCI cases. Results: Two regions about 860 and 895 nm completely separate AD patients from controls and differentiate MCI subjects according to the degree of impairment. The 895 nm feature is more important in separating MCI subjects from controls (ratio-of-weights: 1.3); the 860 nm feature is more important for distinguishing MCI from AD (ratio-of-weights: 8.2). Conclusion: These results form a proof of the concept that near-infrared spectroscopy can detect and classify diseased and normal human brain in vivo. A clinical trial is needed to determine whether the two features can track disease progression and monitor potential therapeutic interventions.
引用
收藏
页码:791 / 802
页数:12
相关论文
共 50 条
  • [21] Efficient Near-Infrared In Vivo Imaging of Amyoid-β Deposits in Alzheimer's Disease Mouse Models
    Schmidt, Anke
    Pahnke, Jens
    JOURNAL OF ALZHEIMERS DISEASE, 2012, 30 (03) : 651 - 664
  • [22] Assessment of Persistent, Bioaccumulative and Toxic Organic Environmental Pollutants in Liver and Adipose Tissue of Alzheimer's Disease Patients and Age-matched Controls
    Manivannan, Bhagyashree
    Yegambaram, Manivannan
    Supowit, Samuel
    Beach, Thomas G.
    Halden, Rolf U.
    CURRENT ALZHEIMER RESEARCH, 2019, 16 (11) : 1039 - 1049
  • [23] Altered cerebrovascular-CSF coupling in Alzheimer's Disease measured by functional near-infrared spectroscopy
    Ferdinando, Hany
    Moradi, Sadegh
    Korhonen, Vesa
    Kiviniemi, Vesa
    Myllyla, Teemu
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [24] Global Dimensional Complexity of multichannel EEG in mild Alzheimer's disease and age-matched cohorts
    Yagyu, T
    Wackermann, J
    Shigeta, M
    Jelic, V
    Kinoshita, T
    Kochi, K
    Julin, P
    Almkvist, O
    Wahlund, LO
    Kondakor, I
    Lehmann, D
    DEMENTIA AND GERIATRIC COGNITIVE DISORDERS, 1997, 8 (06) : 343 - 347
  • [25] In Vivo Brain Imaging of Amyloid-β Aggregates in Alzheimer's Disease with a Near-Infrared Fluorescent Probe
    Wu, Jian
    Shao, Chenwen
    Ye, Xiaolian
    Di, Xiaojiao
    Li, Dongdong
    Zhao, Hu
    Zhang, Bing
    Chen, Guiquan
    Liu, Hong-Ke
    Qian, Yong
    ACS SENSORS, 2021, 6 (03): : 863 - 870
  • [26] Near-infrared Fluorescence Ocular Imaging (NIRFOI) of Alzheimer's Disease
    Yang, Jian
    Yang, Jing
    Li, Yuyan
    Xu, Yungen
    Ran, Chongzhao
    MOLECULAR IMAGING AND BIOLOGY, 2019, 21 (01) : 35 - 43
  • [27] A Pilot Study of Near-Infrared Light Treatment for Alzheimer's Disease
    Chen, Liang
    Xue, Jun
    Zhao, Qianhua
    Liang, Xiaoniu
    Zheng, Li
    Fan, Zhen
    Souare, Ibrahima Sory Jnr
    Suo, Yuanzhen
    Wei, Xunbin
    Ding, Ding
    Mao, Ying
    JOURNAL OF ALZHEIMERS DISEASE, 2023, 91 (01) : 191 - 201
  • [28] Near-infrared Fluorescence Ocular Imaging (NIRFOI) of Alzheimer’s Disease
    Jian Yang
    Jing Yang
    Yuyan Li
    Yungen Xu
    Chongzhao Ran
    Molecular Imaging and Biology, 2019, 21 : 35 - 43
  • [29] Plasma near-infrared spectroscopy for diagnosis of idiopathic Parkinson's disease: the SPIN-PD study
    Ravina, Bernard
    Eberly, Shirley
    Oakes, David
    Lang, Anthony E.
    Dodelet, Vince
    Roos, Pieter
    Harman, Jennifer
    Shoulson, Ira
    Schipper, Hyman M.
    BIOMARKERS IN MEDICINE, 2015, 9 (02) : 89 - 97
  • [30] Correlation Between Prefrontal Functional Connectivity and the Degree of Cognitive Impairment in Alzheimer's Disease: A Functional Near-Infrared Spectroscopy Study
    Zhang, Mengxue
    Qu, Yanjie
    Li, Qian
    Gu, Chao
    Zhang, Limin
    Chen, Hongxu
    Ding, Minrui
    Zhang, Tong
    Zhen, Rongrong
    An, Hongmei
    JOURNAL OF ALZHEIMERS DISEASE, 2024, 98 (04) : 1287 - 1300