An Effective Brain Imaging Biomarker for AD and aMCI: ALFF in Slow-5 Frequency Band

Author(s): Luoyu Wang, Qi Feng, Mei Wang, Tingting Zhu, Enyan Yu, Jialing Niu, Xiuhong Ge, Dewang Mao, Yating Lv*, Zhongxiang Ding*

Journal Name: Current Alzheimer Research

Volume 18 , Issue 1 , 2021


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Abstract:

Background: As a potential brain imaging biomarker, amplitude of low frequency fluctuation (ALFF) has been used as a feature to distinguish patients with Alzheimer’s disease (AD) and amnestic mild cognitive impairment (aMCI) from normal controls (NC). However, it remains unclear whether the frequency-dependent pattern of ALFF alterations can effectively distinguish the different phases of the disease.

Methods: In the present study, 52 AD and 50 aMCI patients were enrolled together with 43 NC in total. The ALFF values were calculated in the following three frequency bands: classical (0.01-0.08 Hz), slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) for the three different groups. Subsequently, the local functional abnormalities were employed as features to examine the effect of classification among AD, aMCI and NC using a support vector machine (SVM).

Results: We found that the among-group differences of ALFF in the different frequency bands were mainly located in the left hippocampus (HP), right HP, bilateral posterior cingulate cortex (PCC) and bilateral precuneus (PCu), left angular gyrus (AG) and left medial prefrontal cortex (mPFC). When the local functional abnormalities were employed as features, we identified that the ALFF in the slow-5 frequency band showed the highest accuracy to distinguish among the three groups.

Conclusion: These findings may deepen our understanding of the pathogenesis of AD and suggest that slow-5 frequency band may be helpful to explore the pathogenesis and distinguish the phases of this disease.

Keywords: Alzheimer’s disease, amnestic mild cognitive impairment, resting-state functional magnetic resonance imaging, amplitude of low frequency fluctuation, slow-5 frequency band, support vector machine.

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VOLUME: 18
ISSUE: 1
Year: 2021
Published on: 24 March, 2021
Page: [45 - 55]
Pages: 11
DOI: 10.2174/1567205018666210324130502
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