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An Effective Brain Imaging Biomarker for AD and aMCI: ALFF in Slow-5 Frequency Band
Current Alzheimer Research ( IF 2.1 ) Pub Date : 2020-12-31 , DOI: 10.2174/1567205018666210324130502
Luoyu Wang 1 , Qi Feng 2 , Mei Wang 2 , Tingting Zhu 1 , Enyan Yu 3 , Jialing Niu 2 , Xiuhong Ge 2 , Dewang Mao 4 , Yating Lv 1 , Zhongxiang Ding 2
Affiliation  

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.



中文翻译:

AD 和 aMCI 的有效脑成像生物标志物:Slow-5 频段的 ALFF

背景:作为一种潜在的脑成像生物标志物,低频波动幅度(ALFF)已被用作区分阿尔茨海默病(AD)和遗忘性轻度认知障碍(aMCI)患者与正常对照(NC)的特征。然而,目前尚不清楚 ALFF 改变的频率依赖性模式是否可以有效地区分疾病的不同阶段。

方法:本研究共纳入 52 名 AD 患者、50 名 aMCI 患者以及 43 名 NC 患者。三个不同组的 ALFF 值在以下三个频带中计算:古典(0.01-0.08 Hz)、慢速 4(0.027-0.073 Hz)和慢速 5(0.01-0.027 Hz)。随后,采用局部功能异常作为特征,使用支持向量机(SVM)检查 AD、aMCI 和 NC 之间的分类效果。

结果:我们发现不同频段的ALFF组间差异主要位于左侧海马(HP)、右侧HP、双侧后扣带皮层(PCC)和双侧楔前叶(PCu)、左侧角回(AG) )和左内侧前额皮质(mPFC)。当采用局部功能异常作为特征时,我们发现慢 5 频段的 ALFF 在区分三组时表现出最高的准确度。

结论:这些发现可能加深我们对AD发病机制的认识,并提示slow-5频段可能有助于探讨该疾病的发病机制和区分该疾病的阶段。

更新日期:2020-12-31
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