Wang Luoyu, Feng Qi, Wang Mei, Zhu Tingting, Yu Enyan, Niu Jialing, Ge Xiuhong, Mao Dewang, Lv Yating, Ding Zhongxiang
Centre for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang,China.
Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang,China.
Curr Alzheimer Res. 2021;18(1):45-55. doi: 10.2174/1567205018666210324130502.
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.
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).
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.
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.
作为一种潜在的脑成像生物标志物,低频振幅(ALFF)已被用作区分阿尔茨海默病(AD)、遗忘型轻度认知障碍(aMCI)患者与正常对照(NC)的一个特征。然而,ALFF改变的频率依赖性模式是否能有效区分疾病的不同阶段仍不清楚。
在本研究中,共纳入52例AD患者、50例aMCI患者以及43名NC。对三组不同人群计算以下三个频段的ALFF值:经典频段(0.01 - 0.08Hz)、慢4频段(0.027 - 0.073Hz)和慢5频段(0.01 - 0.027Hz)。随后,将局部功能异常作为特征,使用支持向量机(SVM)检验其在AD、aMCI和NC之间的分类效果。
我们发现不同频段ALFF的组间差异主要位于左侧海马(HP)、右侧HP、双侧后扣带回皮质(PCC)和双侧楔前叶(PCu)、左侧角回(AG)和左侧内侧前额叶皮质(mPFC)。当将局部功能异常作为特征时,我们发现慢5频段的ALFF在区分三组人群时显示出最高的准确率。
这些发现可能会加深我们对AD发病机制的理解,并表明慢5频段可能有助于探索该疾病的发病机制和区分疾病阶段。