Department of Neurology, The First Affiliated Hospital of Anhui Medical University, the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.
Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.
J Alzheimers Dis. 2023;93(4):1443-1455. doi: 10.3233/JAD-221037.
Abnormalities in white matter (WM) may be a crucial physiologic feature of Alzheimer's disease (AD). However, neuroimaging's ability to visualize the underlying functional degradation of the WM region in AD is unclear.
This study aimed to explore the differences in amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) in the WM region of patients with AD and healthy controls (HC) and to investigate further whether these values can provide supplementary information for diagnosing AD.
Forty-eight patients with AD and 46 age-matched HC were enrolled and underwent resting-state functional magnetic resonance imaging and a neuropsychological battery assessment. We analyzed the differences in WM activity between the two groups and further explored the correlation between WM activity in the different regions and cognitive function in the AD group. Finally, a machine learning algorithm was adopted to construct a classifier in detecting the clinical classification ability of the values of ALFF/ALFF in the WM.
Compared with HCs, patients with AD had lower WM activity in the right anterior thalamic radiation, left frontal aslant tract, and left forceps minor, which are all positively related to global cognitive function, memory, and attention function (all p < 0.05). Based on the combined WM ALFF and fALFF characteristics in the different regions, individuals not previously assessed were classified with moderate accuracy (75%), sensitivity (71%), specificity (79%), and area under the receiver operating characteristic curve (85%).
Our results suggest that WM activity is reduced in AD and can be used for disease classification.
脑白质（WM）异常可能是阿尔茨海默病（AD）的重要生理特征。然而，神经影像学是否能够可视化 AD 患者 WM 区域的潜在功能退化尚不清楚。
本研究旨在探讨 AD 患者和健康对照（HC）之间 WM 区域的低频振幅（ALFF）和分数 ALFF（fALFF）的差异，并进一步研究这些值是否可以为 AD 的诊断提供补充信息。
纳入 48 例 AD 患者和 46 名年龄匹配的 HC，并进行静息态功能磁共振成像和神经心理学量表评估。我们分析了两组之间 WM 活动的差异，并进一步探讨了 AD 组不同区域 WM 活动与认知功能之间的相关性。最后，采用机器学习算法构建分类器，以检测 WM 中 ALFF/fALFF 值在临床分类中的能力。
与 HC 相比，AD 患者右侧前丘脑辐射、左侧额斜束和左侧小钳的 WM 活性较低，这些区域的 WM 活性均与整体认知功能、记忆力和注意力功能呈正相关（均 p<0.05）。基于不同区域的 WM ALFF 和 fALFF 特征，对未预先评估的个体进行分类，具有中等准确性（75%）、敏感性（71%）、特异性（79%）和受试者工作特征曲线下面积（85%）。
我们的研究结果表明，AD 患者的 WM 活动减少，可用于疾病分类。
