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静息态功能磁共振成像揭示阿尔茨海默病患者功能连接性的改变。

Alteration of functional connectivity in patients with Alzheimer's disease revealed by resting-state functional magnetic resonance imaging.

作者信息

Zhao Jie, Du Yu-Hang, Ding Xue-Tong, Wang Xue-Hu, Men Guo-Zun

机构信息

School of Electronic and Information Engineering, Hebei University; Research Center of Machine Vision Engineering & Technology of Hebei Province; Key Laboratory of Digital Medical Engineering of Hebei Province, Baoding, Hebei Province, China.

School of Electronic and Information Engineering, Hebei University, Baoding, Hebei Province, China.

出版信息

Neural Regen Res. 2020 Feb;15(2):285-292. doi: 10.4103/1673-5374.265566.

Abstract

The main symptom of patients with Alzheimer's disease is cognitive dysfunction. Alzheimer's disease is mainly diagnosed based on changes in brain structure. Functional connectivity reflects the synchrony of functional activities between non-adjacent brain regions, and changes in functional connectivity appear earlier than those in brain structure. In this study, we detected resting-state functional connectivity changes in patients with Alzheimer's disease to provide reference evidence for disease prediction. Functional magnetic resonance imaging data from patients with Alzheimer's disease were used to show whether particular white and gray matter areas had certain functional connectivity patterns and if these patterns changed with disease severity. In nine white and corresponding gray matter regions, correlations of normal cognition, early mild cognitive impairment, and late mild cognitive impairment with blood oxygen level-dependent signal time series were detected. Average correlation coefficient analysis indicated functional connectivity patterns between white and gray matter in the resting state of patients with Alzheimer's disease. Functional connectivity pattern variation correlated with disease severity, with some regions having relatively strong or weak correlations. We found that the correlation coefficients of five regions were 0.3-0.5 in patients with normal cognition and 0-0.2 in those developing Alzheimer's disease. Moreover, in the other four regions, the range increased to 0.45-0.7 with increasing cognitive impairment. In some white and gray matter areas, there were specific connectivity patterns. Changes in regional white and gray matter connectivity patterns may be used to predict Alzheimer's disease; however, detailed information on specific connectivity patterns is needed. All study data were obtained from the Alzheimer's Disease Neuroimaging Initiative Library of the Image and Data Archive Database.

摘要

阿尔茨海默病患者的主要症状是认知功能障碍。阿尔茨海默病主要根据脑结构变化进行诊断。功能连接反映了非相邻脑区之间功能活动的同步性,且功能连接的变化比脑结构变化出现得更早。在本研究中,我们检测了阿尔茨海默病患者静息态功能连接的变化,以为疾病预测提供参考依据。使用阿尔茨海默病患者的功能磁共振成像数据来显示特定的白质和灰质区域是否具有特定的功能连接模式,以及这些模式是否随疾病严重程度而变化。在九个白质和相应的灰质区域中,检测了正常认知、早期轻度认知障碍和晚期轻度认知障碍与血氧水平依赖信号时间序列的相关性。平均相关系数分析表明了阿尔茨海默病患者静息态下白质和灰质之间的功能连接模式。功能连接模式变化与疾病严重程度相关,一些区域的相关性相对较强或较弱。我们发现,在认知正常的患者中,五个区域的相关系数为0.3 - 0.5,而在患阿尔茨海默病的患者中为0 - 0.2。此外,在其他四个区域,随着认知障碍的加重,范围增加到0.45 - 0.7。在一些白质和灰质区域,存在特定的连接模式。区域白质和灰质连接模式的变化可用于预测阿尔茨海默病;然而,需要有关特定连接模式的详细信息。所有研究数据均来自图像与数据存档数据库的阿尔茨海默病神经影像倡议库。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e13/6905343/497321ad5338/NRR-15-285-g002.jpg

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