College of Electronic Information Engineering, Shandong University of Science and Technology, Qingdao, China.
School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China.
Med Phys. 2023 Jun;50(6):3873-3884. doi: 10.1002/mp.16410. Epub 2023 Apr 25.
The lack of analysis of brain networks in individuals with end-stage renal disease (ESRD) is an obstacle to detecting and preventing neurological complications of ESRD.
This study aims to explore the correlation between brain activity and ESRD based on a quantitative analysis of the dynamic functional connectivity (dFC) of brain networks. It provides insights into differences in brain functional connectivity between healthy individuals and ESRD patients and aims to identify the brain activities and regions most relevant to ESRD.
Differences in brain functional connectivity between healthy individuals and ESRD patients were analyzed and quantitatively evaluated in this study. Blood oxygen level-dependent (BOLD) signals obtained through resting-state functional magnetic resonance imaging (rs-fMRI) were used as information carriers. First, a connectivity matrix of dFC was constructed for each subject using Pearson correlation. Then a high-order connectivity matrix was built by applying the "correlation's correlation" method. Second, sparsification of the high-order connectivity matrix was performed using the graphical least absolute shrinkage and selection operator (gLASSO) model. The discriminative features of the sparse connectivity matrix were extracted and sifted using central moments and t-tests, respectively. Finally, feature classification was conducted using a support vector machine (SVM).
The experiment showed that functional connectivity was reduced to some degree in certain brain regions of ESRD patients. The sensorimotor, visual, and cerebellum subnetworks had the highest numbers of abnormal functional connectivities. It is inferred that these three subnetworks most likely have a direct relationship to ESRD.
The low-order and high-order dFC features can identify the positions where brain damage occurs in ESRD patients. In contrast to healthy individuals, the damaged brain regions and the disruption of functional connectivity in ESRD patients were not limited to specific regions. This indicates that ESRD has a severe impact on brain function. Abnormal functional connectivity was mainly associated with the three functional brain regions responsible for visual processing, emotional, and motor control. The findings presented here have the potential for use in the detection, prevention, and prognostic evaluation of ESRD.
终末期肾病（ESRD）患者的大脑网络缺乏分析，这是检测和预防 ESRD 神经并发症的障碍。
本研究旨在通过对大脑网络的动态功能连接（dFC）进行定量分析，探索基于脑活动与 ESRD 之间的相关性。它提供了对健康个体和 ESRD 患者之间大脑功能连接差异的深入了解，并旨在确定与 ESRD 最相关的大脑活动和区域。
本研究分析和定量评估了健康个体和 ESRD 患者之间的大脑功能连接差异。使用静息态功能磁共振成像（rs-fMRI）获得的血氧水平依赖（BOLD）信号作为信息载体。首先，通过 Pearson 相关对每个受试者的 dFC 构建连接矩阵。然后，通过应用“相关性的相关性”方法构建高阶连接矩阵。其次，使用图形最小绝对收缩和选择算子（gLASSO）模型对高阶连接矩阵进行稀疏化。使用中心矩和 t 检验分别提取和筛选稀疏连接矩阵的鉴别特征。最后，使用支持向量机（SVM）进行特征分类。
实验表明，ESRD 患者某些大脑区域的功能连接度降低到一定程度。感觉运动、视觉和小脑子网具有最高数量的异常功能连接。推断这三个子网很可能与 ESRD 直接相关。
低阶和高阶 dFC 特征可以识别 ESRD 患者大脑受损的位置。与健康个体相比，ESRD 患者受损的大脑区域和功能连接的中断不仅限于特定区域。这表明 ESRD 对大脑功能有严重影响。异常功能连接主要与负责视觉处理、情感和运动控制的三个功能大脑区域相关。本研究结果具有用于 ESRD 的检测、预防和预后评估的潜力。
