Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Department of Radiology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei Province, China.
Lupus Sci Med. 2024 Sep 11;11(2):e001221. doi: 10.1136/lupus-2024-001221.
This study investigated the topological structural characteristics of systemic lupus erythematosus (SLE) with and without neuropsychiatric symptoms (NPSLE and non-NPSLE), and explore their clinical implications.
We prospectively recruited 50 patients with SLE (21 non-NPSLE and 29 NPSLE) and 32 age-matched healthy controls (HCs), using MRI diffusion tensor imaging. Individual structural networks were constructed using fibre numbers between brain areas as edge weights. Global metrics (eg, small-worldness, global efficiency) and local network properties (eg, degree centrality, nodal efficiency) were computed. Group comparisons of network characteristics were conducted. Clinical correlations were assessed using partial correlation, and differentiation between non-NPSLE and NPSLE was performed using support vector classification.
Patients with oth non-NPSLE and NPSLE exhibited significant global and local topological alterations compared with HCs. These changes were more pronounced in NPSLE, particularly affecting the default mode and sensorimotor networks. Topological changes in patients with SLE correlated with lesion burdens and clinical parameters such as disease duration and the systemic lupus international collaborating clinics damage index. The identified topological features enabled accurate differentiation between non-NPSLE and NPSLE with 87% accuracy.
Structural networks in patients SLE may be altered at both global and local levels, with more pronounced changes observed in NPSLE, notably affecting the default mode and sensorimotor networks. These alterations show promise as biomarkers for clinical diagnosis.
本研究旨在探讨伴有和不伴有神经精神性狼疮(NPSLE 和非 NPSLE)的系统性红斑狼疮(SLE)的拓扑结构特征,并探讨其临床意义。
我们前瞻性招募了 50 例 SLE 患者(21 例非 NPSLE 和 29 例 NPSLE)和 32 名年龄匹配的健康对照者(HCs),使用 MRI 弥散张量成像。使用脑区之间的纤维数量作为边权重构建个体结构网络。计算全局度量(例如小世界性、全局效率)和局部网络特性(例如度中心性、节点效率)。进行组间网络特征比较。使用偏相关评估临床相关性,并使用支持向量分类来区分非 NPSLE 和 NPSLE。
与 HCs 相比,非 NPSLE 和 NPSLE 患者均表现出明显的全局和局部拓扑改变。在 NPSLE 中,这些改变更为明显,特别是影响默认模式和感觉运动网络。SLE 患者的拓扑变化与病变负荷以及疾病持续时间和系统性红斑狼疮国际合作诊所损害指数等临床参数相关。所确定的拓扑特征可准确地区分非 NPSLE 和 NPSLE,准确率为 87%。
SLE 患者的结构网络可能在全局和局部水平上发生改变,NPSLE 中更为明显,特别是影响默认模式和感觉运动网络。这些改变有望成为临床诊断的生物标志物。