Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Korean J Radiol. 2022 Oct;23(10):986-997. doi: 10.3348/kjr.2022.0320. Epub 2022 Sep 5.
Whether metabolic redistribution occurs in patients with white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) is unknown. This study aimed 1) to propose a measure of the brain metabolic network for an individual patient and preliminarily apply it to identify impaired metabolic networks in patients with WMHs, and 2) to explore the clinical and imaging features of metabolic redistribution in patients with WMHs.
This study included 50 patients with WMHs and 70 healthy controls (HCs) who underwent F-fluorodeoxyglucose-positron emission tomography/MRI. Various global property parameters according to graph theory and an individual parameter of brain metabolic network called "individual contribution index" were obtained. Parameter values were compared between the WMH and HC groups. The performance of the parameters in discriminating between the two groups was assessed using the area under the receiver operating characteristic curve (AUC). The correlation between the individual contribution index and Fazekas score was assessed, and the interaction between age and individual contribution index was determined. A generalized linear model was fitted with the individual contribution index as the dependent variable and the mean standardized uptake value (SUV) of nodes in the whole-brain network or seven classic functional networks as independent variables to determine their association.
The means ± standard deviations of the individual contribution index were (0.697 ± 10.9) × 10 and (0.0967 ± 0.0545) × 10 in the WMH and HC groups, respectively ( < 0.001). The AUC of the individual contribution index was 0.864 (95% confidence interval, 0.785-0.943). A positive correlation was identified between the individual contribution index and the Fazekas scores in patients with WMHs ( = 0.57, < 0.001). Age and individual contribution index demonstrated a significant interaction effect on the Fazekas score. A significant direct association was observed between the individual contribution index and the SUV of the limbic network ( < 0.001).
The individual contribution index may demonstrate the redistribution of the brain metabolic network in patients with WMHs.
磁共振成像（MRI）上存在脑白质高信号（WMHs）的患者是否存在代谢再分布尚不清楚。本研究旨在：1）提出一种个体患者脑代谢网络的测量方法，并初步应用该方法识别 WMHs 患者的代谢网络受损情况；2）探讨 WMHs 患者代谢再分布的临床和影像特征。
本研究纳入了 50 例 WMHs 患者和 70 例健康对照者（HCs），所有受试者均接受 F-氟脱氧葡萄糖正电子发射断层扫描/磁共振检查。根据图论获得各种全局属性参数和个体脑代谢网络的个体参数，称为“个体贡献指数”。比较 WMHs 组和 HCs 组的参数值。采用受试者工作特征曲线下面积（AUC）评估参数在两组间的鉴别能力。评估个体贡献指数与 Fazekas 评分的相关性，并确定年龄与个体贡献指数的交互作用。以个体贡献指数为因变量，全脑网络或 7 个经典功能网络的节点平均标准化摄取值（SUV）为自变量，拟合广义线性模型，以确定它们之间的关系。
WMHs 组和 HCs 组的个体贡献指数均值±标准差分别为（0.697±10.9）×10 和（0.0967±0.0545）×10（ < 0.001）。个体贡献指数的 AUC 为 0.864（95%置信区间，0.785~0.943）。WMHs 患者的个体贡献指数与 Fazekas 评分呈正相关（ = 0.57， < 0.001）。年龄和个体贡献指数对 Fazekas 评分有显著的交互作用。个体贡献指数与边缘网络 SUV 呈显著直接关联（ < 0.001）。
个体贡献指数可能显示了 WMHs 患者脑代谢网络的再分布。
