基于图论的急性脑梗死后应激性高血糖患者脑网络研究

doi:10.3969/j.issn.1004-583X.2025.09.002

摘要/Abstract

摘要：

目的基于扩散张量成像技术及图论研究方法,从结构脑网络水平探究急性脑梗死(acute cerebral infarction,ACI)后应激性高血糖(stress-induced hyperglycemia,SIH)的神经生理学机制。方法前瞻性纳入ACI后SIH患者32例和年龄、性别相匹配的健康对照组(healthy control,HC)35例。基于应激性高血糖比率(stress hyperglycemia ratio,SHR)确定脑梗死患者是否入组。所有受试者均行磁共振成像检查,通过确定性纤维束追踪方法构建结构脑网络。采用图论分析方法,计算结构脑网络的全局属性指标及富人俱乐部(Rich-Club)属性参数,并基于网络的边进行连接强度分析,同时分析SIH患者异常的网络属性指标与SHR之间的相关性。结果全局属性指标中,SIH组的聚类系数(Cp)、全局效率(Eglob)、局部效率(Eloc)均较HC组减低,而特征路径长度(Lp)较HC组增大( $P$ <0.01);SIH组与HC组均表现出小世界属性,且SIH组小世界属性值(σ)、标准化特征路径长度(λ)、标准化聚类系数(γ)均较HC组增大( $P$ <0.01);与HC组相比,SIH组的rich连接(Rich-Club节点之间的连接)、local连接(非Rich-Club节点之间的连接)、feeder连接(Rich-Club节点与非Rich-Club节点之间的连接)的连接强度均减低( $P$ <0.01);基于网络的边的分析表明经过基于网络的统计(NBS)校正后发现SIH组存在一个连接强度减低的子网络( $P$ =0.0002),即左侧额叶-脑岛-边缘系统子网络,其主要由6个节点及5条连边构成;相关性分析结果显示异常脑网络参数指标与SHR未见明显关联( $P$ >0.05)。结论 ACI后发生SIH的患者大脑结构网络明显受损,并具有向规则网络转化的趋势;同时SIH患者Rich-Club属性严重受损,多种连接强度减低;左侧额叶-脑岛-边缘系统子网络连接强度减低涉及大脑核心节点损伤,提示该子网络可能是致病核心区域,并且患者未来存在多种功能障碍及潜在疾病风险。

关键词: 脑梗死, 应激性高血糖, 扩散张量成像, 富人俱乐部, 脑网络拓扑属性

Abstract:

Objective To explore the neurophysiological mechanisms of stress-induced hyperglycemia (SIH) after acute cerebral infarction (ACI) at the level of structural brain networks based on diffusion tensor imaging (DTI) and graph theory. Methods A total of 32 SIH patients after ACI and 35 healthy controls (HC) matched for sex and age were prospectively selected. SIH patients were identified based on the stress hyperglycemia ratio (SHR). All subjects underwent magnetic resonance imaging (MRI), and structural brain networks were constructed using deterministic tractography. Graph theory analysis was applied to calculate the global attribute indicators and the Rich-Club attribute parameters of the structural brain network. Additionally, this study analyzed connection strength based on the edges of the network, and the potential correlation between the abnormal network attribute indicators and SHR in post-ACI patients. Results In the global attribute indicators, the clustering coefficient (Cp), global efficiency (Eglob), and local efficiency (Eloc) of the SIH group were significantly lower compared to the HC group, while the characteristic path length (Lp) was significantly higher compared to the HC group ( $P$ <0.01). Both the SIH group and the HC group exhibited small-world organization, and the values of small-worldness (σ), normalized characteristic path length (λ), and normalized clustering coefficient (γ) in the SIH group were significantly larger than those in the HC group ( $P$ <0.01). Compared to the HC group, the connection strength of rich connections (connections between Rich-Club nodes), local connections (connections between non-Rich-Club nodes), and feeder connections (connections between Rich-Club nodes and non-Rich-Club nodes) were significantly lower in the SIH group ( $P$ <0.01). Network-based edge analysis showed that after network-based statistics (NBS) correction, a subnetwork with reduced connection strength was found to exist in the SIH group ( $P$ =0.0002), namely the left frontal-insula-limbic system subnetwork, consisting mainly of 6 nodes and 5 connected edges. The results of the correlation analysis showed no significant association between the abnormal brain network parameter indicators and SHR ( $P$ >0.05). Conclusion Structural brain network is significantly impaired in SIH patients after ACI, and the network has a tendency to transform into a regular network. At the same time, Rich-Club properties are severely impaired in SIH patients after ACI, and the strength of multiple connections is reduced. The reduced connectivity of the left frontal-islet-limbic system sub-network involved damage to the core nodes of the brain, suggesting that this sub-network may be an indication of a pathogenic core region, as well as future multiple dysfunctions and potential disease risks.

Key words: brain infarction, stress-induced hyperglycemia, diffusion tensor imaging, rich-club, brain network topological properties

中图分类号:

R743.33

刘丽莹, 崔凯歌, 于佳琪, 贾娟, 孙利强, 杨冀萍. 基于图论的急性脑梗死后应激性高血糖患者脑网络研究[J]. 临床荟萃, 2025, 40(9): 781-789.

Liu Liying, Cui Kaige, Yu Jiaqi, Jia Juan, Sun Liqiang, Yang Jiping. Study of brain network in patients with stress hyperglycemia after acute cerebral infarction based on graph theory[J]. Clinical Focus, 2025, 40(9): 781-789.

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链接本文: https://www.lchc.cn/CN/10.3969/j.issn.1004-583X.2025.09.002

https://www.lchc.cn/CN/Y2025/V40/I9/781

图/表 10

图1 构建SIH组(图1a)和HC组(图1b)结构网络矩阵

Fig.1 Structural network matrix construction for the SIH group (Fig.1a) and the HC group (Fig.1b)

表1 2组一般临床资料比较

Tab.1 General clinical data between groups

组别	例数	性别(男/女)	年龄(岁)	SIH比率	NIHSS评分(分)	利手(右/左)
SIH组	32	21/11	57.0±7.3	1.12±0.24	2.78±2.47	32/0
HC组	35	16/19	54.4±7.6	-	-	35/0
χ²/ $t$ 值		2.680	1.447	-	-	-
$P$ 值		0.102	0.153	-	-	-

表1 2组一般临床资料比较

Tab.1 General clinical data between groups

组别	例数	性别(男/女)	年龄(岁)	SIH比率	NIHSS评分(分)	利手(右/左)
SIH组	32	21/11	57.0±7.3	1.12±0.24	2.78±2.47	32/0
HC组	35	16/19	54.4±7.6	-	-	35/0
χ²/ $t$ 值		2.680	1.447	-	-	-
$P$ 值		0.102	0.153	-	-	-

表2 脑网络拓扑属性参数分析

Tab.2 Parameters analysis of brain network topology properties

组别	例数	Cp	Lp	γ	λ	σ	Eglob	Eloc
SIH组	32	0.440±0.039	2.838±0.138	5.886±0.433	1.190±0.024	4.944±0.338	0.353±0.017	0.596±0.058
对照组	35	0.474±0.031	2.578±0.177	5.063±0.665	1.166±0.026	4.333±0.499	0.389±0.026	0.664±0.047
$t$ 值		-4.019	6.65	6.047	3.872	5.912	-6.893	-5.319
$P$ 值		<0.01	<0.01	<0.01	<0.01	<0.01	<0.01	<0.01

表2 脑网络拓扑属性参数分析

Tab.2 Parameters analysis of brain network topology properties

组别	例数	Cp	Lp	γ	λ	σ	Eglob	Eloc
SIH组	32	0.440±0.039	2.838±0.138	5.886±0.433	1.190±0.024	4.944±0.338	0.353±0.017	0.596±0.058
对照组	35	0.474±0.031	2.578±0.177	5.063±0.665	1.166±0.026	4.333±0.499	0.389±0.026	0.664±0.047
$t$ 值		-4.019	6.65	6.047	3.872	5.912	-6.893	-5.319
$P$ 值		<0.01	<0.01	<0.01	<0.01	<0.01	<0.01	<0.01

图2 SIH组与HC组结构网络全局属性差异

Fig.2 Difference in global properties of structural networks between the SIH group and the HC group

表3 不同连接类型的连接强度分析

Tab.3 Connection strength analysis for different connection types

组别	例数	rich连接	feeder连接	local连接
SIH组	32	6.224±0.936	46.954±4.935	70.782±7.465
HC组	35	8.052±1.631	59.526±10.341	90.909±17.023
$t$ 值		-5.554	-6.254	-6.165
$P$ 值		<0.01	<0.01	<0.01

表3 不同连接类型的连接强度分析

Tab.3 Connection strength analysis for different connection types

组别	例数	rich连接	feeder连接	local连接
SIH组	32	6.224±0.936	46.954±4.935	70.782±7.465
HC组	35	8.052±1.631	59.526±10.341	90.909±17.023
$t$ 值		-5.554	-6.254	-6.165
$P$ 值		<0.01	<0.01	<0.01

图3 两组受试者Rich-Club节点分布及结构脑网络示意图注:FFG.R:右侧梭状回;FFG.L:左侧梭状回;PCUN.L:左侧楔前叶; PreCG.L:左侧中央前回;PreCG.R:右侧中央前回;PCUN.R:右侧楔前叶;DCG.L:左侧内侧和旁扣带回;MOG.L:左侧枕中回;PUT.L:左侧豆状壳核;PUT.R:右侧豆状壳核;INS.L:左侧脑岛;DCG.R:右侧内侧和旁扣带回;HIP.L:左侧海马

Fig.3 Distribution of Rich-Club nodes and schematic diagram of the structural brain network in the two groups of subjects Note: FFG.R: Fusiform_R; FFG.L: Fusiform_L; PCUN.L: Precuneus_L; PreCG.L: Precentral_L; PreCG.R: Precentral_R; PCUN.R: Precuneus_R; DCG.L: Cingulum_Mid_L; MOG.L: Occipital_Mid_L; PUT.L: Putamen_L; PUT.R: Putamen_R; INS.L: Insula_L; DCG.R: Cingulum_Mid_R; HIP.L: Hippocampus_L

图4 Rich-Club 3种连接方式示意图

Fig.4 Schematic diagram of the three types of Rich-Club connections

图5 Rich-Club 3类连接强度的差异

Fig.5 Differences in the strength of three types of Rich-Club connections

图6 SIH组较HC组结构网络减低的连接注:IFGoperc.L:左侧岛盖部额下回;IFGtriang.L:左侧三角部额下回;ORBinf.L:左侧眶部额下回;INS.L:左侧脑岛;HIP.L:左侧海马;AMYG.L:左侧杏仁核

Fig.6 Connection of reduced structural networks in the SIH group compared to the HC group Note: IFGoperc.L: Frontal_Inf_Oper_L; IFGtriang.L: Frontal_Inf_Tri_L; ORBinf.L: Frontal_Inf_Orb_L; INS.L: Insula_L; HIP.L: Hippocampus_L; AMYG.L: Amygdala_L

图7 SIH组异常脑网络参数指标与SHR的相关性分析

Fig.7 Correlation analysis of abnormal brain network parameter indicators with SHR in the SIH group

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