CTA联合血清TNF-α、IFN-γ对缺血性脑卒中患者颈动脉斑块的诊断价值

doi:10.3969/j.issn.1004-583X.2026.01.006

摘要/Abstract

摘要：

目的研究计算机断层扫描血管成像(computed tomography angiography,CTA)联合血清肿瘤坏死因子-α(tumor necrosis factor α, TNF-α)、干扰素-γ(interferon γ, IFN-γ)在缺血性脑卒中患者颈动脉斑块诊断中的价值。方法纳入2024年1月1日-2024年12月31日在江苏盛泽医院神经内科住院治疗的缺血性脑卒中患者69例为观察组,并选取同期66例健康体检者为对照组。研究采用数字减影血管造影和CTA双模态影像学检测方法,观察组均完成以上两种影像学检查,通过影像数据对比评估CTA在缺血性脑卒中患者颈动脉斑块中的诊断价值。两组均检测血清TNF-α和IFN-γ水平,基于数字减影血管造影结果,将观察组分为斑块阳性亚组(n=44)和斑块阴性亚组(n=25),比较两亚组血清TNF-α和IFN-γ水平。构建CTA联合血清TNF-α和IFN-γ的诊断模型,并通过受试者工作特征曲线评估其诊断效能。结果缺血性脑卒中患者CTA颈动脉斑块阳性检出率为62.3%(43/69),敏感度和特异度分别为93.2%和92.0%,阳性和阴性预测值分别为95.3%和88.5%,总体诊断符合率92.8%。试验组TNF-α和IFN-γ水平均高于对照组(P<0.05),且斑块阳性亚组血清TNF-α和IFN-γ水平也均高于斑块阴性亚组(P<0.05)。受试者工作特征曲线表明,联合模型的预测性能较高,曲线下面积为0.966,且敏感度和特异度均较高, 其中高特异度提示其对排除无斑块缺血性脑卒中患者具有重要价值(P<0.05)。结论 CTA联合TNF-α、IFN-γ构建的多模态诊断模型,对缺血性脑卒中患者颈动脉斑块的评估具有较高的敏感度和特异度,将“影像定位”与“生物定性”结合,能为缺血性脑卒中患者的血管风险分层提供更全面的依据。

关键词: 脑梗死, 计算机断层扫描血管成像, 肿瘤坏死因子-α, 干扰素-γ, 颈动脉斑块

Abstract:

Objective To evaluate the diagnostic value of computed tomography angiography (CTA) combined with serum tumor necrosis factor-α (TNF-α) and interferon-γ (IFN-γ) for detecting carotid artery plaques in patients with ischemic stroke. Methods From January 1 to December 31, 2024, sixty-nine consecutive ischemic stroke inpatients treated in the Department of Neurology at Jiangsu Shengze Hospital were enrolled as the observation group; sixty-six contemporaneous healthy examinees served as controls. All patients underwent both digital subtraction angiography (DSA) and CTA; CTA findings were compared with DSA to assess diagnostic performance. Serum TNF-α and IFN-γ levels were measured in both groups. Based on the DSA results, the patient cohort was divided into plaque-positive (n=44) and plaque-negative (n=25) subgroups. TNF-α and IFN-γ levels were compared between subgroups. A diagnostic model combining CTA with serum TNF-α and IFN-γ was constructed and its performance evaluated by receiver operating characteristic (ROC) curve analysis. Results CTA identified carotid plaques in 43 of 69 ischemic stroke patients (62.3%). Versus DSA, CTA demonstrated sensitivity 93.2%, specificity 92.0%, positive predictive value 95.3%, negative predictive value 88.5%, and overall diagnostic accuracy 92.8%. Serum TNF-α and IFN-γ were significantly higher in ischemic stroke patients than in healthy controls (P<0.05), and levels were significantly greater in the plaque-positive subgroup compared with the plaque-negative subgroup (P<0.05). The combined CTA+TNF-α+IFN-γ diagnostic model showed excellent discrimination (area under the ROC curve [AUC]=0.966) with high sensitivity and specificity (P<0.05); the model’s high specificity indicates particular value for excluding patients without carotid plaque. Conclusion A multimodal diagnostic approach that integrates CTA imaging with serum TNF-α and IFN-γ measurements provides high sensitivity and specificity for detecting carotid plaques in patients with ischemic stroke. By combining anatomical localization from imaging with biomarker-based biological characterization, this strategy offers a more comprehensive basis for vascular risk stratification in ischemic stroke patients.

Key words: brain infarction, computed tomography angiography, tumor necrosis factor-alpha, interferon-gamma, carotid artery plaques

中图分类号:

R743.33

陆敏艳, 周莉, 戚志强, 路阳. CTA联合血清TNF-α、IFN-γ对缺血性脑卒中患者颈动脉斑块的诊断价值[J]. 临床荟萃, 2026, 41(1): 38-43.

Lu Minyan, Zhou Li, Qi Zhiqiang, Lu Yang. Diagnostic value of CTA combined with serum TNF-α and IFN-γ for carotid plaques in ischemic stroke patients[J]. Clinical Focus, 2026, 41(1): 38-43.

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链接本文: https://www.lchc.cn/CN/10.3969/j.issn.1004-583X.2026.01.006

https://www.lchc.cn/CN/Y2026/V41/I1/38

图/表 8

表1 CTA与DSA结果一致性

Tab.1 Consistency of CTA and DSA results

CTA检查	DSA检查(例)		合计
CTA检查	有斑块	无斑块	合计
有斑块	41	2	43
无斑块	3	23	26
合计	44	25	69

表2 两组临床数据比较

Tab.2 Comparison of clinical data between two groups

组别	例数	女性 [例(%)]	年龄 (岁)	高血压 [例(%)]	糖尿病 [例(%)]	TNF-α (ng/L)	IFN-γ (ng/L)
对照组	66	20(30.3)	67.30±12.02	51(77.3)	25(37.9)	1.07(0.57, 1.98)	3.01(0.88, 7.80)
观察组	69	19(27.5)	63.77±11.89	52(75.4)	24(34.8)	1.78(1.24, 2.90)	4.41(2.79, 7.57)
χ²/t/Z值		0.126	1.718	0.068	0.14	-3.405	-2.67
P值		0.723	0.088	0.794	0.708	0.001	0.008

表3 有无斑块组细胞因子水平比较

Tab.3 Comparison of cytokine levels between patients with and without plaques

组别	例数	TNF-α(ng/L)	IFN-γ(ng/L)
斑块阴性亚组	25	1.16(0.51, 1.78)	3.56(1.24, 5.07)
斑块阳性亚组	44	2.00(1.56, 4.03)	5.09(3.87, 8.52)
Z值		-3.84	-3.223
P值		<0.001	0.001

表4 缺血性脑卒中患者颈动脉斑块影响因素的多因素logistic回归分析

Tab.4 Multivariate logistic regression analysis of influencing factors of carotid plaque in patients with ischemic stroke

因素	回归系数	标准误	Wald χ²值	值	值	95% 可信区间
因素	回归系数	标准误	Wald χ²值	值	值	下限	上限
TNF-α	0.488	0.224	4.761	0.029	1.630	1.051	2.527
IFN-γ	0.244	0.11	4.919	0.027	1.277	1.029	1.585

表5 联合诊断模型对缺血性脑卒中患者颈动脉斑块的预测价值

Tab.5 The predictive value of a joint diagnostic model for carotid artery plaques in patients with ischemic stroke

预测项目	AUC	P值	95%可信区间		敏感度	特异度
预测项目	AUC	P值	下限	上限	敏感度	特异度
CTA	0.926	<0.001	0.850	1.000	0.932	0.920
TNF-α	0.780	<0.001	0.662	0.897	0.909	0.520
IFN-γ	0.735	0.001	0.607	0.862	1.000	0.440
联合诊断(串联)	0.966	<0.001	0.921	1.000	0.932	1.000

图1 影像-血清多模态诊断模型的ROC曲线

Fig.1 ROC curve of image-serum multimodal diagnostic model

图2 缺血性脑卒中患者颈动脉斑块的影像学典型图像 a.磁共振成像;b.CTA;c.DSA

Fig.2 Typical imaging of carotid artery plaques in patients with ischemic stroke a.magnetic resonance imaging;b.CTA;c.DSA

图3 缺血性脑卒中患者无颈动脉斑块的影像学典型图像 a.磁共振成像;b.CTA;c.DSA

Fig.3 Typical imaging of ischemic stroke patients without carotid plaques a.magnetic resonance imaging;b.CTA;c.DSA

参考文献 26

[1]	Ridker PM. Anticytokine agents: Targeting interleukin signaling pathways for the treatment of atherothrombosis[J]. Circ Res, 2019, 124(3):437-450. doi:10.1161/CIRCRESAHA.118.313129.
[2]	Shalhoub J, Viiri LE, Cross AJ, et al. Multi-analyte profiling in human carotid atherosclerosis uncovers pro-inflammatory macrophage programming in plaques[J]. Thromb Haemost, 2016, 115(5):1064-1072. doi:10.1160/TH15-08-0650.
[3]	Martinez E, Martorell J, Riambau V. Review of serum biomarkers in carotid atherosclerosis[J]. J Vasc Surg, 2020, 71(1):329-341. doi: 10.1016/j.jvs.2019.04.488.
[4]	Ammirati E, Moroni F, Norata GD, et al. Markers of inflammation associated with plaque progression and instability in patients with carotid atherosclerosis[J]. Mediators Inflamm, 2015, 2015:718329. doi:10.1155/2015/718329.
[5]	Edsfeldt A, Grufman H, Asciutto G, et al. Circulating cytokines reflect the expression of pro-inflammatory cytokines in atherosclerotic plaques[J]. Atherosclerosis, 2015, 241(2):443-449. doi:10.1016/j.atherosclerosis.2015.05.019.
[6]	Warner JJ, Harrington RA, Sacco RL, et al. Guidelines for the early management of patients with acute ischemic stroke: 2019 update to the 2018 guidelines for the early management of acute ischemic stroke[J]. Stroke, 2019, 50(12):3331-3332. doi:10.1161/STROKEAHA.119.027708.
[7]	李鑫, 柴家荣, 王彦平, 等. 三维动态增强磁共振血管壁成像在颈动脉蹼诊断中的应用[J]. 中国CT和MRI杂志, 2024, 22(3):19-21. doi:10.3969/j.issn.1672-5131.2024.03.006.
[8]	戴云蛟, 艾伟平, 刘晓翠, 等. CTA联合血清MMP-9、TIMP-1对脑梗死患者颈动脉斑块诊断价值[J]. 中国CT和MRI杂志, 2024, 22(3):25-27. doi:10.3969/j.issn.1672-5131.2024.03.008.
[9]	GBD 2019 Stroke Collaborators. Global, regional, and national burden of stroke and its risk factors, 1990-2019: A systematic analysis for the Global Burden of Disease Study 2019[J]. Lancet Neurol, 2021, 20(10):795-820. doi: 10.1016/S1474-4422(21)00252-0.
[10]	Wang Y, Zhao X, Liu L, et al. Prevalence and outcomes of symptomatic intracranial large artery stenoses and occlusions in China: The Chinese Intracranial Atherosclerosis (CICAS) Study[J]. Stroke, 2014, 45(3):663-669. doi: 10.1161/STROKEAHA.113.003508.
[11]	王晓民, 王国忠. 数字减影血管造影(DSA)设备的发展趋势[C]// 中华医学会医学工程学分会: 中华医学会医学工程学分会第二次医学影像设备应用技术研讨会论文集, 2001:67-69. doi:ConferenceArticle/5aa655e0c095d72220eb2237.
[12]	Leng X, Wong KS, Liebeskind DS. Evaluating intracranial atherosclerosis rather than intracranial stenosis[J]. Stroke, 2014, 45(2):645-651. doi:10.1161/STROKEAHA.113.002491.
[13]	Cloft HJ, Joseph GJ, Dion JE. Risk of cerebral angiography in patients with subarachnoid hemorrhage, cerebral aneurysm, and arteriovenous malformation: A meta-analysis[J]. Stroke, 1999, 30(2):317-320.doi: 10.1161/01.str.30.2.317.
[14]	Gao L, Li Z, Yuan Z, et al. Major intracranial arterial stenosis influence association between baseline blood pressure and clinical outcomes after thrombolysis in ischemic stroke patients[J]. Brain Behav, 2023, 13(6):e3022. doi: 10.1002/brb3.3022.
[15]	Dieleman N, van der Kolk AG, Zwanenburg JJ, et al. Imaging intracranial vessel wall pathology with magnetic resonance imaging:Current prospects and future directions[J]. Circulation, 2014, 130(2):192-201. doi:10.1161/CIRCULATIONAHA.113.006919.
[16]	吕沙沙, 曹萌萌. CT血管成像与CT灌注成像对急性缺血性脑卒中的诊断价值分析[J]. 实用放射学杂志, 2020, 36(5):4.doi:10.3969/j.issn.1002-1671.2020.05.032.
[17]	Bäck M, Yurdagul A Jr, Tabas I, et al. Inflammation and its resolution in atherosclerosis: Mediators and therapeutic opportunities[J]. Nat Rev Cardiol, 2019, 16(7):389-406. doi: 10.1038/s41569-019-0169-2.
[18]	Williams JW, Huang LH, Randolph GJ. Cytokine circuits in cardiovascular disease[J]. Immunity, 2019, 50(4):941-954. doi:10.1016/j.immuni.2019.03.007.
[19]	Karbach S, Lagrange J, Wenzel P. Thromboinflammation and vascular dysfunction[J]. Hamostaseologie, 2019, 39(2):180-187. doi:10.1055/s-0038-1676130.
[20]	Engelmann B, Massberg S. Thrombosis as an intravascular effector of innate immunity[J]. Nat Rev Immunol, 2013, 13(1):34-45. doi:10.1038/nri3345.
[21]	D'Alessandro E, Becker C, Bergmeier W, et al. Thrombo-inflammation in cardiovascular disease: An Expert consensus document from the third maastricht consensus conference on thrombosis[J]. Thromb Haemost, 2020, 120(4):538-564. doi:10.1055/s-0040-1708035.
[22]	Pfeffer K. Biological functions of tumor necrosis factor cytokines and their receptors[J]. Cytokine Growth Factor Rev, 2003, 14(3-4):185-191. doi: 10.1016/S1359-6101(03)00022-4.
[23]	Ma X, Yao H, Yang Y, et al. miR-195 suppresses abdominal aortic aneurysm through the TNF-α/NF-κB and VEGF/PI3K/Akt pathway[J]. Int J Mol Med, 2018, 41(4):2350-2358. doi: 10.3892/ijmm.2018.3426.
[24]	Batra R, Suh MK, Carson JS, et al. IL-1β (Interleukin-1β) and TNF-α (Tumor Necrosis Factor-α) impact abdominal aortic aneurysm formation by differential effects on macrophage polarization[J]. Arterioscler Thromb Vasc Biol, 2017, 38(2):457-463. doi: 10.1161/ATVBAHA.117.310333.
[25]	Liu P, Zhang C, Chen J, et al. Combinational therapy of interferon-α and chemotherapy normalizes tumor vasculature by regulating pericytes including the novel marker RGS5 in melanoma.[J]. J Immunother, 2011, 34(3):320-326. doi: 10.1097/CJI.0b013e318213cd12.
[26]	Schrimpf C, Koppen T, Duffield JS, et al. TIMP3 is regulated by pericytes upon shear stress detection leading to a modified endothelial cell response[J]. Eur J Vasc Endovasc Surg, 2017, 54(4):524-533. doi:10.1016/j.jvs.2017.08.037.