胶质瘤患者MRI参数Ktrans值和Ve值与血清IL-10、VEGF的交互作用及对脑胶质瘤分级的诊断

doi:10.19854/j.cnki.1008-2425.2024.01.0003

摘要/Abstract

摘要： 目的探讨胶质瘤患者MRI参数容积转运常数(Ktrans)和速率常数(Ve)与血清白细胞介素-10(IL-10)、血管内皮生长因子( VEGF)的交互作用及对脑胶质瘤分级的诊断价值。方法回顾性研究选取2020年10月至2022年10月于我院神经外科接受治疗的120例脑胶质瘤患者为研究组,另选取90例因脑出血而接受开颅手术的患者为对照组。研究组采用MRI动态对比增强扫描获取Ktrans值和Ve值,比较两组患者血清IL-10、VEGF水平。Pearson相关分析Ktrans值和Ve值分别与血清IL-10、VEGF水平的相关性。分析不同脑胶质瘤分级患者Ktrans值和Ve值与血清IL-10、VEGF水平,以及采用ROC曲线分析各指标对脑胶质瘤分级的诊断价值。结果研究组血清IL-10(25.97±7.41 pg/ml 比 14.79±3.37 pg/ml)、VEGF(167.01±34.32 pg/ml 比 90.86±13.64 pg/ml)水平明显高于对照组,差异有统计学意义(P＜0.05)。高级别、低级别患者分别63例、57例,其中高级别患者血清IL-10(30.62±6.22 pg/ml 比 20.97±4.93 pg/ml)、VEGF(191.05±28.61 pg/ml 比 141.22±16.63 pg/ml)水平以及Ktrans值(0.333±0.097 min^-1 比 0.234±0.068 min^-1)和Ve值(0.473±0.136 min^-1 比 0.277±0.091 min^-1)均明显高于低级别患者(P＜0.05)。Pearson相关分析显示,胶质瘤分级与IL-10、VEGF水平以及Ktrans值和Ve值值呈正相关性(r=0.538,0.624,0.502,0.541;P＜0.001),胶质瘤患者血清IL-10、VEGF水平分别与Ktrans值和Ve值呈正相关性(r值分别为0.552、0.695、0.550、0.602;P＜0.05)。血清IL-10、VEGF、Ktrans值和Ve值诊断高级别肿瘤的AUC分别为0.804(0.704~0.905)、0.808(0.717~0.900)、0.793(0.701~0.886)、0.815(0.721~0.909)、0.882(0.810~0.953),其中联合诊断的AUC高于单独诊断(P＜0.05)。结论胶质瘤患者MRI参数Ktrans值和Ve值与血清IL-10、VEGF水平呈正相关性,且对于脑胶质瘤分级具有良好的诊断效能。

关键词: 脑胶质瘤, 肿瘤分级, MRI参数, 白细胞介素-10, 血管内皮生长因子

Abstract: Objective To investigate the interaction of MRI parameters volume transport constant (Ktrans) and rate constant (Ve) with serum interleukin 10 (IL-10) and vascular endothelial growth factor (VEGF) in patients with glioma and their diagnostic value in the grading of glioma. Methods A retrospective study was conducted,120 patients with brain glioma who were treated in neurosurgery of our hospital from October 2020 to October 2022 were selected as the study group,and another 90 patients who underwent craniotomy due to cerebral hemorrhage were selected as the control group.The study group used dynamic contrast-enhanced MRI to obtain the Ktrans value and Ve value,and compared the levels of serum IL-10 and VEGF between the two groups.Pearson correlation analysis showed the correlation between Ktrans value and Ve value and serum IL-10 and VEGF levels,respectively.The Ktrans and Ve values,serum IL-10 and VEGF levels of patients with different grades of glioma were analyzed,and the diagnostic value of each index on the grade of glioma was analyzed by ROC curve. Results The levels of serum IL-10(25.97±7.41 pg/ml 比 14.79±3.37 pg/ml) and VEGF(167.01±34.32 pg/ml vs 90.86±13.64 pg/ml) in the study group were significantly higher than those in the control group (P＜0.05).There were 63 patients with high grade and 57 patients with low grade,and the levels of serum IL-10(30.62±6.22 pg/ml vs 20.97±4.93 pg/ml),VEGF(191.05±28.61 pg/ml vs 141.22±16.63 pg/ml),Ktrans(0.333±0.097 min^-1 vs 0.234±0.068 min^-1) and Ve(0.473±0.136 min^-1 vs 0.277±0.091 min^-1) in high grade patients were significantly higher than those in low grade patients (P＜0.05).Pearson correlation analysis showed that the grade of glioma was positively correlated with the levels of IL-10,VEGF,Ktrans and Ve (r=0.538,0.624,0.502,0.541;P＜0.001),and the serum levels of IL-10,VEGF were positively correlated with Ktrans and Ve (r=0.552,0.695,0.550,0.602;P＜0.05).The AUC of serum IL-10,VEGF,KTrans and Ve values in diagnosis of high-grade tumors were 0.804 (0.704~0.905),0.808 (0.717~0.900),0.793 (0.701~0.886),0.815 (0.721~0.909),0.882 (0.810~0.953),respectively.The AUC of combined diagnosis was higher than that of single diagnosis (P＜0.05). Conclusion The MRI parameters Ktrans and Ve are positively correlated with the serum levels of IL-10 and VEGF in patients with glioma,and have good diagnostic efficacy for the grading of glioma.

Key words: Brain glioma, Tumor grade, MRI parameters, Interleukin-10, Vascular endothelial growth factor

中图分类号:

R739.41 R445.2

王国杰, 刘莹, 韩艳华, 任秀娥, 梁日晶. 胶质瘤患者MRI参数Ktrans值和Ve值与血清IL-10、VEGF的交互作用及对脑胶质瘤分级的诊断[J]. 立体定向和功能性神经外科杂志, 2024, 37(1): 11-16.

Wang Guojie, Liu Ying, Han Yan hua, Ren Xiu'e, Liang Rijing. Interaction of MRI parameters Ktrans and Ve with serum IL-10 and VEGF in patients with glioma and diagnosis of brain glioma grade[J]. Chinese Journal of Stereotactic and Functional Neurosurgery, 2024, 37(1): 11-16.

参考文献

[1] Przybylowski CJ,Hervey-Jumper SL,Sanai N.Surgical strategy for insular glioma[J].J Neurooncol,2021,151(3):491~497.
[2] Bai J,Varghese J,Jain R.Adult Glioma WHO classification update,genomics,and Imaging:what the radiologists need to Know[J].Top Magn Reson Imaging,2020,29(2):71~82.
[3] Van Kempen EJ,Post M,Mannil M,et al.Performance of machine learning algorithms for glioma segmentation of brain MRI:a systematic literature review and meta-analysis[J].Eur Radiol,2021,31(12):9638~9653.
[4] Suh CH,Kim HS,Jung SC,et al.Perfusion MRI as a diagnostic biomarker for differentiating glioma from brain metastasis:a systematic review and meta-analysis[J].Eur Radiol,2018,28(9):3819~3831.
[5] Ni G,Zhang L,Yang X,et al.Targeting interleukin-10 signalling for cancer immunotherapy,a promising and complicated task[J].Hum Vaccin Immunother,2020,16(10):2328~2332.
[6] Siveen KS,Prabhu K,Krishnankutty R,et al.Vascular endothelial growth factor (VEGF) signaling in tumour vascularization:potential and challenges[J].Curr Vasc Pharmacol,2017 15(4):339~351.
[7] 国家卫生健康委员会医政医管局.脑胶质瘤诊疗规范(2018年版)[J].中华神经外科杂志,2019,35(3):217~239.
[8] Leblanc A.A report from the NCI Comparative Brain Tumor Consortium ( CBTC) glioma pathology board:a revised diagnostic classification in support of validation of the canine glioma patient as a model for humans[J].Vet Pathol,2019,56(4):642~643.
[9] Li ZC,Yan J,Zhang S,et al.Glioma survival prediction from whole-brain MRI without tumor segmentation using deep attention network:a multicenter study[J].Eur Radiol,2022,32(8):5719~5729.
[10] Keil VC,Gielen GH,Pintea B,et al.DCE-MRI in Glioma,Infiltration Zone and Healthy Brain to Assess Angiogenesis:A Biopsy Study[J].Clin Neuroradiol,2021,31(4):1049~1058.
[11] 王沛沛,宋曼莉,张文华,等.脑胶质瘤MRI纹理特征的稳健性[J].中国医学影像学杂志,2021,29(5):519~524.
[12] 王大堃,朱建忠,刘辉,等.DCE-MRI测量Ktrans值、Ve值联合ADC值与脑胶质瘤患者MVD及病理分期的相关性[J].中国临床医学影像杂志,2020,6(11):766~769.
[13] 陈鹏,康厚艺,张乐天,等.磁共振动态对比增强不同后处理模型在脑胶质瘤分级中的应用[J].第三军医大学学报,2021,43(23):2577~2583.
[14] 夏喜斌,袁防震,刘军,等.动态对比增强MRI与体素内不相干运动扩散加权成像在鉴别脑胶质瘤真假性进展中的应用[J].实用放射学杂志,2021,37(12):1936~1940,1950.
[15] Sullivan KM,Jiang X,Guha P,et al.Blockade of interleukin 10 potentiates antitumour immune function in human colorectal cancer liver metastases[J].Gut,2023,72(2):325~337.
[16] 赵捷,刘勇,宋震宇,等.动态对比增强MRI定量参数分级诊断胶质瘤:Meta分析[J].中国医学影像技术,2018,34(8):1159~1164.
[17] Malekan M,Ebrahimzaden MA.Vascular Endothelial Growth Factor Receptors [VEGFR] as Target in Breast Cancer Treatment:Current Status in Preclinical and Clinical Studies and Future Directions[J].Curr Top Med Chem,2022,22(11):891~920.
[18] Rallis KS,Corrigan AE,Dadah H,et al.Cytokine-based Cancer Immunotherapy:Challenges and Opportunities for IL-10[J].Anticancer Res,2021,41(7):3247~3252.