Abstract:【Objective】 To investigate the predictive efficacy of quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in the prognosis of glioma. 【Methods】A total of 114 patients with gliomas admitted to The First People's Hospital of Xianyang from February 2017 to February 2020 were examined by DCE-MRI. The quantitative parameters of plasma extracellular space volume transfer constant (Ktrans) and extravascular extracellular space fraction (Ve) were recorded, and the prognosis was evaluated according to the progression free survival (PFS) after adjuvant chemotherapy after glioma resection. The general data of different prognosis, Ktrans and Ve were compared, the influencing factors of glioma prognosis were analyzed by logistic regression, and the predictive value of Ktrans and Ve on prognosis was evaluated by receiver operating characteristic curve (ROC curve). 【Results】Among 114 patients with glioma, 71 had poor prognosis and 43 had good prognosis; The age and high-grade proportion of patients with poor prognosis were greater than those with good prognosis, and KPS score, postoperative radiotherapy proportion and temozolomide use ≥ 4 courses were lower than those with good prognosis (P<0.05); DCE-MRI quantitative parameters Ktrans and Ve in patients with poor prognosis were greater than those in patients with good prognosis (P<0.05). Multivariate logistic regression analysis showed that age, tumor grade, Ktrans, Ve were risk factors for prognosis, KPS score, postoperative radiotherapy, temozolomide use ≥4 courses were protective factors for prognosis (P<0.05). ROC curve analysis showed that the cut off value of DCE-MRI quantitative parameters Ktrans and Ve to predict prognosis was 0.172/min and 0.205, and the AUC value was 0.932 and 0.890. 【Conclusion】 DCE-MRI quantitative parameters Ktrans and Ve are important factors affecting the poor prognosis of patients with glioma, and have important clinical predictive value for prognosis evaluation.
杨毅, 师勇. 动态对比增强扫描MRI定量参数对脑胶质瘤患者预后的预测效能[J]. 医学临床研究, 2022, 39(7): 1068-1071.
YANG Yi, SHI Yong. Predictive Efficacy of Dynamic Contrast-enhanced MRI Quantitative Parameters on the Prognosis of Glioma. JOURNAL OF CLINICAL RESEARCH, 2022, 39(7): 1068-1071.
[1] GUSYATINER O,HEGI M E. Glioma epigenetics: From subclassification to novel treatment options[J].Semin Cancer Biol,2018,51(12):50-58.
[2] 王宁,印弘,康晓伟,等.DCE-MRI定量参数与脑胶质瘤Ki-67标记指数的相关性分析[J].放射学实践,2019,34(4):417-421.
[3] 张永超.DCE-MRI定量参数对脑胶质瘤分级诊断的价值[J].实用临床医学,2020,21(6):47-49.
[4] 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.
[5] MILLER A M,SHAH R H,PENTSOVA E I,et al. Tracking tumour evolution in glioma through liquid biopsies of cerebrospinal fluid[J].Nature,2019,565(7741):654-658.
[6] 龙春琴,周志强,贺文俊,等.CT联合MRI检查在脑胶质瘤术前诊断中的应用研究[J].中国CT和MRI杂志,2020,18(6):9-11.
[7] BAI R,WANG B,JIA Y,et al. Shutter-speed DCE-MRI analyses of human glioblastoma multiforme (GBM) data[J].J Magn Reson Imaging,2020,52(3):850-863.
[8] 徐华,彭东,鲁龙龙.术前MRI增强扫描对脑胶质瘤病理分级诊断及其与微血管密度的相关性[J].中国CT和MRI杂志,2020,18(2):48-50.
[9] 谢录玲,谢春,涂文彬,等.动态增强磁共振成像鉴别诊断胶质瘤复发和放射性脑损伤的临床价值分析[J].中国CT和MRI杂志,2019,17(11):13-15.
[10] LIANG J,LIU D,GAO P,et al. Diagnostic values of DCE-MRI and DSC-MRI for differentiation between high-grade and low-grade gliomas: a comprehensive meta-analysis[J].Acad Radiol,2018,25(3):338-348.
[11] 白顺军,秦丽娟,潘慧丽,等.磁共振成像定量影像学特征用于脑胶质瘤术前分级诊断的价值研究[J].中国医学装备,2019,16(9):75-79.
[12] SU C Q,LU S S,HAN Q Y,et al. Intergrating conventional MRI,texture analysis of dynamic contrast-enhanced MRI,and susceptibility weighted imaging for glioma grading[J].Acta Radiol,2019,60(6):777-787.
[13] 黄鼎祥,艾信平.磁共振动态对比增强联合扩散峰度成像在脑胶质瘤分级中的价值分析[J].医疗卫生装备,2019,40(8):42-45.