|本期目录/Table of Contents|

[1]夏晓亮,夏云宝,陈利华,等.基于MRI特征的脑胶质瘤异柠檬酸脱氢酶1表达预测研究[J].医学研究与战创伤救治(原医学研究生学报),2020,22(3):262-267.[doi:10.3969/j.issn.1672-271X.2020.03.009]
 XIA Xiao-liang,XIA Yun-bao,CHEN Li-hua,et al.The study of correlation between magnetic resonance characteristics and expression of glioma IDH1[J].JOURNAL OF MEDICALRESEARCH —COMBAT TRAUMA CARE,2020,22(3):262-267.[doi:10.3969/j.issn.1672-271X.2020.03.009]
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基于MRI特征的脑胶质瘤异柠檬酸脱氢酶1表达预测研究()

《医学研究与战创伤救治》(原医学研究生学报)[ISSN:1672-271X/CN:32-1713/R]

卷:
第22卷
期数:
2020年3期
页码:
262-267
栏目:
临床研究
出版日期:
2020-05-15

文章信息/Info

Title:
The study of correlation between magnetic resonance characteristics and expression of glioma IDH1
作者:
夏晓亮夏云宝陈利华向定朝耿承军
作者单位:214044无锡,解放军联勤保障部队第九○四医院放射科(夏晓亮、夏云宝、陈利华、向定朝、耿承军)
Author(s):
XIA Xiao-liangXIA Yun-baoCHEN Li-huaXIANG Ding-chaoGENG Cheng-jun
(Department of Radiology,the 904th Hospital of the Joint Logistics Support Force,PLA,Wuxi 214044,Jiangsu,China)
关键词:
胶质瘤异柠檬酸脱氢酶1磁共振成像列线图
Keywords:
gliomaisocitrate dehydrogenase-1magnetic resonance imagingnomogram
分类号:
R446.8
DOI:
10.3969/j.issn.1672-271X.2020.03.009
文献标志码:
A
摘要:
目的利用磁共振特征建立胶质瘤异柠檬酸脱氢酶1(IDH1)突变的预测模型。方法回顾性分析76例术后病理诊断为胶质瘤患者的术前MRI及临床资料,根据免疫组化结果将所有病例分为IDH1突变组与野生组。对2组间影像及临床特征行单变量相关性分析,对有统计学意义的因素行多变量逐步logistic回归并建模,作模型列线图,并采用受试者工作曲线(ROC)、校准曲线及决策曲线对模型进行评价。结果76例患者中IDH1突变组34例,野生型组42例,在单变量分析中,2组间6个影像特征(肿瘤强化、肿瘤边界、肿瘤累及脑叶、肿瘤累及深部白质、瘤周水肿、瘤内坏死或囊变)差异有统计学意义(P<0.05)。多变量逐步logistic回归分析,肿瘤边界、肿瘤累及脑叶、肿瘤累及深部白质、瘤周水肿进入最终模型(P<0.05),ROC曲线(AUC=0.92)、校准曲线及决策曲线(2%<阈值<90%)对模型评估显示模型有较高的预测能力。结论利用MRI特征可建立胶质瘤IDH1突变的预测模型,为临床决策提供参考。
Abstract:
ObjectiveTo establish a predictive model of isocitrate dehydrogenase-1 (IDH1) mutation in glioma using magnetic resonance features.MethodsRetrospective analysis of 76 cases of postoperative pathological diagnosis of glioma patients with preoperative MRI and clinical data. According to the results of immunohistochemistry, all cases were divided into IDH1 mutation group and wild group. Univariate correlation analysis of imaging and clinical features between the two groups, multivariate stepwise logistic regression were performed for statistically significant factors. The model presented as the nomogram and ROC curve. Calibration curve and decision curve were performed to evaluate the model.ResultsIn univariate analysis, there were 6 image features (tumour enhancement; tumour boundary; tumour involve the lobes; tumour involve deep white matter; peritumoral edema; intratumoral necrosis or cystic degeneration) were significantly different (P<0.05). Multivariate stepwise logistic regression analysis showed that tumour boundary, tumour involve the lobes, tumour involve deep white matter and peritumoral edema were included in the final model (P<0.05). The ROC curve (AUC=0.92), calibration curve and decision curve (2%<threshold<90%) were used to evaluate the model, and indicated this model has high prediction ability.ConclusionThe prediction model of IDH1 mutation in glioma is established by using MRIfeatures, which can provide important reference for clinical decision-making.

参考文献/References:

[1]吴志军,张志强,李建瑞,等. 脑多发胶质瘤的磁共振影像特征及鉴别诊断[J]. 医学研究生学报,2019,32(8):828-832.
[2]Weller M,Wick W,Aldape K,et al. Glioma[J]. Nat Rev Dis Primers,2015,1:15017. doi:10.1038/nrdp.2015.17.
[3]吴章泽,王一芳,王正伟,等. 人参皂甙Rh2对人胶质瘤细胞内钙离子浓度的影响[J]. 东南国防医药,2019,21(1):12-16.
[4]Wen PY,Huse JT. 2016 World Health Organization Classification of Central Nervous System Tumors[J]. Continuum (Minneap Minn),2017,23(6,Neuro-oncology):1531-1547.
[5]Hartmann C,Meyer J,Balss J,et al. Type and frequency of IDH1 and IDH2 mutations are related to astrocytic and oligodendroglial differentiation and age:a study of 1,010 diffuse gliomas[J]. Acta Neuropathol,2009,118(4):469-474.
[6]Kickingereder P,Sahm F,Radbruch A,et al. IDH mutation status is associated with a distinct hypoxia/angiogenesis transcriptome signature which is non-invasively predictable with rCBV imaging in human glioma[J]. Sci Rep,2015,5:16238. doi:10.1038/srep16238.
[7]Villa C, Miquel C,Mosses D,et al. The 2016 World Health Organization classification of tumours of the central nervous system[J]. Presse Med,2018,47(11-12 Pt 2):e187-e200.
[8]Leonardi R, Subramanian C, Jackowski S,et al. Cancer-associated isocitrate dehydrogenase mutations inactivate NADPH-dependent reductive carboxylation[J]. J Biol Chem,2012,287(18):14615-14620.
[9]Zhang C,Moore LM,Li X,et al. IDH1/2 mutations target a key hallmark of cancer by deregulating cellular metabolism in glioma[J]. Neuro Oncol,2013,15(9):1114-1126.
[10]Parsons DW, Jones S, Zhang X, et al. An integrated genomic analysis of human glioblastoma multiforme[J]. Science,2008,321(5897):1807-1812.
[11]Kloosterhof NK, Bralten LB, Dubbink HJ,et al. Isocitrate dehydrogenase-1 mutations:a fundamentally new understanding of diffuse glioma?[J] Lancet Oncol,2011,12(1):83-91.
[12]Koivunen P,Lee S, Duncan CG,et al. Transformation by the (R)-enantiomer of 2-hydroxyglutarate linked to EGLN activation[J]. Nature,2012,483(7390):484-488.
[13]Xu W,Yang H,Liu Y,et al. Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of alpha-ketoglutarate-dependent dioxygenases[J]. Cancer Cell,2011,19(1):17-30.
[14]梅东东,龚静山,刘永光,等. 脑胶质瘤IDH基因突变与定量多模态MRI研究进展[J]. 中国医学影像技术,2017,33(10):1550-1553.
[15]Sabha N, Knobbe CB, Maganti M, et al. Analysis of IDH mutation,1p/19q deletion,and PTEN loss delineates prognosis in clinical low-grade diffuse gliomas[J]. Neuro Oncol,2014,16(7):914-923.
[16]杨燕武,谢飞,汤俊佳,等. IDH1基因突变对胶质瘤诊断及预后意义[J]. 中国现代神经疾病杂志,2012,12(6):712-718.
[17]Song TQ, Lei Y,Si G,et al. IDH mutations predict longer survival and response to temozolomide in secondary glioblastoma[J]. Cancer Sci,2012,103(2):269-273.
[18]Nakae S, Murayama K, Sasaki H,et al. Prediction of genetic subgroups in adult supra tentorial gliomas by pre- and intraoperative parameters[J]. J Neurooncol,2017,131(2):403-412.
[19]Lasocki A, Tsui A,Gaillard F,et al. Reliability of noncontrast-enhancing tumor as a biomarker of IDH1 mutation status in glioblastoma[J]. J Clin Neurosci,2017,39:170-175.
[20]Leu K,Ott GA,Lai A,et al. Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II-III diffuse gliomas[J]. 2017,134(1):177-188.
[21]Qi S,Yu L,Li H,et al. Isocitrate dehydrogenase mutation is associated with tumor location and magnetic resonance imaging characteristics in astrocytic neoplasms[J]. Oncol Lett,2014,7(6):1895-1902.
[22]Chen C,Shi Y,Li Y,et al. A glycolysis-based ten-gene signature correlates with the clinical outcome,molecular subtype and IDH1 mutation in glioblastoma[J]. J Genet Genomics,2017,44(11):519-530.
[23]Lee S,Choi SH,Ryoo I,et al. Evaluation of the microenvironmental heterogeneity in high-grade gliomas with IDH1/2 gene mutation using histogram analysis of diffusion-weighted imaging and dynamic-susceptibility contrast perfusion imaging[J]. J Neurooncol,2015,121(1):141-150.

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备注/Memo

备注/Memo:
基金项目:无锡市医学重点人才培育计划(ZDRCPY009)
更新日期/Last Update: 2020-05-15