网站首页期刊介绍通知公告编 委 会投稿须知电子期刊广告合作联系我们
最新消息:
磁共振多模态成像在不同级别胶质瘤术后残留中的应用研究
作者:戴峰1  郭震2  张秀明2  乔伟2  白晨光2  徐寒子3  刘念龙2 
单位:1. 南京市第二医院 介入科, 江苏 南京 210008;
2. 江苏省肿瘤医院 CT与MRI室, 江苏 南京 210009;
3. 江苏省肿瘤医院 放疗科, 江苏 南京 210009
关键词:磁共振多模态成像 灌注加权成像 扩散加权成像 氢质子波谱成像 扩散张量成像 神经胶质瘤 分级 残留 
分类号:R739.4;R445.2
出版年·卷·期(页码):2020·39·第五期(584-588)
摘要:

目的:探讨磁共振多模态成像在显示残留灶范围及在胶质瘤分级中的应用。方法:回顾性分析17例高级别胶质瘤术后残留及13例低级别胶质瘤术后残留患者的灌注加权成像(PWI)、弥散加权成像(DWI)、弥散张量成像(DTI)及氢质子波谱成像(1H-MRS)的影像和临床资料。结果:高级别胶质瘤相对脑血容量(rCBV)为2.73±0.27、相对ADC值(rADC)为0.83±0.08,与低级别胶质瘤的1.55±0.34、1.62±0.14比较,差异有统计学意义(P<0.01)。高级别胶质瘤与低级别胶质瘤的相对部分各向异性(rFA)值分别为0.91±0.05和0.91±0.04,Cho/NAA值分别为9.73±10.68和7.11±3.64,差异无统计学意义(P>0.05)。结论:多模态磁共振成像在脑胶质瘤级别判定方面具有较大的诊断价值,可以更加全面完整地显示残留灶的范围。

Objective: To investigate the application of magnetic resonance multi modality imaging in grading and showing residue glioma comprehensive.Methods: Retrospectively analyzed the imaging including perfusion weighted imaging (PWI), diffusion weighted imaging (DWI), 1H-magnetic resonance spectroscopic imaging(1H-MRS) and diffusion tensor imaging (DTI), and clinical data of 17 cases with high grade glioma and 13 cases with low grade glioma all were post-operation.Results: The average relative-cerebral blood volume (rCBV) of high and low grade glioma were 2.73±0.27 and 1.55±0.34, the relative-apparent diffusion coefficient (rADC) value of high and low grade glioma were 0.83±0.08 and 1.62±0.14 respectively, there were statistical difference between them(P<0.01). The Cho/NAA and relative-fractional anisotropy (rFA) value were 9.73±10.68 and 7.11±3.64, 0.91±0.05 and 0.91±0.04 respectively, which showed no significant difference(P>0.05). All the parameters of MRI between tumor and peritumoral area had statistical difference.Conclusion: Magnetic resonance multi modality imaging is valuable in grading glioma, and can comprehensively show the range of residue glioma.

参考文献:

[1] GOODENBERGER M L,JENKINS R B.Genetics of adult glioma[J].Cancer Genet,2012,205(12):613-621.
[2] 惠小波,王彦平,李正明,等.超声造影在判断脑胶质瘤术肿瘤残留的临床价值[J].现代医学,2018,46(2):149-152.
[3] BACK M,RODRIGUEZ M,JAYAMANNE D et al.Understanding the revised fourth edition of the world health organization classification of tumours of the central nervous system (2016) for clinical decision-marking:a guide for oncologist managing patients with glioma[J].Clin Oncol,2018,30(9):556-562.
[4] VANDENBENT M J,WEFEL J S,SCHIFF D,et al.Response assessment in neuro-oncology (a report of the RANO group):assessment of outcome in trials of diffuse low-grade gliomas[J].Lancet Oncol,2011,12(6):583-593.
[5] WEN P Y,MACDONALD D R,REARDON D A,et al.Updated response assessment criteria for high-grade gliomas:response assessment in neuro-oncology working group[J].J Clin Oncol,2010,28(11):1963-1972.
[6] SUH C H,PARK J E,JUNG S C,et al.Amide proton transfer-weighted MRI in distinguishing high-and low-grade gliomas:a systematic review and meta-analysis[J].Neuroradiology,2019,61(5):525-534.
[7] ZHANG S,CHIANG G C,MAGGE R S,et al.Texture analysis on conventional MRI images accurately predicts early malignant transformation of low-grade gliomas[J].Eur Radiology,2019,29(6):2751-2759.
[8] BAI Y,LIN Y,TIAN J,et al.Grading of gliomas by using monoexponential,biexponential,and stretched exponential diffusion-weighted MR imaging and diffusion kurtosis MR imaging[J].Radiology,2016,278(2):496-504.
[9] SHIROISHI M S,CASTELLAZZI G,BOXERMAN J L,et al.Principles of T2*-weighted dynamic susceptibility contrast MRI technique in brain tumor imaging[J].J Magn Reson Imaging,2015,41(2):296-313.
[10] ESSIG M,NGUYEN T B,SHIROISHI M S,et al.Perfusion MRI:the five most frequently asked clinical questions[J].AJR Am J Roentgenol,2013,201(3):495-510.
[11] SAHIN N,MELHEM E R,WANG S,et al.Advanced MR imaging techniques in the evaluation of nonenhancing gliomas:perfusion-weighted imaging compared with proton magnetic resonance spectroscopy and tumor grade[J].Neuroradiol J,2013,26(5):531-541.
[12] ZHANG J,ZHUANG D X,YAO C J et al.Metabolic approach for tumor delineation in glioma surgery:3D MR spectroscopy image-guided resection[J].J Neurosurg,2015,12(4):1-9.
[13] TIAN H L,ZU Y L,WANG C C,et al.Major metabolite levels of preoperative proton magnetic resonance spectroscopy and intraoperative fluorescence intensity in glioblastoma[J].Chin Med Sci J,2017,39(4):511-517.
[14] ANDREISEK G,WHITE L M,KASSNER A,et al.Evaluation of diffusion tensor imaging and fiber tractography of the median nerve:preliminary results on intrasubject variability and precision of measurements[J].AJR Am J Roentgenol,2010,194(1):65-72.
[15] FUDABA H,SHIMOMURA T,ABE T,et al.Comparison of multiple parameters obtained on 3T pulsed arterial spin-labeling,diffusiong tensor imaging,and MRS and the Ki-67 labeling index in evaluating glioma grading[J].AJNR Am J Neuroradiol,2014,35(11):2091-2098.
[16] SERVER A,GRAFF B A,JOSEFSEN R,et al.Analysis of diffusion tensor imaging metrics for gliomas grading at 3T[J].Eur J Radiol,2014,83(3):156-165.
[17] 薛强.恶性胶质瘤术后同期推量调强放疗的疗效及其预后影响因素分析[J].东南大学学报(医学版),2016,35(5):746-751.
[18] MIZUTANI T,MAGOME T,IGAKI H,et al.Optimization of treatment strategy by using a machine learning model to predict survival time of patients with malignant glioma after radiotherapy[J].J Radiat Res,2019,60(6):818-824.

服务与反馈:
文章下载】【发表评论】【查看评论】【加入收藏
提示:您还未登录,请登录!点此登录
您是第 748261 位访问者


 ©《现代医学》编辑部
联系电话:025-83272481;83272479
电子邮件: xdyx@pub.seu.edu.cn

苏ICP备09058541