不同磁共振成像模式判断胶质母细胞瘤预后研究

doi:10.3969/j.issn.1672-6731.2019.11.008

中国现代神经疾病杂志 ›› 2019, Vol. 19 ›› Issue (11): 850-857. doi: 10.3969/j.issn.1672-6731.2019.11.008

2 不同磁共振成像模式判断胶质母细胞瘤预后研究

陈红燕¹, 陈绪珠¹, 茹小娟⁴, 张月青¹, 汪晓鹏¹, 黄伟⁵, 任晓辉², 林松², 李洋³, 吴涛⁶, 刘亚欧¹

1. 100070 首都医科大学附属北京天坛医院放射科;
2. 100070 首都医科大学附属北京天坛医院神经外科;
3. 100070 首都医科大学附属北京天坛医院信息中心;
4. 100070 北京市神经外科研究所;
5. 100062 北京市普仁医院神经外科;
6. 100176 通用电气医疗系统贸易发展(上海)有限公司

收稿日期:2019-11-14 出版日期:2019-11-25 发布日期:2019-11-25
通讯作者: 陈绪珠,Email:radiology888@aliyun.com
基金资助:
国家自然科学基金资助项目（项目编号：81772005）；国家自然科学基金资助项目（项目编号：81771309）；国家自然科学基金资助项目（项目编号：81571632）；国家自然科学基金青年科学基金资助项目（项目编号：81401381）

The comparative study of multimodal MRI techniques in prognosis of glioblastoma

CHEN Hong-yan¹, CHEN Xu-zhu¹, RU Xiao-juan⁴, ZHANG Yue-qing¹, WANG Xiao-peng¹, HUANG Wei⁵, REN Xiao-hui², LIN Song², LI Yang³, WU Tao⁶, LIU Ya-ou¹

1 Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China;
2 Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China;
3 Information Centre, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China;
4 Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China;
5 Department of Neurosurgery, Beijing Puren Hospital, Beijing 100062, China;
6 GE Medical System Trade Development(Shanghai) Limited Company, Shanghai 100176, China

Received:2019-11-14 Online:2019-11-25 Published:2019-11-25
Contact: CHEN Xu-zhu (Email: radiology888@aliyun.com)
Supported by:
This study was supported by the National Natural Science Foundation of China (No. 81772005, 81771309, 81571632) and the National Natural Science Foundation of China for Young Scientists (No. 81401381).

摘要/Abstract

摘要：

目的探讨动态磁敏感增强灌注成像（DSC-MRI）、三维动脉自旋标记（3D-ASL）和体素内不相干运动成像（IVIM）这3种反映肿瘤组织灌注情况的影像学指标对胶质母细胞瘤预后的预测价值。方法纳入2016年8月至2017年10月住院治疗的34例胶质母细胞瘤患者，根据总生存期分为< 14个月组（17例）和≥14个月组（17例），术前行MRI常规扫描，以及DSC-MRI、3D-ASL、IVIM扫描，于肿瘤强化区域和强化肿瘤瘤周区域勾画兴趣区，记录DSC-最大相对脑血容量（rCBV_max）值和相对脑血流量（rCBF）值、ASL-脑血流量（CBF）值、IVIM-灌注分数（PF）值，绘制受试者工作特征曲线（ROC曲线）评价各项影像学指标对判断预后的参考价值。结果在肿瘤强化区域，总生存期< 14个月组与≥ 14个月组患者ASL-CBF值、IVIM-PF值、DSC-rCBF值、DSC-rCBV_max值差异无统计学意义（均P>0.05）；在强化肿瘤瘤周区域，总生存期< 14个月组患者IVIM-PF值低于（P=0.011）、DSC-rCBF值（P=0.009）和DSC-rCBV_max值（P=0.012）高于≥ 14个月组。绘制强化肿瘤瘤周区域ASL-CBF值、DSC-rCBF值和DSC-rCBV_max值的ROC曲线，曲线下面积分别为0.579（95% CI：0.372~0.787，P=0.453）、0.763（95% CI：0.588~0.937，P=0.013）和0.746（95% CI：0.565~0.926，P=0.020），提示DSC-rCBF值和DSC-rCBV_max值对预后判断的参考价值更佳。结论 DSC-rCBF值和DSC-rCBV_max值对胶质母细胞瘤的预后判断的参考价值更佳，而ASL和IVIM序列未显示出较好的预后判断价值。

关键词: 胶质母细胞瘤, 磁共振成像, 预后

Abstract:

Objective To investigate the prognostic value of dynamic susceptibility contrast-enhanced MRI (DSC-MRI), 3D-arterial spin labeling (3D-ASL) and intravoxel incoherentmotion (IVIM) in glioblastoma. Methods From August 2016 to October 2017, a total of 34 patients with glioblastoma were enrolled. According to the overall survival (OS), they were divided into < 14 months group (17 cases) and ≥ 14 months group (17 cases). MRI conventional sequences, DSC-MRI, 3D-ASL, IVIM were acquired before operation. Multiple regions of interest (ROIs) were placed in the tumor-enhanced region and the peritumoral region, and recorded the values of DSC-maximum relative cerebral blood volume (DSC-rCBV_max) and relative cerebral blood flow (DSC-rCBF), ASL-cerebral blood flow (ASL-CBF), IVIM-perfusion fraction (PF). Receiver operating characteristic (ROC) curve was used to evaluated the prognostic value of the imaging indicators. Results There were no significant differences in ASL-CBF, IVIM-PF, DSC-rCBF and DSC-rCBV_max between the OS < 14 months group and the OS ≥ 14 months group in tumor-enhanced region (P>0.05, for all). In the peritumoral region, the IVIM-PF of the patients in OS < 14 months was lower (P=0.011) while DSC-rCBF (P=0.009) and DSC-rCBV_max (P=0.012) were higher than OS ≥ 14 months group. The area under the ROC curve was 0.579 (95% CI:0.372-0.787, P=0.453), 0.763 (95% CI:0.588-0.937, P=0.013) and 0.746 (95% CI:0.565-0.926, P=0.020) respectively, suggesting that DSC-rCBF and DSC-rCBV_max have better reference value for prognosis. Conclusions The imaging indicators of DSC-MRI have an effect on the OS of glioblastoma, while IVIM and ASL have not shown an effect on overall survival.

Key words: Glioblastoma, Magnetic resonance imaging, Prognosis

陈红燕, 陈绪珠, 茹小娟, 张月青, 汪晓鹏, 黄伟, 任晓辉, 林松, 李洋, 吴涛, 刘亚欧. 不同磁共振成像模式判断胶质母细胞瘤预后研究[J]. 中国现代神经疾病杂志, 2019, 19(11): 850-857.

CHEN Hong-yan, CHEN Xu-zhu, RU Xiao-juan, ZHANG Yue-qing, WANG Xiao-peng, HUANG Wei, REN Xiao-hui, LIN Song, LI Yang, WU Tao, LIU Ya-ou. The comparative study of multimodal MRI techniques in prognosis of glioblastoma[J]. Chinese Journal of Contemporary Neurology and Neurosurgery, 2019, 19(11): 850-857.

http://journal11.magtechjournal.com/cjcnn/CN/Y2019/V19/I11/850

参考文献

[1] Ostrom QT, Gittleman H, Fulop J, Liu M, Blanda R, Kromer C, Wolinsky Y, Kruchko C, Barnholtz-Sloan JS. CBTRUS statistical report:primary brain and central nervous system tumors diagnosed in the united states in 2008-2012[J]. Neuro Oncal, 2015, 17 Suppl 4:iv1-62.
[2] Ostrom QT, Bauchet L, Davis FG, Deltour I, Fisher JL, Langer CE, Pekmezci M, Schwartzbaum JA, Turner MC, Walsh KM, Wrensch MR, Barnholtz-Sloan JS. The epidemiology of glioma in adults:a "state of the science" review[J]. Neuro Oncol, 2014, 16:896-913.
[3] Sharma S, Sharma MC, Sarkar C. Morphology of angiogenesis in human cancer:a conceptual overview, histoprognostic perspective and significance of neoangiogenesis[J]. Histopathology, 2005, 46:481-489.
[4] Chen L, Lin ZX, Lin GS, Zhou CF, Chen YP, Wang XF, Zheng ZQ. Classification of microvascular patterns via cluster analysis reveals their prognostic significance in glioblastoma[J]. Hum Pathol, 2015, 46:120-128.
[5] Jain R, Poisson L, Narang J, Gutman D, Scarpace L, Hwang SN, Holder C, Wintermark M, Colen RR, Kirby J, Freymann J, Brat DJ, Jaffe C, Mikkelsen T. Genomic mapping and survival prediction in glioblastoma:molecular subclassification strengthened by hemodynamic imaging biomarkers[J]. Radiology, 2013, 267:212-220.
[6] Jain R, Poisson LM, Gutman D, Scarpace L, Hwang SN, Holder CA, Wintermark M, Rao A, Colen RR, Kirby J, Freymann J, Jaffe CC, Mikkelsen T, Flanders A. Outcome prediction in patients with glioblastoma by using imaging, clinical, and genomicbiomarkers:focus on the nonenhancing component of the tumor[J]. Radiology, 2014, 272:484-493.
[7] Liu X, Mangla R, Tian W, Qiu X, Li D, Walter KA, Ekholm S, Johnson MD. The preliminary radiogenomics association between MR perfusion imaging parameters and genomic biomarkers, and their predictive performance of overall survival in patients with glioblastoma[J]. J Neurooncol, 2017, 135:553-560.
[8] Liang TT, Zhang H, Wang XC, Tan Y, Qin JB, Wang L, Zhang L. Prognostic value of preoperative dynamic susceptibility contrast-enhanced MR imaging in patients with gliomas[J]. Ci Gong Zhen Cheng Xiang, 2018, 9:406-410.[梁甜甜,张辉,王效春,谭艳,秦江波,王乐,张磊.术前动态磁敏感对比增强MR灌注加权成像在脑胶质瘤预后评估中的价值研究[J].磁共振成像, 2018, 9:406-410.]
[9] Liu T, Cheng G, Kang X, Xi Y, Zhu Y, Wang K, Sun C, Ye J, Li P, Yin H. Noninvasively evaluating the grading and IDH1 mutation status of diffuse gliomas by three-dimensional pseudo-continuous arterial spin labeling and diffusion-weighted imaging[J]. Neuroradiology, 2018, 60:693-702.
[10] Pope WB, Prins RM, Albert Thomas M, Nagarajan R, Yen KE, Bittinger MA, Salamon N, Chou AP, Yong WH, Soto H, Wilson N, Driggers E, Jang HG, Su SM, Schenkein DP, Lai A, Cloughesy TF, Kornblum HI, Wu H, Fantin VR, Liau LM. Non-invasive detection of 2-hydroxyglutarate and other metabolites in IDH1 mutant glioma patients using magnetic resonance spectroscopy[J]. J Neurooncol, 2012, 107:197-205.
[11] Tan W, Xiong J, Huang W, Wu J, Zhang S, Geng D. Noninvasively detecting isocitrate dehydrogenase 1 gene status in astrocytoma by dynamic susceptibility contrast MRI[J]. J Magn Reson Imaging, 2017, 45:492-499.
[12] Tan W, Huang WY, Yin B, Xiong J, Wu JS, Geng DY. Can diffusion tensor imaging noninvasively detect IDH1 gene mutations in astrogliomas:a retrospective study of 112 cases[J]?AJNR Am J Neuroradiol, 2014, 35:920-927.
[13] Hempel JM, Bisdas S, Schittenhelm J, Brendle C, Bender B, Wassmann H, Skardelly M, Tabatabai G, Vega SC, Ernemann U, Klose U. In vivo molecular profiling of human glioma using diffusion kurtosis imaging[J]. J Neurooncol, 2017, 131:93-101.
[14] Jiang S, Zou T, Eberhart CG, Villalobos MA, Heo HY, Zhang Y, Wang Y, Wang X, Yu H, Du Y, van Ziji PC, Wen Z, Zhou J. Predicting IDH mutation status in grade Ⅱ gliomas using amide proton transfer-weighted (APTw) MRI[J]. Magn Reson Med, 2017, 78:1100-1109.
[15] Xiao HF, Chen ZY, Lou X, Wang YL, Gui QP, Wang Y, Shi KN, Zhou ZY, Zheng DD, Wang DJ, Ma L. Astrocytic tumour grading:a comparative study of three-dimensional pseudocontinuous arterial spin labelling, dynamic susceptibility contrast-enhanced perfusion-weighted imaging, and diffusion-weighted imaging[J]. Eur Radiol, 2015, 25:3423-3430.
[16] Wen Y, Dai JP, Gao PY, Ai L, Chen HY. Comparison of arterial spin labeling and dynamic susceptibility-weighted contrast-enhanced MR imaging in grading of brain gliomas[J]. Zhonghua Fang She Xue Za Zhi, 2007, 41:363-365.[温洋,戴建平,高培毅,艾林,陈红燕. MR动脉质子自旋标记与动态磁敏感对比增强灌注技术在脑胶质瘤分级中的价值[J].中华放射学杂志, 2007, 41:363-365.]
[17] Yip S, Iafrate AJ, Louis DN. Molecular diagnostic testing in malignant gliomas:a practical update on predictive markers[J]. J Neuropathol Exp Neurol, 2008, 67:1-15.
[18] Radiology Quality and Safety Group, Chinese Medical Association; Radiology MR Group, Chinese Medical Association. Recommended clinical application of aterial spin labeling MRI:an expert consensus[J]. Zhonghua Fang She Xue Za Zhi, 2016, 50:817-824.[中华医学会放射学分会质量管理与安全管理学组,中华医学会放射学分会磁共振学组.动脉自旋标记脑灌注MRI技术规范化应用专家共识[J].中华放射学杂志, 2016, 50:817-824.]
[19] Cha S, Johnson G, Wadghiri YZ, Jin O, Babb J, Zagzag D, Turnbull DH. Dynamic, contrast-enhanced perfusion MRI in mouse gliomas:correlation with histopathology[J]. Magn Reson Med, 2003, 49:848-855.
[20] Ningning D, Haopeng P, Xuefei D, Wenna C, Yan R, Jingsong W, Chengjun Y, Zhenwei Y, Xiaoyuan F. Perfusion imaging of brain gliomas using arterial spin labeling:correlation with histopathological vascular density in MRI-guided biopsies[J]. Neuroradiology, 2017, 59:51-59.
[21] Federau C, Meuli R, O'Brien K, Maeder P, Hagmann P. Perfusion measurement in brain gliomas with intravoxel incoherent motion MRI[J]. AJNR Am J Neuroradiol, 2014, 35:256-262.
[22] Federau C, Maeder P, O'Brien K, Browaeys P, Meuli R, Hagmann P. Quantitative measurement of brain perfusion with intravoxel incoherent motion MR imaging[J]. Radiology, 2012, 265:874-881.
[23] Wang CC, Dong HB, Ding F, Li YD, Wang GY, Ding HX. Quantitative evaluation of intravoxel incoherent motion diffusion-weighted imaging and three-dimensional arterial spin labeling in Ki-67 labeling index and grading of brain gliomas[J]. Zhonghua Yi Xue Za Zhi, 2019, 99:338-342.[王超超,董海波,丁方,李亚迪,王高燕,丁华新.体素内不相干运动扩散加权成像和三维动脉自旋标记成像评估脑胶质瘤Ki-67标记指数和分级的价值[J].中华医学杂志, 2019, 99:338-342.]
[24] Rau MK, Braun C, Skardelly M, Schittenhelm J, Paulsen F, Bender B, Ernemann U, Bisdas S. Prognostic value of blood flow estimated by arterial spin labeling and dynamic susceptibility contrast-enhanced MR imaging in high-grade gliomas[J]. J Neurooncol, 2014, 120:557-566.
[25] Elson A, Bovi J, Siker M, Schultz C, Paulson E. Evaluation of absolute and normalized apparent diffusion coefficient (ADC) values within the post-operative T₂/FLAIR volume as adverse prognostic indicators in glioblastoma[J]. J Neurooncol, 2015, 122:549-558.
[26] Federau C, Cerny M, Roux M, Mosimann PJ, Maeder P, Meuli R, Wintermark M. IVIM perfusion fraction is prognostic for survival in brain glioma[J]. Clin Neuroradiol, 2017, 27:485-492.
[27] National Comprehensive Cancer Network. NCCN clinical practice guidelines in oncology:central nervous system cancers[DB/OL]. 2016[2019-09-20]. http://www.nccn.org/professionals/physician_gls/default.aspx
[28] Jiang HH, Ren XH, Cui Yong, Li MX, Yang KY, Lei YF, Lin S. Clinical prognostic factors of adult supratentorial glioblastoma[J]. Zhonghua Wai Ke Za Zhi, 2019, 57:377-382.[蒋海辉,任晓辉,崔勇,李铭孝,杨凯元,雷逸斐,林松.成人幕上脑胶质母细胞瘤患者临床预后因素研究[J].中华外科杂志, 2019, 57:377-382.]
[29] Society for Neuro-Oncology of China, Neuro-Tumor Branch of Shanghai Anticancer Association. Expert consensus on Chinese central nervous system glioma immunization and targeted therapy[J]. Zhonghua Yi Xue Za Zhi, 2018, 98:324-331.[中国医师协会脑胶质瘤专业委员会,上海市抗癌协会神经肿瘤分会.中国中枢神经系统胶质瘤免疫和靶向治疗专家共识[J].中华医学杂志, 2018, 98:324-331.]
[30] Brandão LA, Shiroishi MS, Law M. Brain tumors:a multimodality approach with diffusion-weighted imaging, diffusion tensorimaging, magnetic resonance spectroscopy, dynamic susceptibility contrast and dynamiccontrast-enhanced magnetic resonance imaging[J]. Magn Reson Imaging Clin N Am, 2013, 21:199-239.
[31] Mangla R, Kolar B, Zhu T, Zhong J, Almast J, Ekholm S. Percentage signal recovery derived from MR dynamic susceptibility contrast imaging is useful to differentiate common enhancing malignant lesions of the brain[J]. AJNR Am J Neuroradiol, 2011, 32:1004-1010.
[32] Law M, Cha S, Knopp EA, Johnson G, Arnett J, Litt AW. High-grade gliomas and solitary metastases:differentiation by using perfusion and proton spectroscopic MR imaging[J]. Radiology, 2002, 222:715-721.
[33] Wang S, Kim S, Chawla S, Wolf RL, Knipp DE, Vossough A, O'Rourke DM, Judy KD, Poptani H, Melhem ER. Differentiation between glioblastomas, solitary brain metastases, and primary cerebral lymphomas using diffusion tensor and dynamic susceptibility contrast-enhanced MR imaging[J]. AJNR Am J Neuroradiol, 2011, 32:507-514.
[34] Zhao K, Wang XY. Viewpoint and interpretation of 2017 EMA's restrictions on the use of gadolinium contrast agents in MR contrast enhanced scanning[J]. Fang She Xue Shi Jian, 2018, 33:10-12.[赵凯,王霄英. 2017 EMA对MR增强扫描钆对比剂使用限制的观点及解读[J].放射学实践, 2018, 33:10-12.]
[35] Tang M, Wu JL. Prestnt status and progress of MRI study on gadolinium contrast agent deposition in the brain[J]. Zhonghua Fang She Xue Za Zhi, 2018, 52:971-973.[汤敏,伍建林.脑内钆对比剂沉积MRI研究现状[J].中华放射学杂志, 2018, 52:971-973.]
[36] Liao HB, Xiao XL, Dai ZQ, Liu ZH, Yu JH, Wang ZQ, Jin WJ, Wu L, Shen XL, Wang JH. A study of 3.0 TMR3D-PCASL in microperfusion of brain gliomas[J]. Shi Yong Fang She Xue Za Zhi, 2016, 32:441-444.[廖海波,肖新兰,戴中强,刘征华,于建华,王志强,金文晶,吴雷,沈晓黎,汪建华. 3.0 TMR3D-PCASL技术在脑胶质瘤微灌注研究[J].实用放射学杂志, 2016, 32:441-444.]

选择文件类型/文献管理软件名称

选择包含的内容

2 不同磁共振成像模式判断胶质母细胞瘤预后研究

The comparative study of multimodal MRI techniques in prognosis of glioblastoma

RichHTML

PDF

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	任修德, 李涛, 范吉康, 王希森, 贾晓丹, 杨学军. 胶质母细胞瘤FGFR3-TACC3融合基因介导丙酮酸激酶M2入核促进DNA损伤修复基础研究[J]. 中国现代神经疾病杂志, 2023, 23(8): 745-757.
[2]	刘俊其, 王蠡, 王振霖, 张秋航, 齐岩, 危维. 内镜下经口鼻联合入路手术切除颅底脊索瘤[J]. 中国现代神经疾病杂志, 2023, 23(7): 580-585.
[3]	潘希娟, 邢英琦, 刘玉梅. 脑小血管病影像学评分方法[J]. 中国现代神经疾病杂志, 2023, 23(7): 633-637.
[4]	张磊, 张涛. 脑电双频指数与自发性脑出血患者预后相关性分析[J]. 中国现代神经疾病杂志, 2023, 23(6): 515-521.
[5]	刘臣超, 刘慧权, 袁小勇, 王健, 陈绅, 王义义, 柳兴军. 重症结核性脑膜炎预后不良影响因素分析[J]. 中国现代神经疾病杂志, 2023, 23(6): 522-529.
[6]	邵暇荔, 张泳, 金莉蓉, 王剑. 震颤为主型帕金森病与特发性震颤患者脑灌注对比分析[J]. 中国现代神经疾病杂志, 2023, 23(6): 542-548.
[7]	刘智强, 陈金桃, 唐文龙, 翁超群, 张金锋, 林志雄. Dandy-Walker综合征患儿腹腔分流术前后临床与影像学特征分析[J]. 中国现代神经疾病杂志, 2023, 23(5): 433-438.
[8]	姚莉萍, 王睿晗, 包翌, 蔡瀚林, 陈芹. 后部皮质萎缩临床及影像学特征分析[J]. 中国现代神经疾病杂志, 2023, 23(4): 326-334.
[9]	葛懿, 陈聪, 王爽, 丁瑶. 7T超高场强MRI在耐药性癫痫诊断与治疗中的应用进展[J]. 中国现代神经疾病杂志, 2023, 23(3): 161-166.
[10]	耿雨梅, 李存, 李慧敏, 王梦莹, 康慧聪. 伴癫痫发作的自身免疫性脑炎临床特征分析[J]. 中国现代神经疾病杂志, 2023, 23(3): 205-213.
[11]	刘敏婷, 戴利军, 张振斌, 邵媛, 赖名耀, 张笑坛. 转化生长因子-β联合CD3⁺、CD4⁺、CD8⁺T细胞检测胶质母细胞瘤免疫微环境初探[J]. 中国现代神经疾病杂志, 2023, 23(3): 247-253.
[12]	李建瑞, 刘宵雪, 许强, 骆仲强, 卢光明, 张志强. 扩散峰度成像直方图联合EphA2分级在胶质瘤分级诊断中的价值[J]. 中国现代神经疾病杂志, 2023, 23(3): 254-263.
[13]	孙梦凡, 姜季委, 王艳丽, 张源, 徐俊. 动脉自旋标记测定脑血流量在阿尔茨海默病研究中的进展[J]. 中国现代神经疾病杂志, 2023, 23(1): 29-34.
[14]	于宁波, 游煜根, 王鸿鹏, 秦岩丁, 梁思泉, 韩建达. 机器人辅助神经介入手术研究进展[J]. 中国现代神经疾病杂志, 2023, 23(1): 45-52.
[15]	刘雪菲, 王佳伟. 视神经炎合并慢性乙型肝炎病毒感染临床分析[J]. 中国现代神经疾病杂志, 2022, 22(9): 770-776.

模态框（Modal）标题

选择文件类型/文献管理软件名称

选择包含的内容

2 不同磁共振成像模式判断胶质母细胞瘤预后研究

The comparative study of multimodal MRI techniques in prognosis of glioblastoma

RichHTML

PDF

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价