国际肿瘤学杂志 ›› 2020, Vol. 47 ›› Issue (11): 686-690.doi: 10.3760/cma.j.cn371439-20200529-00101
收稿日期:
2020-05-29
修回日期:
2020-07-25
出版日期:
2020-11-08
发布日期:
2021-01-06
通讯作者:
宋启斌
E-mail:qibinsong@163.com
Zhang Wen1, Song Qibin1,2(), Hu Weiguo1,2
Received:
2020-05-29
Revised:
2020-07-25
Online:
2020-11-08
Published:
2021-01-06
Contact:
Song Qibin
E-mail:qibinsong@163.com
摘要:
多模态磁共振成像是将多种功能的磁共振成像技术融合的一种新兴颅脑成像技术,具有高精确度、高分辨率及低侵入性的优点,能够从解剖、功能及分子水平更加全面系统地获取脑组织信息。近年来随着磁共振成像技术的不断发展,多模态磁共振技术已广泛用于脑胶质瘤的临床诊疗中。了解多模态磁共振成像技术的原理及其在脑胶质瘤诊断分级、鉴别诊断及预后评估中的应用,有助于临床工作者更好地制定诊疗决策。
张雯, 宋启斌, 胡伟国. 多模态磁共振成像在脑胶质瘤中的临床应用[J]. 国际肿瘤学杂志, 2020, 47(11): 686-690.
Zhang Wen, Song Qibin, Hu Weiguo. Clinical application of multimodal magnetic resonance imaging in glioma[J]. Journal of International Oncology, 2020, 47(11): 686-690.
[1] |
Bush NA, Chang SM, Berger MS. Current and future strategies for treatment of glioma[J]. Neurosurg Rev, 2017,40(1):1-14. DOI: 10.1007/s10143-016-0709-8.
doi: 10.1007/s10143-016-0709-8 pmid: 27085859 |
[2] |
Louis DN, Perry A, Reifenberger G, et al. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary[J]. Acta Neuropathol, 2016,131(6):803-820. DOI: 10.1007/s00401-016-1545-1.
doi: 10.1007/s00401-016-1545-1 pmid: 27157931 |
[3] | Zhang J, Liu H, Tong H, et al. Clinical applications of contrast-enhanced perfusion MRI techniques in gliomas: recent advances and current challenges[J]. Contrast Media Mol Imaging, 2017,2017:1-27. DOI: 10.1155/2017/7064120. |
[4] |
Schmainda KM. Diffusion-weighted MRI as a biomarker for treatment response in glioma[J]. CNS Oncol, 2012,1(2):169-180. DOI: 10.2217/cns.12.25.
doi: 10.2217/cns.12.25 pmid: 23936625 |
[5] |
Sauwen N, Acou M, Van Cauter S, et al. Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI[J]. NeuroImage Clin, 2016,12:753-764. DOI: 10.1016/j.nicl.2016.09.021.
doi: 10.1016/j.nicl.2016.09.021 pmid: 27812502 |
[6] |
Svolos P, Kousi E, Kapsalaki E, et al. The role of diffusion and perfusion weighted imaging in the differential diagnosis of cerebral tumors: a review and future perspectives[J]. Cancer Imaging, 2014,14(1):1-20. DOI: 10.1186/1470-7330-14-20.
doi: 10.1186/1470-7330-14-1 |
[7] |
Potgieser AR, Wagemakers M, van Hulzen AL, et al. The role of diffusion tensor imaging in brain tumor surgery: a review of the literature[J]. Clin Neurol Neurosurg, 2014,124:51-58. DOI: 10.1016/j.clineuro.2014.06.009.
doi: 10.1016/j.clineuro.2014.06.009 pmid: 25016239 |
[8] |
Ma L, Song ZJ. Differentiation between low-grade and high-grade glioma using combined diffusion tensor imaging metrics[J]. Clin Neurol Neurosurg, 2013,115(12):2489-2495. DOI: 10.1016/j.clineuro.2013.10.003.
doi: 10.1016/j.clineuro.2013.10.003 pmid: 24183513 |
[9] | Xu W, Wang Q, Shao A, et al. The performance of MR perfusion-weighted imaging for the differentiation of high-grade glioma from primary central nervous system lymphoma: a systematic review and meta-analysis[J]. PLoS One, 2017,12(3):e173430. DOI: 10.1371/journal.pone.0173430. |
[10] |
Boxerman JL, Shiroishi MS, Ellingson BM, et al. Dynamic susceptibility contrast MR imaging in glioma: review of current clinical practice[J]. Magn Reson Imaging Clin N Am, 2016,24(4):649-670. DOI: 10.1016/j.mric.2016.06.005.
doi: 10.1016/j.mric.2016.06.005 pmid: 27742108 |
[11] |
Shiroishi MS, Castellazzi G, Boxerman JL, et al. Principles of $T_2^*$-weighted dynamic susceptibility contrast MRI technique in brain tumor imaging [J]. J Magn Reson Imaging, 2015,41(2):296-313. DOI: 10.1002/jmri.24648.
doi: 10.1002/jmri.24648 pmid: 24817252 |
[12] |
Chiang GC, Kovanlikaya I, Choi C, et al. Magnetic resonance spectroscopy, positron emission tomography and radiogenomics-relevance to glioma[J]. Front Neurol, 2018,9:33-42. DOI: 10.3389/fneur.2018.00033.
doi: 10.3389/fneur.2018.00033 pmid: 29459844 |
[13] | Aquino D, Gioppo A, Finocchiaro G, et al. MRI in glioma immunotherapy: evidence, pitfalls, and perspectives[J]. J Immunol Res, 2017,2017:1-16. DOI: 10.1155/2017/5813951. |
[14] |
van Dijken BRJ, van Laar PJ, Holtman GA, et al. Diagnostic accuracy of magnetic resonance imaging techniques for treatment response evaluation in patients with high-grade glioma, a systematic review and meta-analysis[J]. Eur Radiol, 2017,27(10):4129-4144. DOI: 10.1007/s00330-017-4789-9.
doi: 10.1007/s00330-017-4789-9 pmid: 28332014 |
[15] |
Suh CH, Kim HS, Jung SC, et al. Diffusion-weighted imaging and diffusion tensor imaging for differentiating high-grade glioma from solitary brain metastasis: a systematic review and Meta-analysis[J]. AJNR Am J Neuroradiol, 2018,39(7):1208-1214. DOI: 10.3174/ajnr.A5650.
doi: 10.3174/ajnr.A5650 pmid: 29724766 |
[16] |
Jakab A, Molnár P, Emri M, et al. Glioma grade assessment by using histogram analysis of diffusion tensor imaging-derived maps[J]. Neuroradiology, 2011,53(7):483-491. DOI: 10.1007/s00234-010-0769-3.
doi: 10.1007/s00234-010-0769-3 |
[17] |
Hilario A, Ramos A, Perez-Nuïez A, et al. The added value of apparent diffusion coefficient to cerebral blood volume in the pre-operative grading of diffuse gliomas[J]. AJNR Am J Neuroradiol, 2012,33(4):701-707. DOI: 10.3174/ajnr.A2846.
doi: 10.3174/ajnr.A2846 pmid: 22207304 |
[18] | Giussani C, Poliakov A, Ferri RT, et al. DTI fiber tracking to differentiate demyelinating diseases from diffuse brain stem glioma[J]. Neuromage, 2010,52(1):217-223. DOI: 10.1016/j.neuro-image.2010.03.079. |
[19] |
Nguyen TB, Cron GO, Perdrizet K, et al. Comparison of the diagnostic accuracy of DSC- and dynamic contrast-enhanced MRI in the preoperative grading of astrocytomas[J]. AJNR Am J Neuroradiol, 2015,36(11):2017-2022. DOI: 10.3174/ajnr.A4398.
doi: 10.3174/ajnr.A4398 pmid: 26228886 |
[20] |
Cebeci H, Aydin O, Ozturk-Isik E, et al. Assesment of perfusion in glial tumors with arterial spin labeling; comparison with dynamic susceptibility contrast method[J]. Eur J Radiol, 2014,83(10):1914-1919. DOI: 10.1016/j.ejrad.2014.07.002.
doi: 10.1016/j.ejrad.2014.07.002 |
[21] |
Rapalino O, Ratai EM. Multiparametric imaging analysis: magnetic resonance spectroscopy[J]. Magn Reson Imaging Clin N Am, 2016,24(4):671-686. DOI: 10.1016/j.mric.2016.06.001.
doi: 10.1016/j.mric.2016.06.001 pmid: 27742109 |
[22] |
Chao ST, Ahluwalia MS, Barnett GH, et al. Challenges with the diagnosis and treatment of cerebral radiation necrosis[J]. Int J Radiat Oncol Biol Phys, 2013,87(3):449-457. DOI: 10.1016/j.ijrobp.2013.05.015.
doi: 10.1016/j.ijrobp.2013.05.015 pmid: 23790775 |
[23] |
Zhang H, Ma L, Wang Q, et al. Role of magnetic resonance spectroscopy for the differentiation of recurrent glioma from radiation necrosis: a systematic review and meta-analysis[J]. Eur J Radiol, 2014,83(12):2181-2189. DOI: 10.1016/j.ejrad.2014.09.018.
doi: 10.1016/j.ejrad.2014.09.018 |
[24] |
Wang S, Martinez-Lage M, Sakai Y, et al. Differentiating tumor progression from pseudoprogression in patients with glioblastomas using diffusion tensor imaging and dynamic susceptibility contrast MRI[J]. AJNR Am J Neuroradiol, 2016,37(1):28-36. DOI: 10.3174/ajnr.A4474.
doi: 10.3174/ajnr.A4474 pmid: 26450533 |
[25] | Patel P, Baradaran H, Delgado D, et al. MR perfusion-weighted imaging in the evaluation of high-grade gliomas after treatment: a systematic review and meta-analysis[J]. Neur Oncol, 2016,19(1):118-127. DOI: 10.1093/neuonc/now148. |
[26] |
Muccio CF, Caranci F, D'Arco F, et al. Magnetic resonance features of pyogenic brain abscesses and differential diagnosis using morphological and functional imaging studies: a pictorial essay[J]. J Neuroradiol, 2014,41(3):153-167. DOI: 10.1016/j.neurad.2014.05.004.
doi: 10.1016/j.neurad.2014.05.004 pmid: 24957685 |
[27] |
Pal D, Bhattacharyya A, Husain M, et al. In vivo proton MR spectroscopy evaluation of pyogenic brain abscesses: a report of 194 cases[J]. AJNR Am J Neuroradiol, 2010,31(2):360-366. DOI: 10.3174/ajnr.A1835.
doi: 10.3174/ajnr.A1835 pmid: 19797788 |
[28] |
Mitsuya K, Nakasu Y, Horiguchi S, et al. Perfusion weighted magnetic resonance imaging to distinguish the recurrence of metastatic brain tumors from radiation necrosis after stereotactic radiosurgery[J]. J Neurooncol, 2010,99(1):81-88. DOI: 10.1007/s11060-009-0106-z.
doi: 10.1007/s11060-009-0106-z pmid: 20058049 |
[29] |
Blasel S, Jurcoane A, Franz K, et al. Elevated peritumoural rCBV values as a mean to differentiate metastases from high-grade gliomas[J]. Acta Neurochir, 2010,152(11):1893-1899. DOI: 10.1007/s00701-010-0774-7.
doi: 10.1007/s00701-010-0774-7 |
[30] |
Parsons DW, Jones S, Zhang X, et al. An integrated genomic analysis of human glioblastoma multiforme[J]. Science, 2008,321(5897):1807-1812. DOI: 10.1126/science.1164382.
doi: 10.1126/science.1164382 pmid: 18772396 |
[31] |
Thust SC, Hassanein S, Bisdas S, et al. Apparent diffusion coefficient for molecular subtyping of non-gadolinium-enhancing WHO grade Ⅱ/Ⅲ glioma: volumetric segmentation versus two-dimensional region of interest analysis[J]. Eur Radiol, 2018,28(9):3779-3788. DOI: 10.1007/s00330-018-5351-0.
doi: 10.1007/s00330-018-5351-0 pmid: 29572636 |
[32] |
Tan WL, Huang WY, Yin B, et al. Can diffusion tensor imaging noninvasively detect IDH1 gene mutations in astrogliomas? A retrospective study of 112 cases[J]. AJNR Am J Neuroradiol, 2014,35(5):920-927. DOI: 10.3174/ajnr.A3803.
doi: 10.3174/ajnr.A3803 pmid: 24557705 |
[33] |
Pope WB, Prins RM, Thomas MA, et al. Non-invasive detection of 2-hydroxyglutarate and other metabolites in IDH1mutant glioma patients using magnetic resonance spectroscopy[J]. J Neurooncol, 2012,107(1):197-205. DOI: 10.1007/s11060-011-0737-8.
doi: 10.1007/s11060-011-0737-8 pmid: 22015945 |
[1] | 刘萍萍, 何学芳, 张翼, 杨旭, 张珊珊, 季一飞. 原发性脑胶质瘤患者术后复发危险因素及预测模型构建[J]. 国际肿瘤学杂志, 2024, 51(4): 193-197. |
[2] | 高新雨, 李振江, 孙洪福, 韩丹, 赵倩, 刘成新, 黄伟. 基于MR加速器的MR引导放疗在食管癌患者中的临床应用[J]. 国际肿瘤学杂志, 2024, 51(1): 37-42. |
[3] | 曾利武, 杜雨强, 张鹏, 陶凯雄. 直肠癌侧方淋巴结转移的影像评估进展[J]. 国际肿瘤学杂志, 2023, 50(4): 248-251. |
[4] | 肖楠, 孙鹏飞. 氧化应激在胶质瘤放化疗敏感性中的研究进展[J]. 国际肿瘤学杂志, 2022, 49(6): 357-361. |
[5] | 孔春禹, 孙鹏飞. SLC7A11与胶质瘤[J]. 国际肿瘤学杂志, 2022, 49(10): 604-607. |
[6] | 张贝, 赵博峰, 王英, 于军, 陈平, 陈宝莹. MRI对乳腺成簇环样强化良恶性病变的诊断价值[J]. 国际肿瘤学杂志, 2021, 48(9): 527-531. |
[7] | 郭世豪, 任叶青, 郭庚. 脑胶质瘤血管生成拟态分子机制[J]. 国际肿瘤学杂志, 2021, 48(6): 362-365. |
[8] | 王宪伟, 史美燕, 王凤芹, 齐福, 王朝喆, 周飞. TSA上调miR-4298靶向抑制PADI4表达在诱导U251细胞凋亡中的作用[J]. 国际肿瘤学杂志, 2021, 48(4): 193-199. |
[9] | 张雯, 胡伟国, 宋启斌. 3D-ASL与DCE-MRI在脑胶质瘤复发与放射性脑坏死鉴别诊断中的价值[J]. 国际肿瘤学杂志, 2021, 48(10): 631-634. |
[10] | 杨明慧, 金风. 3D-ASL、MRS及DTI对鼻咽癌放射性颞叶损伤的诊断及指导治疗价值[J]. 国际肿瘤学杂志, 2020, 47(9): 550-554. |
[11] | 赵聪选, 于韬. 胶质瘤相关基因的挖掘及预测[J]. 国际肿瘤学杂志, 2020, 47(5): 293-296. |
[12] | 王才华, 赵有红, 丰翠, 林照, 杨涟, 葛卫星. 深部软组织弥漫大B细胞淋巴瘤一例[J]. 国际肿瘤学杂志, 2020, 47(5): 319-320. |
[13] | 杨娅, 刘晓萌, 董银萍, 黄伟. 保乳术后放疗瘤床靶区勾画进展[J]. 国际肿瘤学杂志, 2020, 47(2): 103-106. |
[14] | 南阳, 钟跃. 长非编码RNA在神经胶质瘤研究中的新进展[J]. 国际肿瘤学杂志, 2020, 47(2): 98-102. |
[15] | 陈亮, 秦军, 雷军荣, 刘俊, 王璐. miR-1254通过靶向CSF-1抑制胶质瘤细胞的增殖和侵袭能力[J]. 国际肿瘤学杂志, 2020, 47(10): 577-584. |
阅读次数 | ||||||
全文 |
|
|||||
摘要 |
|
|||||