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The application progess of magnetic resonance imaging in prognosis of patients with glioblastoma
MA Jie-ling  AI Lin 

DOI:10.3969/j.issn.1674-8034.2015.05.015.


[Abstract] Glioblastoma multiforme (GBM) is the most common form of primary brain cancer and the most malignant neoplasm with predominant astroytic differentiation. The patient with GBM has met the difficulty of complicated treatment, high morbidity and mortality, and short mean lifetime after surgery during the clinic work. There are many influencing factors related to the prognosis. Magnetic resonance imaging (MRI) provides information to assist clinicians in making important decisions of treatment plan, and has been respected in the matter of morphologic analysis before the surgery, supervision and analysis of the effect of treatment. It is considered that MRI can do some prediction of the patients with GBM by using different sequence of MRI with index like scoup of the tumor, necrosis and edema.
[Keywords] Magnetic resonance imaging；Glioblastoma

MA Jie-ling Department of Radiology, Beijng Tiantan Hospital, Capital Medical University, Beijing 100050, China

AI Lin* Department of Radiology, Beijng Tiantan Hospital, Capital Medical University, Beijing 100050, China

*Correspondence to: Ai L, E-mail: ailin.grf@gmail.com

Conflicts of interest   None.

Received  2015-02-09
Accepted  2015-04-16
DOI: 10.3969/j.issn.1674-8034.2015.05.015
DOI:10.3969/j.issn.1674-8034.2015.05.015.

[1]
武春雪，马军．颅外胶质母细胞瘤的影像学检查方法推荐．磁共振成像, 2015, 6(1): 45-49.
[2]
Osborn AG, Salzman KL, Barkovich AJ. Diagnostic Imaging Brain. New York: Lippincott Williams & Wilkins; 2nd ed, 2009: I-6-18, I-6-21.
[3]
Gutman DA, Cooper LA, Hwang SN, et al. MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set1. Radiology, 2013, 5, 267(2): 560-569.
[4]
Lacroix M, Abi-Said D, Fourney DR, et al. A multivariate analysis of 416 patients with glioblastoma multiforme: prognosis, extent of resection, and survival. J Neurosurg, 2001(95): 190-198.
[5]
Tortosa A, Vinolas N, Villa S, et al. Prognostic implication of clinical, radiologic, and pathologic features in patients with anaplastic gliomas. Cancer, 2003, 297(15): 1063-1071.
[6]
Stark AM, Nabavi A, Mehdorn HM, et al. Glioblastoma multiforme: report of 267 cases treated at a single institution. Surgical Neurology, 2005(63): 162-169.
[7]
Verhaak RG, Hoadley KA, Purdom E, et al. An integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR and NF1. Cancer Cell, 2010, 117(1): 98-110.
[8]
Zinn PO, Sathyan P, Mahajan P, et al. A Novel volume-Age-KPS (VAK) glioblastoma classification identifies a prognostic cognate micrornagene signature，PLoS One, 2012, 7(8): e41522.
[9]
Aghi M, Gaviani P, Henson JW, et al. Magnetic resonance imaging characteristics predict epidermal growth factor receptor amplification status in glioblastoma. Clin Cancer Res, 2005, 11: 8600-8605.
[10]
Zinn PO, Majadan B, Sathyan P, et al. Radiogenomic mapping of edema/cellular invasion MRI-phenotypes in glioblastoma multiforme; radiogenomic mapping in glioblastoma multiforme. PLoS One, 2011, 10, 6(10): e25451.
[11]
唐铠，李文斌，江涛．胶质母细胞瘤核磁共振影像学特点和分子病理相关性研究．交通医学, 2014, 28(1): 5-10.
[12]
Pope WB, Sayre J, Perlina A, et al. MR imaging correlates of survival in patients with high-grade gliomas. AJNR Am J Neuroradiol, 2005, 26(10): 2466-2474.
[13]
Jafri NF, Clarke JL, Weinberg V, et al. Relationship of glioblastoma multiforme to the subventricular zone is associated with survival. Neuro Oncol, 2013, 15(1): 91-96.
[14]
Park JK, Hodges T, Arko L, et al. Scale to predict survival after surgery for recurrent glioblastoma multiforme. J Clin Oncol, 2010, 28(24): 3838-3842.
[15]
Kumabe T, Saito R, Kanamori M, et al. Treatment results of glioblastoma during the last 30 years in a single institute. Neurol Med Chir (Tokyo), 2013, 10(53): 786-796.
[16]
Pichler J, Pachinger C, Pelz M, et al. Volumetric measurement of enhanced and FLAIR lesions for evaluation of response and progression: A pilot study. Eur J Radiol, 2013(82): e240-e245.
[17]
Barajas Jr RF, Phillips JJ, Parvataneni R, et al. Regional variation in histopathologic features of tumor specimens from treatment-naive glioblastoma correlates with anatomic and physiologic MR imaging. Neuro Oncol, 2012, 14(7): 942-954.
[18]
Law M, Yang S, Babb JS, et al. Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade. AJNR Am J Neuroradiol, 2004, 25(5): 746-755.
[19]
Carrillo AJ, Lai A, Nghiemphu PL, et al. Relationship between tumor enhancement, edema, idh1 mutational status, MGMT promoter methylation, and survival in glioblastoma. AJNR Am J Neuroradiol, 2012, 8(33): 1349-1355.
[20]
Iliadis G, Kotoula V, Chatzisotiriou A, et al. Volumetric and MGMT parameters in glioblastoma patients: survival analysis. BMC Cancer, 2012, 12: 3.
[21]
Furuta T, Nakada M, Ueda F, et al. Prognostic paradox: brain iamage around the glioblastoma resection cavity. J Neurooncol, 2014, 118(1): 187-192.
[22]
Galbán CJ, Chenevert TL, Meyer CR, et al. Prospective analysis of parametric response map-derived MRI patterns not predicted by standard radiographic assessment biomarkers: identification of early and distinct glioma response. Clin Cancer Res, 2011(17): 4751-4760.
[23]
Kitis O, Altay H, Calli C, et al. Minimum apparent diffusion coefficients in the evaluation of brain tumors. Eur J Radiol, 2005(55): 393-400.
[24]
Chu HH, Choi SH, Ryoo I, et al. Differentiation of true progression from pseudoprogression in glioblastoma treated with radiation therapy and concomitant temozolomide: comparison study of standard and high-b-value diffusion-weighted imaging. Radiology, 2013, 12(269): 831-840.
[25]
Lupo JM, Essock-Burns E, Molinaro AM, et al. Using susceptibility-weighted imaging to determine response to combined antiangiogenic, cytotoxic, and radiation therapy in patients with glioblastoma multiforme. Neuro Oncol, 2013, 15(4): 480-489.
[26]
Matsumura A, Isobe T, Anno I, et al. Correlation between choline and MIB-1 index in human gliomas: a quantitative in proton MR spectroscopy study. J Clin Neurosci, 2005, 12(4): 416-420.
[27]
Zeng QS, Liu HP, Zhang K, et al. Noninvasive evaluation of cerebral glioma grade by using multivoxel 3D proton MR spectroscopy. Magn Reson Imaging, 2011, 29(1): 25-31.
[28]
Ratai EM, Zhang Z, Snyder BS, et al. Magnetic resonance spectroscopy as an early indicator of response to anti-angiogenic therapy in patients with recurrent glioblastoma: RTOG 0625/ACRIN 6677. Neuro Oncol, 2013, 15(7): 936-944.
[29]
Spampinato MV, Schiarelli C, Cianfoni A, et al. Correlation between cerebral blood volume measurements by perfusion-weighted magnetic resonance imaging and two-year progression-free survival in gliomas. J Neuro Radiol, 2013, 26(4): 385-395.
[30]
白雪菲，牛广明，韩晓东，等. PWI和DWI技术在鉴别脑胶质瘤复发与放射性脑损伤中的价值．磁共振成像, 2014, 5(1): 7-10.
[31]
Sugahara T, Korogi Y, Kochi M, et al. Correlation of MR imaging-determined cerebral blood volume maps with histologic and angiographic determination of vascularity of gliomas. AJR Am J Roentgenol, 1998, 171(6): 1479-1486.
[32]
Sanz-Requena R, Revert-Ventura A, Marti-Bonmati A, et al. Quantitative MR perfusion parameters related to survival time in high-grade gliomas. Eur Radiol, 2013(23): 3456-3465.
[33]
Mangla R, Ginat DT, Kamalian S, et al. Correlation between progression free survival and dynamic susceptibility contrast MRI perfusion in WHO grade III glioma subtypes. J Neurooncol, 2014, 116(2): 325-331.
[34]
李军，张雪雁，姜兴岳，等．联合MR扩散张量成像与波谱分析对胶质母细胞瘤放疗前后的评价．磁共振成像, 2014, 5(2): 88-91.
[35]
吴裕强，林祺，兰玉华，等．胶质母细胞瘤多模式MRI表现及其病理组织学基础．磁共振成像, 2013, 4(3):196-200.
[36]
Li WB, Tang K, Chen Q, et al. MRI manifestions correlate with survival of glioblastoma multiforme patients. Cancer Biol Med, 2012, 9(2): 120-123.
[37]
Alexiou GA, Tsiouris S, Kyritsis AP, et al. Assessment of glioma proliferation using imaging modalities. J Clin Neurosci, 2010, (17): 1233-1238.
[38]
Hu LS, Eschbacher JM, Heiserman JE, et al. Reevaluating the imaging definition of tumor progression: perfusion MRI quantifies recurrent glioblastoma tumor fraction, pseudoprogression, and radiation necrosis to predict survival. Neuro Oncol, 2012, 14(7): 919-930.

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