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Research progress on isocitrate dehydrogenase genotype and imaging of glioma
JIANG Jian  ZHANG Xueling  ZHOU Junlin 

Cite this article as: Jiang J, Zhang XL, Zhou JL. Research progress on isocitrate dehydrogenase genotype and imaging of glioma[J]. Chin J Magn Reson Imaging, 2021, 12(5): 103-106. DOI:10.12015/issn.1674-8034.2021.05.025.


[Abstract] Isocitrate dehydrogenase (IDH) is not only one of the important contents of glioma gene diagnosis, but also one of the key factors affecting the treatment and prognosis of glioma patients. A variety of imaging features and radiomic features of MRI imaging, multimodal imaging and radiomics are associated with the phenotype of IDH gene. This article reviews the progress in the study of IDH genotypes and imaging of gliomas.
[Keywords] isocitrate dehydrogenase genotype；glioma；functional magnetic resonance imaging；multi-modal imaging；radiomics

JIANG Jian1, 2, 3   ZHANG Xueling2, 3   ZHOU Junlin2, 3*  

1 Second Clinical school, Lanzhou University, Lanzhou 730030, China

2 Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730030, China

3 Key Laboratory of Medical Imaging of Gansu Province, Lanzhou 730030, China

Zhou JL, E-mail: lzuzjl601@163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS This article is supported by the National Natural Science Found of China (No. 82071872) and Applied basic Research Project of "Cuiying Science and Technology Innovation Plan" in the Lanzhou University second Hospital (No. CY2017-MS03).
Received  2020-12-09
Accepted  2021-03-25
DOI: 10.12015/issn.1674-8034.2021.05.025
Cite this article as: Jiang J, Zhang XL, Zhou JL. Research progress on isocitrate dehydrogenase genotype and imaging of glioma[J]. Chin J Magn Reson Imaging, 2021, 12(5): 103-106. DOI:10.12015/issn.1674-8034.2021.05.025.

1
Molinaro AM, Taylor JW, Wiencke JK, et al. Genetic and molecular epidemiology of adult diffuse glioma[J]. Nat Rev Neurol, 2019, 15(7): 405-417. DOI: 10.1038/s41582-019-0220-2.
2
Cohen A, Sato M, Aldape K, et al. DNA copy number analysis of grade II-III and grade IV gliomas reveals differences in molecular ontogeny including chromothripsis associated with IDH mutation status[J]. Acta Neuropathol Commun, 2015, 20(3): 34. DOI: 10.1186/s40478-015-0213-3.
3
Banan R, Stichel D, Bleck A, et al. Infratentorial IDH-mutant astrocytoma is a distinct subtype[J]. Acta Neuropathol, 2020, 140(4): 569-581. DOI: 10.1007/s00401-020-02194-y.
4
Chen R, Ravindra VM, Cohen AL, et al. Molecular features assisting in diagnosis, surgery, and treatment decision making in low-grade gliomas[J]. Neurosurg Focus, 2015, 38(3): E2. DOI: 10.3171/2015.1.FOCUS14745.
5
Karsy M, Guan J, Cohen AL, et al. New molecular considerations for glioma: IDH, ATRX, BRAF, TERT, H3 K27M[J]. Curr Neurol Neurosci Rep, 2017, 17(2): 19. DOI: 10.1007/s11910-017-0722-5.
6
Smits M, van den Bent MJ. Imaging correlates of adult glioma genotypes[J]. Radiology, 2017, 284(2): 316-331. DOI: 10.1148/radiol.2017151930.
7
Arita H, Kinoshita M, Kawaguchi A, et al. Lesion location implemented magnetic resonance imaging radiomics for predicting IDH and TERT promoter mutations in grade II/III gliomas[J]. Sci Rep, 2018, 8(1): 11773. DOI: 10.1038/s41598-018-30273-4.
8
Villanueva-Meyer JE, Wood MD, Choi BS, et al. MRI features and IDH mutational status of grade II diffuse gliomas: impact on diagnosis and prognosis[J]. AJR Am J Roentgenol, 2018, 210(3): 621-628. DOI: 10.2214/AJR.17.18457.
9
Sonoda Y, Shibahara I, Kawaguchi T, et al. Association between molecular alterations and tumor location and MRI characteristics in anaplastic gliomas[J]. Brain Tumor Pathol, 2015, 32(2): 99-104. DOI: 10.1007/s10014-014-0211-3.
10
Wakimoto H, Tanaka S, Curry WT, et al. Targetable signaling pathway mutations are associated with malignant phenotype in IDH-mutant gliomas[J]. Clin Cancer Res, 2014, 20(11): 2898-909. DOI: 10.1158/1078-0432.CCR-13-3052.
11
Fontebasso AM, Bechet D, Jabado N. Molecular biomarkers in pediatric glial tumors: a needed wind of change[J]. Curr Opin Oncol, 2013, 25(6): 665-673. DOI: 10.1097/CCO.0000000000000007.
12
Sun C, Zhao Y, Shi J, et al. Isocitrate dehydrogenase1 mutation reduces the pericyte coverage of microvessels in astrocytic tumours[J]. J Neurooncol, 2019, 143(2): 187-196. DOI: 10.1007/s11060-019-03156-5.
13
Hewer E, Phour J, Gutt-Will M, et al. TERT promoter mutation analysis to distinguish glioma from gliosis[J]. J Neuropathol Exp Neurol, 2020, 1;79(4): 430-436. DOI: 10.1093/jnen/nlaa004.
14
Ding H, Huang Y, Li Z, et al. Prediction of IDH status through MRI features and enlightened reflection on the delineation of target volume in low-grade gliomas[J]. Technol Cancer Res Treat, 2019, 18: 1533033819877167. DOI: 10.1177/1533033819877167.
15
Juratli TA, Tummala SS, Riedl A, et al. Radiographic assessment of contrast enhancement and T2/FLAIR mismatch sign in lower grade gliomas: correlation with molecular groups[J]. J Neurooncol, 2019, 141(2): 327-335. DOI: 10.1007/s11060-018-03034-6.
16
Hyare H, Rice L, Thust S, et al. Modelling MR and clinical features in grade II/III astrocytomas to predict IDH mutation status[J]. Eur J Radiol, 2019, 114: 120-127. DOI: 10.1016/j.ejrad.2019.03.003.
17
Lasocki A, Anjari M, Ӧrs Kokurcan S, et al. Conventional MRI features of adult diffuse glioma molecular subtypes: a systematic review[J]. Neuroradiology, 2020, 25. DOI: 10.1007/s00234-020-02532-7.
18
Delfanti RL, Piccioni DE, Handwerker J, et al. Imaging correlates for the 2016 update on WHO classification of grade II/III gliomas: implications for IDH, 1p/19q and ATRX status[J]. J Neurooncol, 2017, 135(3): 601-609. DOI: 10.1007/s11060-017-2613-7.
19
Wang X, Chen XZ, Shi L, et al. Glioma grading and IDH1 mutational status: assessment by intravoxel incoherent motion MRI[J]. Clin Radiol, 2019, 74(8): 651.e7-651.e14. DOI: 10.1016/j.crad.2019.03.020.
20
Figini M, Riva M, Graham M, et al. Prediction of isocitrate dehydrogenase genotype in brain gliomas with mri: single-shell versus multishell diffusion models[J]. Radiology, 2018, 289(3): 788-796. DOI: 10.1148/radiol.2018180054.
21
Di Ieva A, Magnussen JS, McIntosh J, et al. Magnetic resonance spectroscopic assessment of isocitrate dehydrogenase status in gliomas: the new frontiers of spectrobiopsy in neurodiagnostics[J]. World Neurosurg, 2020, 133: e421-e427. DOI: 10.1016/j.wneu.2019.09.040.
22
Goryawala M, Saraf-Lavi E, Nagornaya N, et al. The association between whole-brain MR spectroscopy and IDH mutation status in gliomas[J]. J Neuroimaging, 2020, 30(1): 58-64. DOI: 10.1111/jon.12685.
23
von Deimling A, Ono T, Shirahata M, et al. Grading of diffuse astrocytic gliomas: a review of studies before and after the advent of IDH testing[J]. Semin Neurol, 2018, 38(1): 19-23. DOI: 10.1055/s-0038-1636430.
24
Xing Z, Zhang H, She D, et al. IDH genotypes differentiation in glioblastomas using DWI and DSC-PWI in the enhancing and peri-enhancing region[J]. Acta Radiol, 2019, 60(12): 1663-1672. DOI: 10.1177/0284185119842288.
25
Jiang S, Zou T, Eberhart CG, et al. Predicting IDH mutation status in grade II gliomas using amide proton transfer-weighted (APTw) MRI[J]. Magn Reson Med, 2017, 78(3): 1100-1109. DOI: 10.1002/mrm.26820.
26
Paech D, Windschuh J, Oberhollenzer J, et al. Assessing the predictability of IDH mutation and MGMT methylation status in glioma patients using relaxation-compensated multipool CEST MRI at 7.0 T[J]. Neuro Oncol, 2018, 20(12): 1661-1671. DOI: 10.1093/neuonc/noy073.
27
Tan Y, Mu W, Wang XC, et al. Whole-tumor radiomics analysis of DKI and DTI may improve the prediction of genotypes for astrocytomas: a preliminary study[J]. Eur J Radiol, 2020, 124: 108785. DOI: 10.1016/j.ejrad.2019.108785.
28
Chang P, Grinband J, Weinberg BD, et al. Deep-learning convolutional neural networks accurately classify genetic mutations in gliomas[J]. AJNR Am J Neuroradiol, 2018, 39(7): 1201-1207. DOI: 10.3174/ajnr.A5667.
29
Matsui Y, Maruyama T, Nitta M, et al. Prediction of lower-grade glioma molecular subtypes using deep learning[J]. J Neurooncol, 2020, 146(2): 321-327. DOI: 10.1007/s11060-019-03376-9.
30
Zhang HW, Lyu GW, He WJ, et al. DSC and DCE Histogram analyses of glioma biomarkers, including IDH, MGMT, and TERT, on differentiation and survival[J]. Acad Radiol, 2020, 27(12): e263-e271. DOI: 10.1016/j.acra.2019.12.010.
31
Stadlbauer A, Zimmermann M, Kitzwögerer M, et al. MR imaging-derived oxygen metabolism and neovascularization characterization for grading and IDH gene mutation detection of gliomas[J]. Radiology, 2017, 283(3): 799-809. DOI: 10.1148/radiol.2016161422.
32
Kebir S, Weber M, Lazaridis L, et al. Hybrid 11C-MET PET/MRI combined with "machine learning" in glioma diagnosis according to the revised glioma WHO classification 2016[J]. Clin Nucl Med, 2019, 44(3): 214-220. DOI: 10.1097/RLU.0000000000002398.
33
Röhrich M, Loktev A, Wefers AK, et al. IDH-wildtype glioblastomas and grade III/IV IDH-mutant gliomas show elevated tracer uptake in fibroblast activation protein-specific PET/CT[J]. Eur J Nucl Med Mol Imaging, 2019, 46(12): 2569-2580. DOI: 10.1007/s00259-019-04444-y.
34
Thompson CB. Metabolic enzymes as oncogenes or tumor suppressors[J]. N Engl J Med, 2009, 360(8): 813-815. DOI: 10.1056/NEJMe0810213.
35
Michiwaki Y, Hata N, Mizoguchi M, et al. Relevance of calcification and contrast enhancement pattern for molecular diagnosis and survival prediction of gliomas based on the 2016 World Health Organization Classification[J]. Clin Neurol Neurosurg, 2019, 187: 105556. DOI: 10.1016/j.clineuro.2019.105556.

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