Abstract
In 2016, the World Health Organization (WHO) updated its brain tumor classification system to recognize the importance of key genetic alterations in glioma, incorporating these features into the definitions of a variety of brain tumors for the first time. Several of these genetic alterations, such as IDH mutation and 1p/19q codeletion, can be assessed at imaging, with approaches including visual inspection, advanced MR and PET techniques, and machine learning reported in the literature. Reliable noninvasive assessment of these genetic features by imaging may allow for improved treatment planning and patient counseling, and an understanding of how the various genetically defined tumor types respond to therapy is useful in interpretation of post-treatment imaging. In the future, the importance of genetic features in glioma diagnosis and treatment will only increase, and it is incumbent upon neuroradiologists to stay abreast of these developments in order to provide optimal patient care.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Louis DN, Ohgaki H, Wiestler OD, Cavenee WK. World Health Organization histological classification of tumours of the central nervous system. Lyon: International Agency for Research on Cancer; 2007.
Louis DN, Perry A, Burger P, Ellison DW, Reifenberger G, von Deimling A, et al. International Society of Neuropathology–Haarlem consensus guidelines for nervous system tumor classification and grading. Brain Pathol. 2014;24(5):429–35.
Hartmann C, Hentschel B, Wick W, Capper D, Felsberg J, Simon M, et al. Patients with IDH1 wild type anaplastic astrocytomas exhibit worse prognosis than IDH1-mutated glioblastomas, and IDH1 mutation status accounts for the unfavorable prognostic effect of higher age: implications for classification of gliomas. Acta Neuropathol. 2010;120(6):707–18.
Watanabe T, Nobusawa S, Kleihues P, Ohgaki H. IDH1 mutations are early events in the development of astrocytomas and oligodendrogliomas. Am J Pathol. 2009;174(4):1149–53.
Beiko J, Suki D, Hess KR, Fox BD, Cheung V, Cabral M, et al. IDH1 mutant malignant astrocytomas are more amenable to surgical resection and have a survival benefit associated with maximal surgical resection. Neuro-Oncology. 2014;16(1):81–91.
Vogelbaum MA. Towards a genomic definition of completeness of resection? Neuro-Oncology. 2014;16(1):2–3.
Yamashita K, Hiwatashi A, Togao O, Kikuchi K, Hatae R, Yoshimoto K, et al. MR imaging-based analysis of glioblastoma multiforme: estimation of IDH1 mutation status. AJNR Am J Neuroradiol. 2016;37(1):58–65.
Carrillo JA, Lai A, Nghiemphu PL, Kim HJ, Phillips HS, Kharbanda S, et al. Relationship between tumor enhancement, edema, IDH1 mutational status, MGMT promoter methylation, and survival in glioblastoma. AJNR Am J Neuroradiol. 2012;33(7):1349–55.
Lee S, Choi SH, Ryoo I, Yoon TJ, Kim TM, Lee SH, et al. Evaluation of the microenvironmental heterogeneity in high-grade gliomas with IDH1/2 gene mutation using histogram analysis of diffusion-weighted imaging and dynamic-susceptibility contrast perfusion imaging. J Neuro-Oncol. 2015;121(1):141–50.
Pope WB, Prins RM, Albert Thomas M, Nagarajan R, Yen KE, Bittinger MA, et al. Non-invasive detection of 2-hydroxyglutarate and other metabolites in IDH1 mutant glioma patients using magnetic resonance spectroscopy. J Neuro-Oncol. 2012;107(1):197–205.
de la Fuente MI, Young RJ, Rubel J, Rosenblum M, Tisnado J, Briggs S, et al. Integration of 2-hydroxyglutarate-proton magnetic resonance spectroscopy into clinical practice for disease monitoring in isocitrate dehydrogenase-mutant glioma. Neuro-Oncology. 2016;18(2):283–90.
Pepin KM, McGee KP, Arani A, Lake DS, Glaser KJ, Manduca A, et al. MR elastography analysis of glioma stiffness and IDH1-mutation status. AJNR Am J Neuroradiol. 2018;39(1):31–6.
Chitneni SK, Yan H, Zalutsky MR. Synthesis and evaluation of a (18)F-labeled triazinediamine analogue for imaging mutant IDH1 expression in gliomas by PET. ACS Med Chem Lett. 2018;9(7):606–11.
Aibaidula A, Chan AK, Shi Z, Li Y, Zhang R, Yang R, et al. Adult IDH wild-type lower-grade gliomas should be further stratified. Neuro-Oncology. 2017;19(10):1327–37.
Cairncross G, Wang M, Shaw E, Jenkins R, Brachman D, Buckner J, et al. Phase III trial of chemoradiotherapy for anaplastic oligodendroglioma: long-term results of RTOG 9402. J Clin Oncol. 2013;31(3):337–43.
Buckner JC, Shaw EG, Pugh SL, Chakravarti A, Gilbert MR, Barger GR, et al. Radiation plus procarbazine, CCNU, and vincristine in low-grade glioma. N Engl J Med. 2016;374(14):1344–55.
Villanueva-Meyer JE, Wood MD, Choi BS, Mabray MC, Butowski NA, Tihan T, et al. MRI features and IDH mutational status of grade II diffuse gliomas: impact on diagnosis and prognosis. AJR Am J Roentgenol. 2018;210(3):621–8.
Johnson DR, Diehn FE, Giannini C, Jenkins RB, Jenkins SM, Parney IF, et al. Genetically defined oligodendroglioma is characterized by indistinct tumor borders at MRI. AJNR Am J Neuroradiol. 2017;38:678.
Patel SH, Poisson LM, Brat DJ, Zhou Y, Cooper L, Snuderl M, et al. T2-FLAIR mismatch, an imaging biomarker for IDH and 1p/19q status in lower-grade gliomas: a TCGA/TCIA project. Clin Cancer Res. 2017;23(20):6078–85.
Gajjar A, Pfister SM, Taylor MD, Gilbertson RJ. Molecular insights into pediatric brain tumors have the potential to transform therapy. Clin Cancer Res. 2014;20(22):5630–40.
Solomon DA, Wood MD, Tihan T, Bollen AW, Gupta N, Phillips JJ, et al. Diffuse midline gliomas with histone H3-K27M mutation: a series of 47 cases assessing the spectrum of morphologic variation and associated genetic alterations. Brain Pathol. 2016;26(5):569–80.
Meyronet D, Esteban-Mader M, Bonnet C, Joly MO, Uro-Coste E, Amiel-Benouaich A, et al. Characteristics of H3 K27M-mutant gliomas in adults. Neuro-Oncology. 2017;19(8):1127–34.
Gardiman MP, Fassan M, Orvieto E, D’Avella D, Denaro L, Calderone M, et al. Diffuse leptomeningeal glioneuronal tumors: a new entity? Brain Pathol. 2010;20(2):361–6.
Cho HJ, Myung JK, Kim H, Park CK, Kim SK, Chung CK, et al. Primary diffuse leptomeningeal glioneuronal tumors. Brain Tumor Pathol. 2015;32(1):49–55.
Deng MY, Sill M, Chiang J, Schittenhelm J, Ebinger M, Schuhmann MU, et al. Molecularly defined diffuse leptomeningeal glioneuronal tumor (DLGNT) comprises two subgroups with distinct clinical and genetic features. Acta Neuropathol. 2018;136(2):239–53.
Thom M, Liu J, Bongaarts A, Reinten RJ, Paradiso B, Jager HR, et al. Multinodular and vacuolating neuronal tumors in epilepsy: dysplasia or neoplasia? Brain Pathol. 2018;28(2):155–71.
Nunes RH, Hsu CC, da Rocha AJ, do Amaral LLF, Godoy LFS, Watkins TW, et al. Multinodular and vacuolating neuronal tumor of the cerebrum: a new “leave me alone” lesion with a characteristic imaging pattern. AJNR Am J Neuroradiol. 2017;38(10):1899–904.
Alsufayan R, Alcaide-Leon P, de Tilly LN, Mandell DM, Krings T. Natural history of lesions with the MR imaging appearance of multinodular and vacuolating neuronal tumor. Neuroradiology. 2017;59(9):873–83.
Huse JT, Snuderl M, Jones DT, Brathwaite CD, Altman N, Lavi E, et al. Polymorphous low-grade neuroepithelial tumor of the young (PLNTY): an epileptogenic neoplasm with oligodendroglioma-like components, aberrant CD34 expression, and genetic alterations involving the MAP kinase pathway. Acta Neuropathol. 2017;133(3):417–29.
Johnson DR, Giannini C, Jenkins RB, Kim DK, Kaufmann TJ. Plenty of calcification: imaging characterization of polymorphous low-grade neuroepithelial tumor of the young. Neuroradiology. 2019. https://doi.org/10.1007/s00234-019-02269-y. [Epub ahead of print].
Louis DN, Aldape K, Brat DJ, Capper D, Ellison DW, Hawkins C, et al. Announcing cIMPACT-NOW: the consortium to inform molecular and practical approaches to CNS tumor taxonomy. Acta Neuropathol. 2017;133(1):1–3.
Brat DJ, Aldape K, Colman H, Holland EC, Louis DN, Jenkins RB, et al. cIMPACT-NOW update 3: recommended diagnostic criteria for “diffuse astrocytic glioma, IDH-wildtype, with molecular features of glioblastoma, WHO grade IV”. Acta Neuropathol. 2018;136:805.
Akkus Z, Ali I, Sedlar J, Agrawal JP, Parney IF, Giannini C, et al. Predicting deletion of chromosomal arms 1p/19q in low-grade gliomas from MR images using machine intelligence. J Digit Imaging. 2017;30(4):469–76.
Chang P, Grinband J, Weinberg BD, Bardis M, Khy M, Cadena G, et al. Deep-learning convolutional neural networks accurately classify genetic mutations in gliomas. AJNR Am J Neuroradiol. 2018;39(7):1201–7.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Johnson, D.R., Giannini, C., Kaufmann, T.J. (2020). Review of WHO 2016 Changes to Classification of Gliomas; Incorporation of Molecular Markers. In: Pope, W. (eds) Glioma Imaging. Springer, Cham. https://doi.org/10.1007/978-3-030-27359-0_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-27359-0_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-27358-3
Online ISBN: 978-3-030-27359-0
eBook Packages: MedicineMedicine (R0)