TY - STD TI - Louis DN, Ohgaki H, Wiestler OD, Cavenee WK (2016) WHO classification oftumours of the central nervous system, revised 4th edition. IARC, Lyon. ID - ref1 ER - TY - STD TI - Sahm F, Reuss D, Koelsche C et al (2014) Farewell to oligoastrocytoma: insitu molecular genetics favor classification as either oligodendroglioma orastrocytoma. Acta Neuropathol 128(4):551–559. https://doi.org/10.1007/s00401-014-1326-7 ID - ref2 ER - TY - STD TI - Bready D, Placantonakis DG (2019) Molecular pathogenesis of low-gradeglioma. Neurosurg Clin N Am 30(1):17–25. https://doi.org/10.1016/j.nec.2018.08.011 ID - ref3 ER - TY - STD TI - Duffau H (2016) Long-term outcomes after supratotal resection of diffuselow-grade gliomas: a consecutive series with 11-year follow-up. ActaNeurochir (Wien) 158(1):51–58. https://doi.org/10.1007/s00701-015-2621-3 ID - ref4 ER - TY - STD TI - National Comprehensive Cancer Network. Central nervous system cancers (Version 1.2019). https://www.nccn.org/professionals/physician_gls/pdf/cns.pdf. Accessed Mar 5 2019 UR - https://www.nccn.org/professionals/physician_gls/pdf/cns.pdf ID - ref5 ER - TY - JOUR AU - Olson, J. J. AU - Kalkanis, S. N. AU - Ryken, T. C. PY - 2015 DA - 2015// TI - Evidence-based clinical practiceparameter guidelines for the treatment of adults with diffuse low-gradeglioma: introduction and methods JO - J Neurooncol VL - 125 UR - https://doi.org/10.1007/s11060-015-1847-5 DO - 10.1007/s11060-015-1847-5 ID - Olson2015 ER - TY - STD TI - Fouke SJ, Benzinger T, Gibson D, Ryken TC, Kalkanis SN, Olson JJ (2015) Therole of imaging in the management of adults with diffuse low-gradeglioma: a systematic review and evidence-based clinical practice guideline. JNeurooncol 125(3):457–479. https://doi.org/10.1007/s11060-015-1908-9 ID - ref7 ER - TY - STD TI - Caulo M, Panara V, Tortora D et al (2014) Data-driven grading of braingliomas: a multiparametric MR imaging study. Radiology 272(2):494–503. https://doi.org/10.1148/radiol.14132040. ID - ref8 ER - TY - JOUR AU - Li, X. AU - Zhu, Y. AU - Kang, H. PY - 2015 DA - 2015// TI - Glioma grading by microvascularpermeability parameters derived from dynamic contrast-enhanced MRI andintratumoral susceptibility signal on susceptibility weighted imaging JO - CancerImaging VL - 15 ID - Li2015 ER - TY - JOUR AU - Delgado, A. F. AU - Delgado, A. F. PY - 2017 DA - 2017// TI - Discrimination between glioma grades IIand III using dynamic susceptibility perfusion MRI: a meta-analysis JO - AJNR AmJ Neuroradiol VL - 38 UR - https://doi.org/10.3174/ajnr.A5218 DO - 10.3174/ajnr.A5218 ID - Delgado2017 ER - TY - STD TI - Kong L, Chen H, Yang Y, Chen L (2017) A meta-analysis of arterial spinlabelling perfusion values for the prediction of glioma grade. Clin Radiol72(3):255–261. https://doi.org/10.1016/j.crad.2016.10.016. ID - ref11 ER - TY - STD TI - ACR Committee on Drugs and Contrast Media (2018) ACR manual oncontrast media (Version 10.3, 2018). https://www.acr.org/-/media/ACR/Files/Clinical-Resources/Contrast_Media.pdf. Accessed 2018. UR - https://www.acr.org/-/media/ACR/Files/Clinical-Resources/Contrast_Media.pdf ID - ref12 ER - TY - JOUR AU - Choi, C. AU - Ganji, S. K. AU - DeBerardinis, R. J. PY - 2012 DA - 2012// TI - 2-hydroxyglutarate detectionby magnetic resonance spectroscopy in IDH-mutated patients with gliomas JO - Nat Med VL - 18 UR - https://doi.org/10.1038/nm.2682 DO - 10.1038/nm.2682 ID - Choi2012 ER - TY - JOUR AU - Tietze, A. AU - Choi, C. AU - Mickey, B. PY - 2018 DA - 2018// TI - Noninvasive assessment of isocitratedehydrogenase mutation status in cerebral gliomas by magnetic resonancespectroscopy in a clinical setting JO - J Neurosurg VL - 128 UR - https://doi.org/10.3171/2016.10.JNS161793 DO - 10.3171/2016.10.JNS161793 ID - Tietze2018 ER - TY - JOUR AU - Suh, C. H. AU - Park, J. E. AU - Jung, S. C. AU - Choi, C. G. AU - Kim, S. J. AU - Kim, H. S. PY - 2019 DA - 2019// TI - Amide protontransfer-weighted MRI in distinguishing high- and low-grade gliomas: asystematic review and meta-analysis JO - Neuroradiology VL - 61 UR - https://doi.org/10.1007/s00234-018-02152-2 DO - 10.1007/s00234-018-02152-2 ID - Suh2019 ER - TY - STD TI - Park JE, Kim HS, Park KJ, Choi CG, Kim SJ (2015) Histogram analysis of amideproton transfer imaging to identify contrast-enhancing low-grade braintumor that mimics high-grade tumor: increased accuracy of MR perfusion.Radiology 277(1):151–161. https://doi.org/10.1148/radiol.2015142347. ID - ref16 ER - TY - JOUR AU - Biller, A. AU - Badde, S. AU - Nagel, A. PY - 2016 DA - 2016// TI - Improved brain tumor classification bysodium MR imaging: prediction of IDH mutation status and tumor progression.AJNR JO - Am J Neuroradiol VL - 37 UR - https://doi.org/10.3174/ajnr.A4493 DO - 10.3174/ajnr.A4493 ID - Biller2016 ER - TY - JOUR AU - Pepin, K. M. AU - McGee, K. P. AU - Arani, A. PY - 2018 DA - 2018// TI - MR elastography analysis ofglioma stiffness and IDH1-mutation status JO - AJNR Am J Neuroradiol VL - 39 UR - https://doi.org/10.3174/ajnr.A5415 DO - 10.3174/ajnr.A5415 ID - Pepin2018 ER - TY - JOUR AU - Law, M. AU - Yang, S. AU - Wang, H. PY - 2003 DA - 2003// TI - Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MRspectroscopic imaging compared with conventional MR imaging JO - AJNR AmJ Neuroradiol VL - 24 ID - Law2003 ER - TY - JOUR AU - Bulakbasi, N. AU - Kocaoglu, M. AU - Farzaliyev, A. AU - Tayfun, C. AU - Ucoz, T. AU - Somuncu, I. PY - 2005 DA - 2005// TI - Assessment of diagnostic accuracy of perfusion MR imaging in primary andmetastatic solitary malignant brain tumors JO - AJNR Am J Neuroradiol VL - 26 ID - Bulakbasi2005 ER - TY - JOUR AU - Anzalone, N. AU - Castellano, A. AU - Cadioli, M. PY - 2018 DA - 2018// TI - Brain gliomas: multicenterstandardized assessment of dynamic contrast-enhanced and dynamicsusceptibility contrast MR images JO - Radiology VL - 287 UR - https://doi.org/10.1148/radiol.2017170362 DO - 10.1148/radiol.2017170362 ID - Anzalone2018 ER - TY - JOUR AU - Liang, J. AU - Liu, D. AU - Gao, P. PY - 2018 DA - 2018// TI - Diagnostic values of DCE-MRI and DSC-MRIfor differentiation between high-grade and low-grade gliomas: acomprehensive meta-analysis JO - Acad Radiol VL - 25 UR - https://doi.org/10.1016/j.acra.2017.10.001 DO - 10.1016/j.acra.2017.10.001 ID - Liang2018 ER - TY - STD TI - Bulakbasi N, Guvenc I, Onguru O, Erdogan E, Tayfun C, Ucoz T (2004) Theadded value of the apparent diffusion coefficient calculation to magneticresonance imaging in the differentiation and grading of malignant braintumors. J Comput Assist Tomogr 28(6):735–46 ID - ref23 ER - TY - STD TI - Server A, Kulle B, Gadmar ØB, Josefsen R, Kumar T, Nakstad PH (2011) Measurements of diagnostic examination performance using quantitativeapparent diffusion coefficient and proton MR spectroscopic imaging in thepreoperative evaluation of tumor grade in cerebral gliomas. Eur J Radiol 80(2):462–70. https://doi.org/10.1016/j.ejrad.2010.07.017 ID - ref24 ER - TY - STD TI - Miloushev VZ, Chow DS, Filippi CG (2015) Meta-analysis of diffusion metricsfor the prediction of tumor grade in gliomas. AJNR Am J Neuroradiol 36(2):302–8. https://doi.org/10.3174/ajnr.A4097 ID - ref25 ER - TY - STD TI - Zhang L, Min Z, Tang M, Chen S, Lei X, Zhang X (2017) The utility ofdiffusion MRI with quantitative ADC measurements for differentiating high-grade from low-grade cerebral gliomas: evidence from a meta-analysis. JNeurol Sci 373:9–15. https://doi.org/10.1016/j.jns.2016.12.008Erratum in: JNeurol Sci. 2017;375:103–6 ID - ref26 ER - TY - STD TI - Liang R, Wang X, Li M et al. (2014) Potential role of fractionalanisotropy derived from diffusion tensor imaging in differentiatinghigh-grade gliomas from low-grade gliomas: a meta-analysis. Int J ClinExp Med 7(10):3647–53 ID - ref27 ER - TY - JOUR AU - Falk Delgado, A. AU - Nilsson, M. AU - Westen, D. AU - Falk Delgado, A. PY - 2018 DA - 2018// TI - Gliomagrade discrimination with MR diffusion kurtosis imaging: a meta-analysis ofdiagnostic accuracy JO - Radiology VL - 287 UR - https://doi.org/10.1148/radiol.2017171315 DO - 10.1148/radiol.2017171315 ID - Falk Delgado2018 ER - TY - JOUR AU - Castillo, M. AU - Smith, J. K. AU - Kwock, L. PY - 2000 DA - 2000// TI - Correlation of myo-inositol levels andgrading of cerebral astrocytomas JO - AJNR Am J Neuroradiol VL - 21 ID - Castillo2000 ER - TY - JOUR AU - Wang, Q. AU - Zhang, H. AU - Zhang, J. PY - 2016 DA - 2016// TI - The diagnostic performance ofmagnetic resonance spectroscopy in differentiating high-from low-gradegliomas: a systematic review and meta-analysis JO - Eur Radiol VL - 26 UR - https://doi.org/10.1007/s00330-015-4046-z DO - 10.1007/s00330-015-4046-z ID - Wang2016 ER - TY - JOUR AU - Usinskiene, J. AU - Ulyte, A. AU - Bjørnerud, A. PY - 2016 DA - 2016// TI - Optimal differentiation ofhigh- and low-grade glioma and metastasis: a meta-analysis of perfusion, diffusion, and spectroscopy metrics JO - Neuroradiology VL - 58 UR - https://doi.org/10.1007/s00234-016-1642-9 DO - 10.1007/s00234-016-1642-9 ID - Usinskiene2016 ER - TY - JOUR AU - Hilario, A. AU - Sepulveda, J. M. AU - Perez-Nuñez, A. PY - 2014 DA - 2014// TI - A prognostic modelbased on preoperative MRI predicts overall survival in patients with diffusegliomas JO - AJNR Am J Neuroradiol VL - 35 UR - https://doi.org/10.3174/ajnr.A3837 DO - 10.3174/ajnr.A3837 ID - Hilario2014 ER - TY - JOUR AU - Cuccarini, V. AU - Erbetta, A. AU - Farinotti, M. PY - 2016 DA - 2016// TI - Advanced MRI maycomplement histological diagnosis of lower grade gliomas and help inpredicting survival JO - J Neurooncol VL - 126 UR - https://doi.org/10.1007/s11060-015-1960-5 DO - 10.1007/s11060-015-1960-5 ID - Cuccarini2016 ER - TY - JOUR AU - Villanueva-Meyer, J. E. AU - Wood, M. D. AU - Choi, B. S. PY - 2018 DA - 2018// TI - MRI features and IDHmutational status of grade II diffuse gliomas: impact on diagnosis andprognosis JO - AJR Am J Roentgenol VL - 210 UR - https://doi.org/10.2214/AJR.17.18457 DO - 10.2214/AJR.17.18457 ID - Villanueva-Meyer2018 ER - TY - JOUR AU - Law, M. AU - Oh, S. AU - Babb, J. S. PY - 2006 DA - 2006// TI - Low-grade gliomas: dynamicsusceptibility-weighted contrast-enhanced perfusion MR imaging-predictionof patient clinical response JO - Radiology. VL - 238 UR - https://doi.org/10.1148/radiol.2382042180 DO - 10.1148/radiol.2382042180 ID - Law2006 ER - TY - STD TI - Nguyen TB, Cron GO, Mercier JF et al. (2015) Preoperative prognostic valueof dynamic contrast-enhanced MRI-derived contrast transfer coefficient andplasma volume in patients with cerebral gliomas. AJNR Am J Neuroradiol36(1):63–69. https://doi.org/10.3174/ajnr.A4006 ID - ref36 ER - TY - JOUR AU - Hlaihel, C. AU - Guilloton, L. AU - Guyotat, J. AU - Streichenberger, N. AU - Honnorat, J. AU - Cotton, F. PY - 2010 DA - 2010// TI - Predictive value of multimodality MRI using conventional, perfusion, and spectroscopy MR in anaplastic transformation of low-gradeoligodendrogliomas JO - J Neurooncol VL - 97 UR - https://doi.org/10.1007/s11060-009-9991-4 DO - 10.1007/s11060-009-9991-4 ID - Hlaihel2010 ER - TY - STD TI - Law M, Young RJ, Babb JS et al. (2008) Gliomas: predicting time toprogression or survival with cerebral blood volume measurements atdynamic susceptibility-weighted contrast-enhanced perfusion MR imaging.Radiology 247(2):490–98. https://doi.org/10.1148/radiol.2472070898 ID - ref38 ER - TY - JOUR AU - Danchaivijitr, N. AU - Waldman, A. D. AU - Tozer, D. J. PY - 2008 DA - 2008// TI - Low-grade gliomas: dochanges in rCBV measurements at longitudinal perfusion-weighted MRimaging predict malignant transformation? JO - Radiology VL - 247 UR - https://doi.org/10.1148/radiol.2471062089 DO - 10.1148/radiol.2471062089 ID - Danchaivijitr2008 ER - TY - JOUR AU - Back, M. AU - Jayamanne, D. T. AU - Brazier, D. PY - 2019 DA - 2019// TI - Influence of molecularclassification in anaplastic glioma for determining outcome and futureapproach to management JO - J Med Imaging Radiat Oncol VL - 63 UR - https://doi.org/10.1111/1754-9485.12850 DO - 10.1111/1754-9485.12850 ID - Back2019 ER - TY - JOUR AU - Shirahata, M. AU - Ono, T. AU - Stichel, D. PY - 2018 DA - 2018// TI - Novel, improved gradingsystem(s) for IDH-mutant astrocytic gliomas JO - Acta Neuropathol VL - 136 UR - https://doi.org/10.1007/s00401-018-1849-4 DO - 10.1007/s00401-018-1849-4 ID - Shirahata2018 ER - TY - JOUR AU - Patel, S. H. AU - Poisson, L. M. AU - Brat, D. J. PY - 2017 DA - 2017// TI - T2-FLAIR mismatch, an imagingbiomarker for IDH and 1p/19q status in lower-grade gliomas: a TCGA/TCIA project JO - Clin Cancer Res VL - 23 UR - https://doi.org/10.1158/1078-0432.CCR-17-0560 DO - 10.1158/1078-0432.CCR-17-0560 ID - Patel2017 ER - TY - JOUR AU - Ren, Y. AU - Zhang, X. AU - Rui, W. PY - 2019 DA - 2019// TI - Noninvasive prediction of IDH1 mutationand ATRX expression loss in low-grade gliomas using multiparametric MRradiomic features JO - J Magn Reson Imaging VL - 49 UR - https://doi.org/10.1002/jmri.26240 DO - 10.1002/jmri.26240 ID - Ren2019 ER - TY - JOUR AU - Hasselblatt, M. AU - Jaber, M. AU - Reuss, D. PY - 2018 DA - 2018// TI - Diffuse astrocytoma, IDH-wildtype: a dissolving diagnosis JO - J Neuropathol Exp Neurol VL - 77 UR - https://doi.org/10.1093/jnen/nly012 DO - 10.1093/jnen/nly012 ID - Hasselblatt2018 ER - TY - STD TI - BratDJ, AldapeK, ColmanH, etal. (2018) cIMPACT-NOWupdate3:recommended diagnostic criteria for "diffuse astrocytic glioma, IDH-wildtype, with molecular features of glioblastoma, WHO grade IV. Acta Neuropathol 136(5):805–10. https://doi.org/10.1007/s00401-018-1913-0 ID - ref45 ER - TY - STD TI - Wu CC, Jain R, Radmanesh A et al. (2018) Predicting genotype and survivalin glioma using standard clinical MR imaging apparent diffusion coefficientimages: a pilot study from the cancer genome atlas. AJNR Am J Neuroradiol 39(10):1814–20. https://doi.org/10.3174/ajnr.A5794 ID - ref46 ER - TY - JOUR AU - Smits, M. AU - Bent, M. J. PY - 2017 DA - 2017// TI - Imaging correlates of adult gliomagenotypes JO - Radiology VL - 284 UR - https://doi.org/10.1148/radiol.2017151930 DO - 10.1148/radiol.2017151930 ID - Smits2017 ER - TY - STD TI - Kickingereder P, Sahm F, Radbruch A et al. (2015) IDH mutation status isassociated with a distinct hypoxia/angiogenesis transcriptome signaturewhich is non-invasively predictable with rCBV imaging in human glioma. SciRep 5:16238. https://doi.org/10.1038/srep16238 ID - ref48 ER - TY - JOUR AU - Leu, K. AU - Ott, G. A. AU - Lai, A. PY - 2017 DA - 2017// TI - Perfusion and diffusion MRI signatures inhistologic and genetic subtypes of WHO grade II-III diffuse gliomas JO - JNeurooncol VL - 134 UR - https://doi.org/10.1007/s11060-017-2506-9 DO - 10.1007/s11060-017-2506-9 ID - Leu2017 ER - TY - JOUR AU - Stadlbauer, A. AU - Zimmermann, M. AU - Kitzwögerer, M. PY - 2017 DA - 2017// TI - MR imaging-derived oxygen metabolism and neovascularization characterization forgrading and IDH gene mutation detection of gliomas JO - Radiology VL - 283 UR - https://doi.org/10.1148/radiol.2016161422 DO - 10.1148/radiol.2016161422 ID - Stadlbauer2017 ER - TY - JOUR AU - Bian, W. AU - Khayal, I. S. AU - Lupo, J. M. PY - 2009 DA - 2009// TI - Multiparametric characterization ofgrade 2 glioma subtypes using magnetic resonance spectroscopic, perfusion, and diffusion imaging JO - Transl Oncol VL - 2 UR - https://doi.org/10.1593/tlo.09178 DO - 10.1593/tlo.09178 ID - Bian2009 ER - TY - JOUR AU - Lin, Y. AU - Xing, Z. AU - She, D. PY - 2017 DA - 2017// TI - IDH mutant and 1p/19q co-deletedoligodendrogliomas: tumor grade stratification using diffusion-, susceptibility-, and perfusion-weighted MRI JO - Neuroradiology VL - 59 UR - https://doi.org/10.1007/s00234-017-1839-6 DO - 10.1007/s00234-017-1839-6 ID - Lin2017 ER - TY - JOUR AU - Yoon, H. J. AU - Ahn, K. J. AU - Lee, S. PY - 2017 DA - 2017// TI - Differential diagnosis of oligodendroglialand astrocytic tumors using imaging results: the added value of perfusionMR imaging JO - Neuroradiology VL - 59 UR - https://doi.org/10.1007/s00234-017-1851-x DO - 10.1007/s00234-017-1851-x ID - Yoon2017 ER - TY - STD TI - Jenkinson MD, Smith TS, Joyce KA et al. (2006) Cerebral blood volume, genotype and chemosensitivity in oligodendroglial tumours.Neuroradiology 48(10):703–13. ID - ref54 ER - TY - JOUR AU - Chawla, S. AU - Krejza, J. AU - Vossough, A. PY - 2013 DA - 2013// TI - Differentiation betweenoligodendroglioma genotypes using dynamic susceptibility contrastperfusion-weighted imaging and proton MR spectroscopy JO - AJNR Am JNeuroradiol VL - 34 UR - https://doi.org/10.3174/ajnr.A3384 DO - 10.3174/ajnr.A3384 ID - Chawla2013 ER - TY - JOUR AU - Emblem, K. E. AU - Scheie, D. AU - Due-Tonnessen, P. PY - 2008 DA - 2008// TI - Histogram analysis ofMR imaging-derived cerebral blood volume maps: combined gliomagrading and identification of low-grade oligodendroglial subtypes JO - AJNRAm J Neuroradiol VL - 29 UR - https://doi.org/10.3174/ajnr.A1182 DO - 10.3174/ajnr.A1182 ID - Emblem2008 ER - TY - JOUR AU - Emblem, K. E. AU - Nedregaard, B. AU - Nome, T. PY - 2008 DA - 2008// TI - Glioma grading by usinghistogram analysis of blood volume heterogeneity from MR-derivedcerebral blood volume maps JO - Radiology VL - 247 UR - https://doi.org/10.1148/radiol.2473070571 DO - 10.1148/radiol.2473070571 ID - Emblem2008 ER - TY - STD TI - Dietrich O, Reiser MF, Schoenberg SO (2008) Artifacts in 3T MRI: physicalbackground and reduction strategies. Eur J Radiol 65(1):29–35 ID - ref58 ER - TY - JOUR AU - Vargas, M. I. AU - Delavelle, J. AU - Kohler, R. AU - Becker, C. D. AU - Lovblad, K. PY - 2009 DA - 2009// TI - Brain and spineMRI artifacts at 3Tesla JO - J Neuroradiol VL - 36 UR - https://doi.org/10.1016/j.neurad.2008.08.001 DO - 10.1016/j.neurad.2008.08.001 ID - Vargas2009 ER - TY - JOUR AU - Kang, Y. AU - Choi, S. H. AU - Kim, Y. J. PY - 2011 DA - 2011// TI - Gliomas: histogram analysis of apparentdiffusion coefficient maps with standard- or high-b-value diffusion-weighted MR imaging--correlation with tumor grade JO - Radiology VL - 261 UR - https://doi.org/10.1148/radiol.11110686 DO - 10.1148/radiol.11110686 ID - Kang2011 ER - TY - STD TI - Zhou M, Scott J, Chaudhury B et al. (2018) Radiomics in brain tumor: imageassessment, quantitative feature descriptors, and machine-learningapproaches. AJNR Am J Neuroradiol 39(2):208–16. https://doi.org/10.3174/ajnr.A5391 ID - ref61 ER - TY - JOUR AU - Zhang, X. AU - Yan, L. F. AU - Hu, Y. C. PY - 2017 DA - 2017// TI - Optimizing a machine learning basedglioma grading system using multi-parametric MRI histogram and texturefeatures JO - Oncotarget VL - 8 ID - Zhang2017 ER - TY - STD TI - Lee MH, Kim J, Kim ST et al. (2019) Prediction of IDH1 mutation in GBMusing machine learning technique based on quantitative radiomic data.World Neurosurg 125:e688–e696. https://doi.org/10.1016/j.wneu.2019.01.157 ID - ref63 ER -