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Application of Volumetric Analysis to Glioblastomas: a Correlation Study on the Status of the Isocitrate Dehydrogenase Mutation

  • Bae, Seon Yong (Seoul National University College of Medicine) ;
  • Park, Chul-Kee (Department of Neurosurgery, Seoul National University Hospital) ;
  • Kim, Tae Min (Department of Internal Medicine, Cancer Research Institute, Seoul National University Hospital) ;
  • Park, Sung-Hye (Department of Pathology, Seoul National University Hospital) ;
  • Kim, Il Han (Department of Radiation Oncology, Cancer Research Institute, Seoul National University Hospital) ;
  • Choi, Seung Hong (Institute of Radiation Medicine, Seoul National University Medical Research Center)
  • Received : 2015.10.08
  • Accepted : 2015.11.23
  • Published : 2015.12.31

Abstract

Purpose: To investigate whether volumetric analysis based on T2WI and contrast-enhanced (CE) T1WI can distinguish between isocitrate dehydrogenase-1 mutation-positive ($IDH1^P$) and -negative ($IDH1^N$) glioblastomas (GBMs). Materials and Methods: We retrospectively enrolled 109 patients with histopathologically proven GBMs after surgery or stereotactic biopsy and preoperative MR imaging. We measured the whole-tumor volume in each patient using a semiautomatic segmentation method based on both T2WI and CE T1WI. We compared the tumor volumes between $IDH1^P$ (n = 12) and $IDH1^N$ (n = 97) GBMs using an unpaired t-test. In addition, we performed receiver operating characteristic (ROC) analysis for the differentiation of $IDH1^P$ and $IDH1^N$ GBMs using the tumor volumes based on T2WI and CE T1WI. Results: The mean tumor volume based on T2WI was larger for $IDH1^P$ GBMs than $IDH1^N$ GBMs ($108.8{\pm}68.1$ and $59.3{\pm}37.3mm^3$, respectively, P = 0.0002). In addition, $IDH1^P$ GBMs had a larger tumor volume on CE T1WI than did $IDH1^N$ tumors ($49.00{\pm}40.14$ and $22.53{\pm}17.51mm^3$, respectively, P < 0.0001). ROC analysis revealed that the tumor volume based on T2WI could distinguish $IDH1^P$ from $IDH1^N$ with a cutoff value of 90.25 (P < 0.05): 7 of 12 $IDH1^P$ (58.3%) and 79 of 97 $IDH1^N$ (81.4%). Conclusion: Volumetric analysis of T2WI and CE T1WI could enable $IDH1^P$ GBMs to be distinguished from $IDH1^N$ GBMs. We assumed that secondary GBMs with $IDH1^P$ underwent stepwise progression and were more infiltrative than those with $IDH1^N$, which might have resulted in the differences in tumor volume.

Keywords

References

  1. Daumas-Duport C, Scheithauer B, O'Fallon J, Kelly P. Grading of astrocytomas. A simple and reproducible method. Cancer 1988;62:2152-2165 https://doi.org/10.1002/1097-0142(19881115)62:10<2152::AID-CNCR2820621015>3.0.CO;2-T
  2. Pedersen CL, Romner B. Current treatment of low grade astrocytoma: a review. Clin Neurol Neurosurg 2013;115:1-8 https://doi.org/10.1016/j.clineuro.2012.07.002
  3. Balss J, Meyer J, Mueller W, Korshunov A, Hartmann C, von Deimling A. Analysis of the IDH1 codon 132 mutation in brain tumors. Acta Neuropathol 2008;116:597-602 https://doi.org/10.1007/s00401-008-0455-2
  4. Nobusawa S, Watanabe T, Kleihues P, Ohgaki H. IDH1 mutations as molecular signature and predictive factor of secondary glioblastomas. Clin Cancer Res 2009;15:6002-6007 https://doi.org/10.1158/1078-0432.CCR-09-0715
  5. Yan H, Parsons DW, Jin G, et al. IDH1 and IDH2 mutations in gliomas. N Engl J Med 2009;360:765-773 https://doi.org/10.1056/NEJMoa0808710
  6. Hartmann C, Hentschel B, Wick W, 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;120:707-718 https://doi.org/10.1007/s00401-010-0781-z
  7. Parsons DW, Jones S, Zhang X, et al. An integrated genomic analysis of human glioblastoma multiforme. Science 2008;321:1807-1812 https://doi.org/10.1126/science.1164382
  8. Sanson M, Marie Y, Paris S, et al. Isocitrate dehydrogenase 1 codon 132 mutation is an important prognostic biomarker in gliomas. J Clin Oncol 2009;27:4150-4154 https://doi.org/10.1200/JCO.2009.21.9832
  9. Levner I, Drabycz S, Roldan G, De Robles P, Cairncross JG, Mitchell R. Predicting MGMT methylation status of glioblastomas from MRI texture. Med Image Comput Comput Assist Interv 2009;12:522-530
  10. Jenkinson MD, du Plessis DG, Smith TS, Joyce KA, Warnke PC, Walker C. Histological growth patterns and genotype in oligodendroglial tumours: correlation with MRI features. Brain 2006;129:1884-1891 https://doi.org/10.1093/brain/awl108
  11. Aghi M, Gaviani P, Henson JW, Batchelor TT, Louis DN, Barker FG 2nd. Magnetic resonance imaging characteristics predict epidermal growth factor receptor amplification status in glioblastoma. Clin Cancer Res 2005;11:8600-8605 https://doi.org/10.1158/1078-0432.CCR-05-0713
  12. Mut M, Turba UC, Botella AC, Baskurt E, Lopes MB, Shaffrey ME. Neuroimaging characteristics in subgroup of GBMs with p53 overexpression. J Neuroimaging 2007;17:168-174 https://doi.org/10.1111/j.1552-6569.2007.00112.x
  13. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988;44:837-845 https://doi.org/10.2307/2531595
  14. Lee S, Choi SH, Ryoo I, et al. Evaluation of the microenvironmental heterogeneity in high-grade gliomas with IDH1/2 gene mutation using histogram analysis of diffusionweighted imaging and dynamic-susceptibility contrast perfusion imaging. J Neurooncol 2015;121:141-150 https://doi.org/10.1007/s11060-014-1614-z
  15. Ohgaki H, Kleihues P. The definition of primary and secondary glioblastoma. Clin Cancer Res 2013;19:764-772 https://doi.org/10.1158/1078-0432.CCR-12-3002
  16. Paganetti PA, Caroni P, Schwab ME. Glioblastoma infiltration into central nervous system tissue in vitro: involvement of a metalloprotease. J Cell Biol 1988;107:2281-2291 https://doi.org/10.1083/jcb.107.6.2281
  17. Andronesi OC, Rapalino O, Gerstner E, et al. Detection of oncogenic IDH1 mutations using magnetic resonance spectroscopy of 2-hydroxyglutarate. J Clin Invest 2013;123:3659-3663 https://doi.org/10.1172/JCI67229
  18. Pope WB, Prins RM, Albert Thomas M, et al. Non-invasive detection of 2-hydroxyglutarate and other metabolites in IDH1 mutant glioma patients using magnetic resonance spectroscopy. J Neurooncol 2012;107:197-205 https://doi.org/10.1007/s11060-011-0737-8
  19. Choi C, Ganji SK, DeBerardinis RJ, et al. 2-hydroxyglutarate detection by magnetic resonance spectroscopy in IDHmutated patients with gliomas. Nat Med 2012;18:624-629 https://doi.org/10.1038/nm.2682
  20. SongTao Q, Lei Y, Si G, et al. IDH mutations predict longer survival and response to temozolomide in secondary glioblastoma. Cancer Sci 2012;103:269-273 https://doi.org/10.1111/j.1349-7006.2011.02134.x
  21. Tran AN, Lai A, Li S, et al. Increased sensitivity to radiochemotherapy in IDH1 mutant glioblastoma as demonstrated by serial quantitative MR volumetry. Neuro Oncol 2014;16:414-420 https://doi.org/10.1093/neuonc/not198
  22. Carrillo JA, 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;33:1349-1355 https://doi.org/10.3174/ajnr.A2950
  23. Jiao Y, Killela PJ, Reitman ZJ, et al. Frequent ATRX, CIC, FUBP1 and IDH1 mutations refine the classification of malignant gliomas. Oncotarget 2012;3:709-722