Skip to main content

Advertisement

SpringerLink
Log in

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

  • Clinical Study
  • Published:
Journal of Neuro-Oncology Aims and scope Submit manuscript

Abstract

The purpose of our study was to explore the difference between isocitrate dehydrogenase (IDH)-1/2 gene mutation-positive and -negative high-grade gliomas (HGGs) using histogram analysis of apparent diffusion coefficient (ADC) and normalized cerebral blood volume (nCBV) maps. We enrolled 52 patients with histopathologically confirmed HGGs with IDH1/2 P (n = 16) or IDH1/2 N (n = 36). Histogram parameters of ADC and nCBV maps were correlated with gene mutations by using the unpaired student’s t test and multivariable stepwise logistic regression analysis. The mean ADC value was higher in the IDH1 P group than IDH1 N (1,282.8 vs. 1,159.6 mm2/s, P = .0113). In terms of the cumulative ADC histograms, the 10th and 50th percentile values were also higher in the IDH1 P than IDH1 N (P = .0104 and .0183, respectively). We observed a higher 90th percentile value (3.121 vs. 2.397, P = .0208) and a steeper slope between the 10th (C10) and 90th (C90) of cumulative nCBV histograms (0.03386 vs. 0.02425/%, P = .0067) in the IDH1 N group. Multivariate analysis showed that the mean ADC mean value (P = .0048), the C90 value (P = .0113), and the slope between C10 and C90 (P = .0049) were the significant variables in the differentiation of IDH1 P from IDH1 N. In conclusion, histogram analysis of ADC and nCBV maps based on entire tumor volume can be a useful tool for distinguishing IDH1 P and IDH1 N, and it predicts that IDH P tumors have a more heterogeneous microenvironment than IDH N ones.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Daumas-Duport C, Scheithauer B, O’Fallon J, Kelly P (1988) Grading of astrocytomas. A simple and reproducible method. Cancer 62:2152–2165

    Article  CAS  PubMed  Google Scholar 

  2. Nikiforova MN, Hamilton RL (2011) Molecular diagnostics of gliomas. Arch Pathol Lab Med 135:558–568

    CAS  PubMed  Google Scholar 

  3. Balss J, Meyer J, Mueller W, Korshunov A, Hartmann C, von Deimling A (2008) Analysis of the IDH1 codon 132 mutation in brain tumors. Acta Neuropathol 116:597–602

    Article  CAS  PubMed  Google Scholar 

  4. Yan H, Parsons DW, Jin GL, McLendon R, Rasheed BA, Yuan WS, Kos I, Batinic-Haberle I, Jones S, Riggins GJ, Friedman H, Friedman A, Reardon D, Herndon J, Kinzler KW, Velculescu VE, Vogelstein B, Bigner DD (2009) IDH1 and IDH2 mutations in gliomas. New Engl J Med 360:765–773

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  5. Hartmann C, Hentschel B, Wick W, Capper D, Felsberg J, Simon M, Westphal M, Schackert G, Meyermann R, Pietsch T, Reifenberger G, Weller M, Loeffler M, von Deimling A (2010) 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 120:707–718

    Article  PubMed  Google Scholar 

  6. Parsons DW, Jones S, Zhang X, Lin JC, Leary RJ, Angenendt P, Mankoo P, Carter H, Siu IM, Gallia GL, Olivi A, McLendon R, Rasheed BA, Keir S, Nikolskaya T, Nikolsky Y, Busam DA, Tekleab H, Diaz LA Jr, Hartigan J, Smith DR, Strausberg RL, Marie SK, Shinjo SM, Yan H, Riggins GJ, Bigner DD, Karchin R, Papadopoulos N, Parmigiani G, Vogelstein B, Velculescu VE, Kinzler KW (2008) An integrated genomic analysis of human glioblastoma multiforme. Science 321:1807–1812

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  7. Sanson M, Marie Y, Paris S, Idbaih A, Laffaire J, Ducray F, El Hallani S, Boisselier B, Mokhtari K, Hoang-Xuan K, Delattre JY (2009) Isocitrate dehydrogenase 1 codon 132 mutation is an important prognostic biomarker in gliomas. J Clin Oncol 27:4150–4154

    Article  CAS  PubMed  Google Scholar 

  8. Andronesi OC, Rapalino O, Gerstner E, Chi A, Batchelor TT, Cahil DP, Sorensen AG, Rosen BR (2013) Detection of oncogenic IDH1 mutations using magnetic resonance spectroscopy of 2-hydroxyglutarate. J Clin Invest 123:3659–3663

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  9. Kim H, Choi SH, Kim JH, Ryoo I, Kim SC, Yeom JA, Shin H, Jung SC, Lee AL, Yun TJ, Park CK, Sohn CH, Park SH (2013) Gliomas: application of cumulative histogram analysis of normalized cerebral blood volume on 3 T MRI to tumor grading. PLoS ONE 8(5):e63462. doi:10.1371/journal.pone.0063462

    Article  PubMed Central  PubMed  Google Scholar 

  10. Jung SC, Choi SH, Yeom JA, Kim JH, Ryoo I, Kim SC, Shin H, Lee AL, Yun TJ, Park CK, Sohn CH, Park SH (2013) Cerebral blood volume analysis in glioblastomas using dynamic susceptibility contrast-enhanced perfusion MRI: a comparison of manual and semiautomatic segmentation methods. PLoS ONE 8(8):e69323. doi:10.1371/journal.pone.0069323

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  11. Thomsen H, Steffensen E, Larsson EM (2012) Perfusion MRI (dynamic susceptibility contrast imaging) with different measurement approaches for the evaluation of blood flow and blood volume in human gliomas. Acta Radiol 53:95–101

    Article  CAS  PubMed  Google Scholar 

  12. Carrillo JA, Lai A, Nghiemphu PL, Kim HJ, Phillips HS, Kharbanda S, Moftakhar P, Lalaezari S, Yong W, Ellingson BM, Cloughesy TF, Pope WB (2012) Relationship between tumor enhancement, edema, IDH1 mutational status, MGMT promoter methylation, and survival in glioblastoma. Am J Neuroradiol 33:1349–1355

    Article  CAS  PubMed  Google Scholar 

  13. Kang Y, Choi SH, Kim YJ, Kim KG, Sohn CH, Kim JH, Yun TJ, Chang KH (2011) Gliomas: histogram analysis of apparent diffusion coefficient maps with standard- or high-b-value diffusion-weighted MR imaging—correlation with tumor grade. Radiology 261:882–890

    Article  PubMed  Google Scholar 

  14. Garzon B, Emblem KE, Mouridsen K, Nedregaard B, Due-Tonnessen P, Nome T, Hald JK, Bjornerud A, Haberg AK, Kvinnsland Y (2011) Multiparametric analysis of magnetic resonance images for glioma grading and patient survival time prediction. Acta Radiol 52:1052–1060

    Article  PubMed  Google Scholar 

  15. Rosen BR, Belliveau JW, Vevea JM, Brady TJ (1990) Perfusion imaging with NMR contrast agents. Magn Reson Med 14:249–265

    Article  CAS  PubMed  Google Scholar 

  16. Ostergaard L, Weisskoff RM, Chesler DA, Gyldensted C, Rosen BR (1996) High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. 1. Mathematical approach and statistical analysis. Magnet Reson Med 36:715–725

    Article  CAS  Google Scholar 

  17. Boxerman JL, Schmainda KM, Weisskoff RM (2006) Relative cerebral blood volume maps corrected for contrast agent extravasation significantly correlate with glioma tumor grade, whereas uncorrected maps do not. Am J Neuroradiol 27:859–867

    CAS  PubMed  Google Scholar 

  18. Wetzel SG, Cha S, Johnson G, Lee P, Law M, Kasow DL, Pierce SD, Xue X (2002) Relative cerebral blood volume measurements in intracranial mass lesions: interobserver and intraobserver reproducibility study. Radiology 224:797–803

    Article  PubMed  Google Scholar 

  19. Tozer DJ, Jager HR, Danchaivijitr N, Benton CE, Tofts PS, Rees JH, Waldman AD (2007) Apparent diffusion coefficient histograms may predict low-grade glioma subtype. NMR Biomed 20:49–57

    Article  PubMed  Google Scholar 

  20. Delong ER, Delong DM, Clarkepearson DI (1988) Comparing the areas under 2 or more correlated receiver operating characteristic curves—a nonparametric approach. Biometrics 44:837–845

    Article  CAS  PubMed  Google Scholar 

  21. Hartmann C, Meyer J, Balss J, Capper D, Mueller W, Christians A, Felsberg J, Wolter M, Mawrin C, Wick W, Weller M, Herold-Mende C, Unterberg A, Jeuken JWM, Wesseling P, Reifenberger G, von Deimling A (2009) Type and frequency of IDH1 and IDH2 mutations are related to astrocytic and oligodendroglial differentiation and age: a study of 1,010 diffuse gliomas. Acta Neuropathol 118:469–474

    Article  PubMed  Google Scholar 

  22. Ichimura K, Pearson DM, Kocialkowski S, Backlund LM, Chan R, Jones DTW, Collins VP (2009) IDH1 mutations are present in the majority of common adult gliomas but rare in primary glioblastomas. Neuro-Oncology 11:341–347

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  23. Watanabe T, Nobusawa S, Kleihues P, Ohgaki H (2009) IDH1 mutations are early events in the development of astrocytomas and oligodendrogliomas. Am J Pathol 174:1149–1153

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  24. Pope WB, Prins RM, Albert Thomas M, Nagarajan R, Yen KE, Bittinger MA, Salamon N, Chou AP, Yong WH, Soto H, Wilson N, Driggers E, Jang HG, Su SM, Schenkein DP, Lai A, Cloughesy TF, Kornblum HI, Wu H, Fantin VR, Liau LM (2012) Non-invasive detection of 2-hydroxyglutarate and other metabolites in IDH1 mutant glioma patients using magnetic resonance spectroscopy. J Neurooncol 107:197–205

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  25. Choi C, Ganji SK, DeBerardinis RJ, Hatanpaa KJ, Rakheja D, Kovacs Z, Yang XL, Mashimo T, Raisanen JM, Marin-Valencia I, Pascual JM, Madden CJ, Mickey BE, Malloy CR, Bachoo RM, Maher EA (2012) 2-hydroxyglutarate detection by magnetic resonance spectroscopy in IDH-mutated patients with gliomas. Nat Med 18:624–629

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  26. Emblem KE, Nedregaard B, Nome T, Due-Tonnessen P, Hald JK, Scheie D, Borota OC, Cvancarova M, Bjornerud A (2008) Glioma grading by using histogram analysis of blood volume heterogeneity from MR-derived cerebral blood volume maps. Radiology 247:808–817

    Article  PubMed  Google Scholar 

  27. Tan WL, Huang WY, Yin B, Xiong J, Wu JS, Geng DY (2014) Can diffusion tensor imaging noninvasively detect IDH1 gene mutations in astrogliomas? A retrospective study of 112 cases. AJNR Am J Neuroradiol 35:920–927. doi:10.3174/ajnr.A3803

    Article  CAS  PubMed  Google Scholar 

  28. Emblem KE, Scheie D, Due-Tonnessen P, Nedregaard B, Nome T, Hald JK, Beiske K, Meling TR, Bjornerud A (2008) Histogram analysis of mr imaging-derived cerebral blood volume maps: combined glioma grading and identification of low-grade oligodendroglial subtypes. Am J Neuroradiol 29:1664–1670

    Article  CAS  PubMed  Google Scholar 

  29. Young R, Babb J, Law M, Pollack E, Johnson G (2007) Comparison of region-of-interest analysis with three different histogram analysis methods in the determination of perfusion metrics in patients with brain gliomas. J Magn Reson Imaging 26:1053–1063

    Article  PubMed  Google Scholar 

  30. Paulson ES, Schmainda KM (2008) Comparison of Dynamic susceptibility-weighted contrast-enhanced mr methods: recommendations for measuring relative cerebral blood volume in brain tumors. Radiology 249:601–613

    Article  PubMed Central  PubMed  Google Scholar 

  31. Jiao YC, Killela PJ, Reitman ZJ, Rasheed BA, Heaphy CM, de Wilde RF, Rodriguez FJ, Rosemberg S, Oba-Shinjo SM, Marie SKN, Bettegowda C, Agrawal N, Lipp E, Pirozzi CJ, Lopez GY, He YP, Friedman HS, Friedman AH, Riggins GJ, Holdhoff M, Burger P, McLendon RE, Bigner DD, Vogelstein B, Meeker AK, Kinzler KW, Papadopoulos N, Diaz LA, Yan H (2012) Frequent ATRX, CIC, FUBP1 and IDH1 mutations refine the classification of malignant gliomas. Oncotarget 3:709–722

    PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgments

This study was supported by a grant from the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea (1120300), the Korea Healthcare technology R&D Projects, Ministry for Health, Welfare & Family Affairs (A112028 and HI13C0015), and the Research Center Program of IBS (Institute for Basic Science) in Korea.

Conflict of interest

None of the authors have any conflict of interest.

Author information

Authors and Affiliations

  1. Department of Radiology, Seoul National University College of Medicine, 28, Yongon-dong, Chongno-gu, Seoul, 110-744, Korea

    Seunghyun Lee, Seung Hong Choi, Inseon Ryoo, Tae Jin Yoon, Ji-Hoon Kim & Chul-Ho Sohn

  2. Center for Nanoparticle Research, Institute for Basic Science, and School of Chemical and Biological Engineering, Seoul National University, Seoul, 151-742, Korea

    Seung Hong Choi

  3. Department of Internal Medicine, Cancer Research Institute, Seoul National University College of Medicine, 28, Yongon-dong, Chongno-gu, Seoul, 110-744, Korea

    Tae Min Kim & Se-Hoon Lee

  4. Department of Neurosurgery, Seoul National University College of Medicine, 28, Yongon-dong, Chongno-gu, Seoul, 110-744, Korea

    Chul-Kee Park

  5. Department of Pathology, Seoul National University College of Medicine, 28, Yongon-dong, Chongno-gu, Seoul, 110-744, Korea

    Sung-Hye Park

  6. Department of Radiation Oncology, Cancer Research Institute, Seoul National University College of Medicine, 28, Yongon-dong, Chongno-gu, Seoul, 110-744, Korea

    Il Han Kim

Authors
  1. Seunghyun Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Seung Hong Choi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Inseon Ryoo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tae Jin Yoon
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tae Min Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Se-Hoon Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Chul-Kee Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ji-Hoon Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Chul-Ho Sohn
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Sung-Hye Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Il Han Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Seung Hong Choi.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 27 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, S., Choi, S.H., Ryoo, I. 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 Neurooncol 121, 141–150 (2015). https://doi.org/10.1007/s11060-014-1614-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11060-014-1614-z

Keywords

Search

Navigation