Skip to main content
SpringerLink
Log in

Radiogenomics correlation between MR imaging features and major genetic profiles in glioblastoma

  • Neuro
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To assess the association between MR imaging features and major genomic profiles in glioblastoma.

Methods

Qualitative and quantitative imaging features such as volumetrics and histogram analysis from normalised CBV (nCBV) and ADC (nADC) were evaluated based on both T2WI and CET1WI. The imaging parameters of different genetic profile groups were compared and regression analyses were used for identifying imaging-molecular associations. Progression-free survival (PFS) was analysed by a Kaplan-Meier test and Cox proportional hazards model.

Results

An IDH mutation was observed in 18/176 patients, and ATRX loss was positive in 17/158 of the IDH-wt cases. The IDH-mut group showed a larger volume on T2WI and a higher volume ratio between T2WI and CET1WI than the IDH-wt group (p < 0.05). In the IDH-mut group, higher mean nADC values were observed compared with the IDH-wt tumours (p < 0.05). Among the IDH-wt tumours, IDH-wt, ATRX-loss tumours revealed higher 5th percentile nADC values than the IDH-wt, ATRX-noloss tumours (p = 0.03). PFS was the longest in the IDH-mut group, followed by the IDH-wt, ATRX-loss groups and the IDH-wt, ATRX-noloss groups, consecutively (p < 0.05). We found significant associations of PFS with the genetic profiles and imaging parameters.

Conclusion

Major genetic profiles of glioblastoma showed a significant association with MR imaging features, along with some genetic profiles, which are independent prognostic parameters for GBM.

Key Points

• Significant correlation exists between radiological parameters such as volumetric and ADC values and major genomic profiles such as IDH mutation and ATRX loss status

• Radiological parameters such as the ADC value were feasible predictors of glioblastoma patients’ prognosis

• Imaging features can predict major genomic profiles of the tumours and the prognosis of glioblastoma patients

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
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

ATRX:

Alpha-thalassemia/mental retardation syndrome X-linked

CBV:

Cerebral blood volume

CET1WI:

Contrast-enhanced T1-weighted imaging

FLAIR:

Fluid attenuation inversion recovery

GBM:

Glioblastoma

IDH:

Isocitrate dehydrogenase

T2WI:

T2-weighted imaging

References

  1. Vigneswaran K, Neill S, Hadjipanayis CG (2015) Beyond the World Health Organization grading of infiltrating gliomas: advances in the molecular genetics of glioma classification. Ann Transl Med 3:95

    PubMed  PubMed Central  Google Scholar 

  2. Zinn PO, Sathyan P, Mahajan B et al (2012) A novel volume-age-KPS (VAK) glioblastoma classification identifies a prognostic cognate microRNA-gene signature. PLoS One 7:e41522

    Article  CAS  Google Scholar 

  3. Verhaak RG, Hoadley KA, Purdom E et al (2010) Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell 17:98–110

    Article  CAS  Google Scholar 

  4. Cancer Genome Atlas Research N (2008) Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 455:1061–1068

    Article  Google Scholar 

  5. Belden CJ, Valdes PA, Ran C et al (2011) Genetics of glioblastoma: a window into its imaging and histopathologic variability. Radiographics 31:1717–1740

    Article  Google Scholar 

  6. Parsons DW, Jones S, Zhang X et al (2008) An integrated genomic analysis of human glioblastoma multiforme. Science 321:1807–1812

    Article  CAS  Google Scholar 

  7. Frattini V, Trifonov V, Chan JM et al (2013) The integrated landscape of driver genomic alterations in glioblastoma. Nat Genet 45:1141–1149

    Article  CAS  Google Scholar 

  8. Yan H, Parsons DW, Jin G et al (2009) IDH1 and IDH2 mutations in gliomas. N Engl J Med 360:765–773

    Article  CAS  Google Scholar 

  9. Sanson M, Marie Y, Paris S et al (2009) Isocitrate dehydrogenase 1 codon 132 mutation is an important prognostic biomarker in gliomas. J Clin Oncol 27:4150–4154

    Article  CAS  Google Scholar 

  10. Stupp R, Hegi ME, Mason WP et al (2009) Effects of radiotherapy with concomitant and adjuvant temozolomide versus radiotherapy alone on survival in glioblastoma in a randomised phase III study: 5-year analysis of the EORTC-NCIC trial. Lancet Oncol 10:459–466

    Article  CAS  Google Scholar 

  11. Aldape K, Burger PC, Perry A (2007) Clinicopathologic aspects of 1p/19q loss and the diagnosis of oligodendroglioma. Arch Pathol Lab Med 131:242–251

    CAS  PubMed  Google Scholar 

  12. Hill C, Hunter SB, Brat DJ (2003) Genetic markers in glioblastoma: prognostic significance and future therapeutic implications. Adv Anat Pathol 10:212–217

    Article  CAS  Google Scholar 

  13. Jiao Y, Killela PJ, Reitman ZJ et al (2012) Frequent ATRX, CIC, FUBP1 and IDH1 mutations refine the classification of malignant gliomas. Oncotarget 3:709–722

    Article  Google Scholar 

  14. Kannan K, Inagaki A, Silber J et al (2012) Whole-exome sequencing identifies ATRX mutation as a key molecular determinant in lower-grade glioma. Oncotarget 3:1194–1203

    Article  Google Scholar 

  15. Reuss DE, Sahm F, Schrimpf D et al (2015) ATRX and IDH1-R132H immunohistochemistry with subsequent copy number analysis and IDH sequencing as a basis for an "integrated" diagnostic approach for adult astrocytoma, oligodendroglioma and glioblastoma. Acta Neuropathol 129:133–146

    Article  CAS  Google Scholar 

  16. Koschmann C, Calinescu AA, Nunez FJ et al (2016) ATRX loss promotes tumor growth and impairs nonhomologous end joining DNA repair in glioma. Sci Transl Med 8:328ra328

    Article  Google Scholar 

  17. Wiestler B, Capper D, Holland-Letz T et al (2013) ATRX loss refines the classification of anaplastic gliomas and identifies a subgroup of IDH mutant astrocytic tumors with better prognosis. Acta Neuropathol 126:443–451

    Article  CAS  Google Scholar 

  18. Zinn PO, Colen RR (2013) Imaging genomic mapping in glioblastoma. Neurosurgery 60 Suppl 1:126–130

    Article  Google Scholar 

  19. Rees JH, Smirniotopoulos JG, Jones RV, Wong K (1996) Glioblastoma multiforme: radiologic-pathologic correlation. Radiographics 16:1413–1438 quiz 1462-1413

    Article  CAS  Google Scholar 

  20. Pope WB, Chen JH, Dong J et al (2008) Relationship between gene expression and enhancement in glioblastoma multiforme: exploratory DNA microarray analysis. Radiology 249:268–277

    Article  Google Scholar 

  21. Diehn M, Nardini C, Wang DS et al (2008) Identification of noninvasive imaging surrogates for brain tumor gene-expression modules. Proc Natl Acad Sci U S A 105:5213–5218

    Article  CAS  Google Scholar 

  22. Zinn PO, Mahmood Z, Elbanan MG, Colen RR (2015) Imaging genomics in gliomas. Cancer J 21:225–234

    Article  CAS  Google Scholar 

  23. Moton S, Elbanan M, Zinn PO, Colen RR (2015) Imaging genomics of glioblastoma: Biology, biomarkers, and breakthroughs. Top Magn Reson Imaging 24:155–163

    Article  Google Scholar 

  24. Jamshidi N, Diehn M, Bredel M, Kuo MD (2014) Illuminating radiogenomic characteristics of glioblastoma multiforme through integration of MR imaging, messenger RNA expression, and DNA copy number variation. Radiology 270:1–2

    Article  Google Scholar 

  25. Gevaert O, Mitchell LA, Achrol AS et al (2014) Glioblastoma multiforme: exploratory radiogenomic analysis by using quantitative image features. Radiology 273:168–174

    Article  Google Scholar 

  26. Gutman DA, Cooper LA, Hwang SN et al (2013) MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set. Radiology 267:560–569

    Article  Google Scholar 

  27. Wilson TA, Karajannis MA, Harter DH (2014) Glioblastoma multiforme: State of the art and future therapeutics. Surg Neurol Int 5:64

    Article  Google Scholar 

  28. Joe BN, Fukui MB, Meltzer CC et al (1999) Brain tumor volume measurement: comparison of manual and semiautomated methods. Radiology 212:811–816

    Article  CAS  Google Scholar 

  29. Busing KA, Kilian AK, Schaible T, Debus A, Weiss C, Neff KW (2008) Reliability and validity of MR image lung volume measurement in fetuses with congenital diaphragmatic hernia and in vitro lung models. Radiology 246:553–561

    Article  Google Scholar 

  30. Louis DN, Perry A, Reifenberger G et al (2016) The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. Acta Neuropathol 131:803–820

    Article  Google Scholar 

  31. Carrillo JA, Lai A, Nghiemphu PL et al (2012) Relationship between tumor enhancement, edema, IDH1 mutational status, MGMT promoter methylation, and survival in glioblastoma. AJNR Am J Neuroradiol 33:1349–1355

    Article  CAS  Google Scholar 

  32. Metellus P, Coulibaly B, Colin C et al (2010) Absence of IDH mutation identifies a novel radiologic and molecular subtype of WHO grade II gliomas with dismal prognosis. Acta Neuropathol 120:719–729

    Article  Google Scholar 

  33. Higano S, Yun X, Kumabe T et al (2006) Malignant astrocytic tumors: clinical importance of apparent diffusion coefficient in prediction of grade and prognosis. Radiology 241:839–846

    Article  Google Scholar 

  34. Kickingereder P, Sahm F, Radbruch A et al (2015) IDH mutation status is associated with a distinct hypoxia/angiogenesis transcriptome signature which is non-invasively predictable with rCBV imaging in human glioma. Sci Rep 5:16238

    Article  CAS  Google Scholar 

  35. Xing Z, Yang X, She D, Lin Y, Zhang Y, Cao D (2017) Noninvasive assessment of IDH mutational status in World Health Organization grade II and III astrocytomas using DWI and DSC-PWI combined with conventional MR imaging. AJNR Am J Neuroradiol 38:1138–1144

    Article  CAS  Google Scholar 

  36. Nobusawa S, Watanabe T, Kleihues P, Ohgaki H (2009) IDH1 mutations as molecular signature and predictive factor of secondary glioblastomas. Clin Cancer Res 15:6002–6007

    Article  CAS  Google Scholar 

  37. Stupp R, Mason WP, van den Bent MJ et al (2005) Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med 352:987–996

    Article  CAS  Google Scholar 

  38. Zhang K, Wang XQ, Zhou B, Zhang L (2013) The prognostic value of MGMT promoter methylation in glioblastoma multiforme: a meta-analysis. Fam Cancer 12:449–458

    Article  CAS  Google Scholar 

Download references

Funding

This study was supported by a grant from the Korea Healthcare Technology R&D Projects, Ministry for Health, Welfare & Family Affairs (HI16C1111), by the Bio & Medical Technology Development Program of the NRF funded by the Korean government, MSIP (NRF-2015M3A9A7029740), by the Brain Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2016M3C7A1914002), by the Creative-Pioneering Researchers Program through Seoul National University (SNU), and by Project Code (IBS-R006-D1).

Author information

Authors and Affiliations

  1. Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea

    Eun Kyoung Hong, Seung Hong Choi, Dong Jae Shin, Sang Won Jo, Roh-Eul Yoo, Koung Mi Kang, Tae Jin Yun, Ji-Hoon Kim & Chul-Ho Sohn

  2. Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea

    Seung Hong Choi

  3. Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul, Republic of Korea

    Seung Hong Choi

  4. Department of Pathology, Seoul National University Hospital, Seoul, Korea

    Sung-Hye Park & Jae-Kyung Won

  5. Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea

    Tae Min Kim

  6. Department of Neurosurgery, Seoul National University Hospital, Seoul, Korea

    Chul-Kee Park

  7. Department of Radiation Oncology, Seoul National University Hospital, Seoul, Korea

    Il Han Kim

  8. Department of Neurology, Seoul National University Hospital, Seoul, Korea

    Soon Tae Lee

Authors
  1. Eun Kyoung Hong
    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. Dong Jae Shin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sang Won Jo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Roh-Eul Yoo
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Koung Mi Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Tae Jin Yun
    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. Jae-Kyung Won
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Tae Min Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Chul-Kee Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Il Han Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Soon Tae Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Seung Hong Choi.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Seung Hong Choi.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• diagnostic or prognostic study

• performed at one institution

Electronic supplementary material

ESM 1

(DOCX 1122 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hong, E.K., Choi, S.H., Shin, D.J. et al. Radiogenomics correlation between MR imaging features and major genetic profiles in glioblastoma. Eur Radiol 28, 4350–4361 (2018). https://doi.org/10.1007/s00330-018-5400-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-018-5400-8

Keywords

Search

Navigation