Skip to main content
SpringerLink
Log in

Combining hyperintense FLAIR rim and radiological features in identifying IDH mutant 1p/19q non-codeleted lower-grade glioma

  • Molecular Imaging
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

Even very small residual tumors of IDH mutant 1p/19q non-codeleted (IDHmut-Noncodel) astrocytoma could have a significantly negative impact on survival; thus, accurate preoperative diagnosis is of utmost importance to guide aggressive tumor resection strategy for this subtype. This study aimed to diagnose IDHmut-Noncodel from IDH mutant 1p/19q codeleted (IDHmut-Codel) and IDH wild-type gliomas by preoperative MRI and CT to guide surgical plan-making.

Methods

Consecutive adult patients diagnosed with diffuse lower-grade glioma (LGG, histological grade 2–3) from December 1, 2013 to December 31, 2020, were retrospectively included in this study. Clinical and radiological features were recorded and analyzed. Patients were divided into cohort A and cohort B for training and validation based on the operation date (2:1).

Results

A total of 585 patients were included in this study (cohort A, 390; cohort B, 195). The hyperintense FLAIR rim with hypointense core (hyperFLAIRrim) was a more sensitive sign than T2-FLAIR mismatch (T2FM) in defining IDHmut-Noncodel astrocytoma (sensitivity in cohort A: 0.713, 0.539, respectively; in cohort B: 0.713, 0.489, respectively) without compromised specificity (all 1.00). The hyperFLAIRrim, higher rADC, homogenous pattern on T2WI, non-calcification, and younger age were the most important factors associated with IDHmut-Noncodel astrocytoma. Combining these factors, the random forest model showed the best predictive ability.

Conclusion

The hyperFLAIRrim sign was a specific and more sensitive sign in diagnosing IDHmut-Noncodel astrocytoma. Combining hyperFLAIRrim, higher rADC, homogenous pattern, non-calcification, and younger age could precisely predict glioma subtype for subsequent surgical plan-making.

Key Points

• A single hyperintense FLAIR rim (hyperFLAIRrim) sign with a hypointense core, regardless of T2 appearance, was more sensitive than T2FM in diagnosing IDHmut-Noncodel astrocytoma with high specificity.

• The higher rADC value, homogenous pattern on T2WI, non-calcification, and younger age have a close relationship with IDHmut-Noncodel astrocytoma.

• Neurosurgeons should perform a more aggressive resection strategy to prolong survival for radiologically indicated IDHmut-Noncodel astrocytoma. Our study provided a usable, practicable, and reliable protocol for neurosurgeons to make an individualized surgical strategy.

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

ADC:

Apparent diffusion coefficient

AUC:

Area under the curve

hyperFLAIRrim:

Hyperintense FLAIR rim

IDH:

Isocitrate dehydrogenase

LGG:

Lower-grade glioma

MGMT:

O6-Methylguanine-DNA methyltransferase

NPV:

Negative predictive value

PPV:

Positive predictive value

ROC curve:

Receiver operating characteristic curve

T2FM:

T2-FLAIR mismatch

References

  1. 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 

  2. Louis DN, Perry A, Wesseling P et al (2021) The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro Oncol 23:1231–1251

    Article  CAS  Google Scholar 

  3. Lombardi G, Barresi V, Castellano A et al (2020) Clinical management of diffuse low-grade gliomas. Cancers (Basel). https://doi.org/10.3390/cancers12103008

    Article  PubMed Central  Google Scholar 

  4. Youssef G, Miller JJ (2020) Lower grade gliomas. Curr Neurol Neurosci Rep. https://doi.org/10.1007/s11910-020-01040-8

    Article  PubMed  PubMed Central  Google Scholar 

  5. Patel SH, Bansal AG, Young EB et al (2019) Extent of surgical resection in lower-grade gliomas: differential impact based on molecular subtype. AJNR Am J Neuroradiol 40:1149–1155

    Article  CAS  Google Scholar 

  6. Wijnenga MMJ, French PJ, Dubbink HJ et al (2018) The impact of surgery in molecularly defined low-grade glioma: an integrated clinical, radiological, and molecular analysis. Neuro Oncol 20:103–112

    Article  CAS  Google Scholar 

  7. Jiang H, Cui Y, Liu X, Ren X, Li M, Lin S (2019) Proliferation-dominant high-grade astrocytoma: survival benefit associated with extensive resection of FLAIR abnormality region. J Neurosurg 132:998–1005

    Article  Google Scholar 

  8. Rossi M, Gay L, Ambrogi F et al (2021) Association of supratotal resection with progression-free survival, malignant transformation, and overall survival in lower-grade gliomas. Neuro Oncol 23:812–826

    Article  Google Scholar 

  9. Patel SH, Poisson LM, Brat DJ et al (2017) T2-FLAIR mismatch, an imaging biomarker for IDH and 1p/19q status in lower-grade gliomas: a TCGA/TCIA project. Clin Cancer Res 23:6078–6085

    Article  CAS  Google Scholar 

  10. Throckmorton P, Graber JJ (2020) T2-FLAIR mismatch in isocitrate dehydrogenase mutant astrocytomas: variability and evolution. Neurology 95:e1582–e1589

    Article  CAS  Google Scholar 

  11. Li M, Ren X, Jiang H et al (2019) Supratentorial high-grade astrocytoma with leptomeningeal spread to the fourth ventricle: a lethal dissemination with dismal prognosis. J Neurooncol 142:253–261

    Article  CAS  Google Scholar 

  12. Li M, Ren X, Dong G et al (2021) Distinguishing pseudoprogression from true early progression in isocitrate dehydrogenase wild-type glioblastoma by interrogating clinical, radiological, and molecular features. Front Oncol. https://doi.org/10.3389/fonc.2021.627325

    Article  PubMed  PubMed Central  Google Scholar 

  13. Li M, Dong G, Zhang W et al (2021) Combining MGMT promoter pyrosequencing and protein expression to optimize prognosis stratification in glioblastoma. Cancer Sci 112:3699–3710

    Article  CAS  Google Scholar 

  14. Yushkevich P, Piven J, Hazlett H et al (2006) User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage 31:1116–1128

    Article  Google Scholar 

  15. Xiong J, Tan W, Wen J et al (2016) Combination of diffusion tensor imaging and conventional MRI correlates with isocitrate dehydrogenase 1/2 mutations but not 1p/19q genotyping in oligodendroglial tumours. Eur Radiol 26:1705–1715

    Article  Google Scholar 

  16. 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

    Article  CAS  Google Scholar 

  17. Kawaguchi T, Sonoda Y, Shibahara I et al (2016) Impact of gross total resection in patients with WHO grade III glioma harboring the IDH 1/2 mutation without the 1p/19q co-deletion. J Neurooncol 129:505–514

    Article  CAS  Google Scholar 

  18. Garton ALA, Kinslow CJ, Rae AI et al (2020) Extent of resection, molecular signature, and survival in 1p19q-codeleted gliomas. J Neurosurg 134:1357–1367

    Article  Google Scholar 

  19. Ding X, Wang Z, Chen D et al (2018) The prognostic value of maximal surgical resection is attenuated in oligodendroglioma subgroups of adult diffuse glioma: a multicenter retrospective study. J Neurooncol 140:591–603

    Article  Google Scholar 

  20. Lasocki A, Gaillard F, Gorelik A, Gonzales M (2018) MRI features can predict 1p/19q status in intracranial gliomas. AJNR Am J Neuroradiol 39:687–692

    Article  CAS  Google Scholar 

  21. Foltyn M, Nieto Taborda KN, Neuberger U et al (2020) T2/FLAIR-mismatch sign for noninvasive detection of IDH-mutant 1p/19q non-codeleted gliomas: validity and pathophysiology. Neurooncol Adv. https://doi.org/10.1093/noajnl/vdaa004

    Article  PubMed  PubMed Central  Google Scholar 

  22. Broen MPG, Smits M, Wijnenga MMJ et al (2018) The T2-FLAIR mismatch sign as an imaging marker for non-enhancing IDH-mutant, 1p/19q-intact lower-grade glioma: a validation study. Neuro Oncol 20:1393–1399

    Article  CAS  Google Scholar 

  23. Batchala PP, Muttikkal TJE, Donahue JH et al (2019) Neuroimaging-based classification algorithm for predicting 1p/19q-codeletion status in IDH-mutant lower grade gliomas. AJNR Am J Neuroradiol 40:426–432

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Aliotta E, Dutta SW, Feng X et al (2020) Automated apparent diffusion coefficient analysis for genotype prediction in lower grade glioma: association with the T2-FLAIR mismatch sign. J Neurooncol 149:325–335

    Article  CAS  Google Scholar 

  25. Lee MK, Park JE, Jo Y, Park SY, Kim SJ, Kim HS (2020) Advanced imaging parameters improve the prediction of diffuse lower-grade gliomas subtype, IDH mutant with no 1p19q codeletion: added value to the T2/FLAIR mismatch sign. Eur Radiol 30:844–854

    Article  CAS  Google Scholar 

  26. Corell A, Ferreyra Vega S, Hoefling N et al (2020) The clinical significance of the T2-FLAIR mismatch sign in grade II and III gliomas: a population-based study. BMC Cancer. https://doi.org/10.1186/s12885-020-06951-w

    Article  PubMed  PubMed Central  Google Scholar 

  27. Deguchi S, Oishi T, Mitsuya K et al (2020) Clinicopathological analysis of T2-FLAIR mismatch sign in lower-grade gliomas. Sci Rep. https://doi.org/10.1038/s41598-020-67244-7

    Article  PubMed  PubMed Central  Google Scholar 

  28. Juratli TA, Tummala SS, Riedl A et al (2019) Radiographic assessment of contrast enhancement and T2/FLAIR mismatch sign in lower grade gliomas: correlation with molecular groups. J Neurooncol 141:327–335

    Article  CAS  Google Scholar 

  29. Kapsalaki EZ, Brotis AG, Tsikrika A et al (2020) The role of the T2-FLAIR mismatch sign as an imaging marker of IDH status in a mixed population of low- and high-grade gliomas. Brain Sci. https://doi.org/10.3390/brainsci10110874

    Article  PubMed  PubMed Central  Google Scholar 

  30. Chen L, Liu M, Bao J et al (2013) The correlation between apparent diffusion coefficient and tumor cellularity in patients: a meta-analysis. PLoS One. https://doi.org/10.1371/journal.pone.0079008

  31. Surov A, Meyer H, Wienke A (2017) Correlation between apparent diffusion coefficient (ADC) and cellularity is different in several tumors: a meta-analysis. Oncotarget 8:59492–59499

    Article  Google Scholar 

  32. Surov A, Meyer HJ, Wienke A (2017) Correlation between minimum apparent diffusion coefficient (ADCmin) and tumor cellularity: a meta-analysis. Anticancer Res 37:3807–3810

    CAS  PubMed  Google Scholar 

  33. Jenkinson MD, Smith TS, Brodbelt AR, Joyce KA, Warnke PC, Walker C (2007) Apparent diffusion coefficients in oligodendroglial tumors characterized by genotype. J Magn Reson Imaging 26:1405–1412

    Article  Google Scholar 

  34. Kim M, Jung SY, Park JE et al (2020) Diffusion- and perfusion-weighted MRI radiomics model may predict isocitrate dehydrogenase (IDH) mutation and tumor aggressiveness in diffuse lower grade glioma. Eur Radiol 30:2142–2151

    Article  Google Scholar 

  35. Aliotta E, Nourzadeh H, Batchala PP et al (2019) Molecular subtype classification in lower-grade glioma with accelerated DTI. AJNR Am J Neuroradiol 40:1458–1463

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Wu CC, Jain R, Radmanesh A et al (2018) Predicting genotype and survival in glioma using standard clinical MR imaging apparent diffusion coefficient images: a pilot study from The Cancer Genome Atlas. AJNR Am J Neuroradiol 39:1814–1820

    Article  Google Scholar 

  37. Thust SC, Hassanein S, Bisdas S et al (2018) Apparent diffusion coefficient for molecular subtyping of non-gadolinium-enhancing WHO grade II/III glioma: volumetric segmentation versus two-dimensional region of interest analysis. Eur Radiol 28:3779–3788

    Article  CAS  Google Scholar 

  38. 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 

  39. van Lent DI, van Baarsen KM, Snijders TJ, Robe P (2020) Radiological differences between subtypes of WHO 2016 grade II-III gliomas: a systematic review and meta-analysis. Neurooncol Adv. https://doi.org/10.1093/noajnl/vdaa044

    Article  PubMed  PubMed Central  Google Scholar 

  40. Saito T, Muragaki Y, Maruyama T et al (2016) Calcification on CT is a simple and valuable preoperative indicator of 1p/19q loss of heterozygosity in supratentorial brain tumors that are suspected grade II and III gliomas. Brain Tumor Pathol 33:175–182

    Article  CAS  Google Scholar 

  41. Kiroglu Y, Calli C, Karabulut N, Oncel C (2010) Intracranial calcifications on CT. Diagn Interv Radiol 16:263–269

    PubMed  Google Scholar 

  42. Bitton RR, Pauly KR (2014) MR-acoustic radiation force imaging (MR-ARFI) and susceptibility weighted imaging (SWI) to visualize calcifications in ex vivo swine brain. J Magn Reson Imaging 39:1294–1300

    Article  Google Scholar 

  43. Saade C, Najem E, Asmar K, Salman R, El Achkar B, Naffaa L (2019) Intracranial calcifications on CT: an updated review. J Radiol Case Rep 13:1–18

    PubMed  PubMed Central  Google Scholar 

  44. Smits M (2016) Imaging of oligodendroglioma. Br J Radiol. https://doi.org/10.1259/bjr.20150857

    Article  PubMed  PubMed Central  Google Scholar 

  45. Zhao K, Sun G, Wang Q et al (2021) The diagnostic value of conventional MRI and CT features in the identification of the IDH1-mutant and 1p/19q co-deletion in WHO grade II gliomas. Acad Radiol 28:e189–e198

    Article  Google Scholar 

  46. Waitkus MS, Diplas BH, Yan H (2018) Biological role and therapeutic potential of IDH mutations in cancer. Cancer Cell 34:186–195

    Article  CAS  Google Scholar 

  47. Suh CH, Kim HS, Jung SC, Choi CG, Kim SJ (2019) Imaging prediction of isocitrate dehydrogenase (IDH) mutation in patients with glioma: a systemic review and meta-analysis. Eur Radiol 29:745–758

    Article  Google Scholar 

  48. Xu H, Xia YK, Li CJ et al (2019) Rapid diagnosis of IDH1-mutated gliomas by 2-HG detection with gas chromatography mass spectrometry. Lab Invest 99:588–598

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors sincerely thank the patients and their families for their participation in the present study. We acknowledge Dr. Gehong Dong and Dr. Weiwei Zhang (Beijing Tiantan Hospital) for collecting and interpreting the pathology data.

Funding

This study was supported by the National Natural Science Foundation of China (81571632&81771309).

Author information

Authors and Affiliations

  1. Department of Neurosurgical Oncology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China

    Mingxiao Li, Xiaohui Ren, Shaoping Shen, Chuanwei Yang, Xuzhe Zhao, Qinghui Zhu, Yong Cui & Song Lin

  2. Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China

    Mingxiao Li, Xiaohui Ren, Shaoping Shen, Chuanwei Yang, Xuzhe Zhao, Qinghui Zhu, Yong Cui & Song Lin

  3. Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China

    Xuzhu Chen

  4. Department of Radiology, Peking University Cancer Hospital, Beijing, China

    Jincheng Wang

  5. Department of Neurosurgery, Peking University Third Hospital, Peking University, Beijing, China

    Haihui Jiang

  6. Center of Brain Tumor, Institute for Brain Disorders and Beijing Key Laboratory of Brain Tumor, Beijing, China

    Song Lin

Authors
  1. Mingxiao Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaohui Ren
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xuzhu Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jincheng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shaoping Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Haihui Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Chuanwei Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Xuzhe Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Qinghui Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Yong Cui
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Song Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Song Lin.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Song Lin, MD., PhD.

Conflict of interest

The authors declare no potential conflicts of interest.

Statistics and biometry

Mingxiao Li and Jincheng Wang have significant statistical expertise.

Informed consent

Written informed consent was waived by the institutional review board.

Ethical approval

Institutional review board approval was obtained.

Methodology

• retrospective

• observational

• performed at one institution

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 13852 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, M., Ren, X., Chen, X. et al. Combining hyperintense FLAIR rim and radiological features in identifying IDH mutant 1p/19q non-codeleted lower-grade glioma. Eur Radiol 32, 3869–3879 (2022). https://doi.org/10.1007/s00330-021-08500-w

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-021-08500-w

Keywords

Search

Navigation