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Increased intratumoral infiltration in IDH wild-type lower-grade gliomas observed with diffusion tensor imaging

  • Clinical Study
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Abstract

Purpose

Diffuse lower grade gliomas (LGG) with isocitrate dehydrogenase (IDH) gene mutations (IDHMUT) have a distinct survival advantage compared with IDH wild-type (IDHWT) cases but the mechanism underlying this disparity is not well understood. Diffusion Tensor Imaging (DTI) has identified infiltrated non-enhancing tumor regions that are characterized by low isotropic (p) and high anisotropic (q) diffusion tensor components that associate with poor survival in glioblastoma. We hypothesized that similar regions are more prevalent in IDHWT (vs. IDHMUT) LGG.

Methods

p and q maps were reconstructed from preoperative DTI scans in N = 41 LGG patients with known IDH mutation and 1p/19q codeletion status. Enhancing and non-enhancing tumor volumes were autosegmented from standard (non-DTI) MRI scans. Percentage non-enhancing tumor volumes exhibiting low p and high q (Vinf) were then determined using threshold values (p = 2 × 10−3mm2/s, q = 3 × 10–4 mm2/s) and compared between IDHWT and IDHMUT LGG, and between IDHMUT LGG with and without 1p/19q codeletion.

Results

Vinf volumes were significantly larger in IDHWT LGG than in IDHMUT LGG (35.4 ± 18.3% vs. 15.9 ± 7.6%, P < 0.001). Vinf volumes did not significantly differ between IDHMUT LGG with and without 1p/19q codeletion (17.1 ± 9.5% vs. 14.8 ± 5.8%, P = 1.0).

Conclusion

IDHWT LGG exhibited larger volumes with suppressed isotropic diffusion (p) and high anisotropic diffusion (q) which reflects regions with increased cell density but non-disrupted neuronal structures. This may indicate a greater prevalence of infiltrative tumor in IDHWT LGG.

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References

  1. Network TCGAR (2015) Comprehensive, integrative genomic analysis of diffuse lower-grade gliomas. N Engl J Med 372(26):2481–2498

    Article  Google Scholar 

  2. Eckel-Passow JE, Lachance DH, Molinaro AM, Walsh KM, Decker PA, Sicotte H et al (2015) Glioma groups based on 1p/19q, IDH, and TERT promoter mutations in tumors. N Engl J Med 372(26):2499–2508

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Ceccarelli M, Barthel FP, Malta TM, Sabedot TS, Salama SR, Murray BA et al (2016) Molecular profiling reveals biologically discrete subsets and pathways of progression in diffuse glioma. Cell 164(3):550–563

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Wijnenga MMJ, French PJ, Dubbink HJ, Dinjens WNM, Atmodimedjo PN, Kros JM et al (2018) The impact of surgery in molecularly defined low-grade glioma: an integrated clinical, radiological, and molecular analysis. Neuro Oncol 20(1):103–112

    Article  CAS  PubMed  Google Scholar 

  5. Beiko J, Suki D, Hess KR, Fox BD, Cheung V, Cabral M et al (2014) IDH1 mutant malignant astrocytomas are more amenable to surgical resection and have a survival benefit associated with maximal surgical resection. Neuro Oncol 16(1):81–91

    Article  CAS  PubMed  Google Scholar 

  6. Price SJ, Jena R, Burnet NG, Hutchinson PJ, Dean AF, Peña A et al (2006) Improved delineation of glioma margins and regions of infiltration with the use of diffusion tensor imaging: an image-guided biopsy study. Am J Neuroradiol 27(9):1969–1974

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Price SJ, Jena R, Burnet NG, Carpenter TA, Pickard JD, Gillard JH (2007) Predicting patterns of glioma recurrence using diffusion tensor imaging. Eur Radiol 17(7):1675–1684

    Article  PubMed  Google Scholar 

  8. Bette S, Huber T, Gempt J, Boeckh-Behrens T, Wiestler B, Kehl V et al (2017) Local fractional anisotropy is reduced in areas with tumor recurrence in glioblastoma. Radiology 283(2):499–507

    Article  PubMed  Google Scholar 

  9. Park YW, Han K, Ahn SS, Choi YS, Chang JH, Kim SH et al (2018) Whole-tumor histogram and texture analyses of DTI for evaluation of IDH1-Mutation and 1p/19q-codeletion status in world health organization grade II gliomas. Am J Neuroradiol 39(4):693–698

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Xiong J, Tan W, Wen J, Pan J, Wang Y, Zhang 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(6):1705–1715

    Article  PubMed  Google Scholar 

  11. Peña A, Green HAL, Carpenter TA, Price SJ, Pickard JD, Gillard JH (2006) Enhanced visualization and quantification of magnetic resonance diffusion tensor imaging using the p : q tensor decomposition. Br J Radiol 79(938):101–109

    Article  PubMed  Google Scholar 

  12. Ellingson BM, Malkin MG, Rand SD, Connelly JM, Quinsey C, LaViolette PS et al (2010) Validation of functional diffusion maps (fDMs) as a biomarker for human glioma cellularity. J Magn Reson Imaging 31(3):538–548

    Article  PubMed  PubMed Central  Google Scholar 

  13. Gupta RK, Cloughesy TF, Sinha U, Garakian J, Lazareff J, Rubino G et al (2000) Relationships between choline magnetic resonance spectroscopy, apparent diffusion coefficient and quantitative histopathology in human glioma. J Neurooncol 50(3):215–226

    Article  CAS  PubMed  Google Scholar 

  14. Sugahara T, Korogi Y, Kochi M, Ikushima I, Shigematu Y, Hirai T et al (1999) Usefulness of diffusion-weighted MRI with echo-planar technique in the evaluation of cellularity in gliomas. J Magn Reson Imaging 9(1):53–60

    Article  CAS  PubMed  Google Scholar 

  15. Price SJ, Peña A, Burnet NG, Jena R, Green HAL, Carpenter TA et al (2004) Tissue signature characterisation of diffusion tensor abnormalities in cerebral gliomas. Eur Radiol 14(10):1909–1917

    Article  PubMed  Google Scholar 

  16. Mohsen LA, Shi V, Jena R, Gillard JH, Price SJ (2013) Diffusion tensor invasive phenotypes can predict progression-free survival in glioblastomas. Br J Neurosurg 27(4):436–441

    Article  CAS  PubMed  Google Scholar 

  17. Price SJ, Lupson VC, Yan J-L, Boonzaier NR, Larkin TJ, Liu H et al (2016) Less invasive phenotype found in isocitrate dehydrogenase–mutated glioblastomas than in isocitrate dehydrogenase wild-type glioblastomas: a diffusion-tensor imaging study. Radiology 283(1):215–221

    Article  PubMed  Google Scholar 

  18. Li C, Wang S, Yan J-L, Piper RJ, Liu H, Torheim T et al (2018) Intratumoral heterogeneity of glioblastoma infiltration revealed by joint histogram analysis of diffusion tensor imaging. Neurosurgery. https://doi.org/10.1093/neuro/nyy388

    Article  PubMed  Google Scholar 

  19. Capper D, Weissert S, Balss J, Habel A, Meyer J, Jäger D et al (2010) Characterization of R132H mutation-specific IDH1 antibody binding in brain tumors. Brain Pathol 20(1):245–254

    Article  CAS  PubMed  Google Scholar 

  20. Felsberg J, Wolter M, Seul H, Friedensdorf B, Göppert M, Sabel MC et al (2010) Rapid and sensitive assessment of the IDH1 and IDH2 mutation status in cerebral gliomas based on DNA pyrosequencing. Acta Neuropathol 119(4):501–507

    Article  CAS  PubMed  Google Scholar 

  21. Riemenschneider MJ, Jeuken JWM, Wesseling P, Reifenberger G (2010) Molecular diagnostics of gliomas: state of the art. Acta Neuropathol 120(5):567–584

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Foster JM, Oumie A, Togneri FS, Vasques FR, Hau D, Taylor M et al (2015) Cross-laboratory validation of the OncoScan® FFPE assay, a multiplex tool for whole genome tumour profiling. BMC Med Genom 8(1):5

    Article  Google Scholar 

  23. Kamnitsas K, Ledig C, Newcombe VFJ, Simpson JP, Kane AD, Menon DK et al (2017) Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation. Med Image Anal 36:61–78

    Article  PubMed  Google Scholar 

  24. Rathore S, Bakas S, Pati S, Akbari H, Kalarot R, Sridharan P et al (2018) Brain cancer imaging phenomics toolkit (brain-CaPTk): an interactive platform for quantitative analysis of glioblastoma. Brainlesion 10670:133–145

    PubMed  PubMed Central  Google Scholar 

  25. Scherer HJ (1938) Structural development in gliomas. Am J Cancer 34(3):333–351

    Google Scholar 

  26. Beppu T, Inoue T, Shibata Y, Yamada N, Kurose A, Ogasawara K et al (2004) Fractional anisotropy value by diffusion tensor magnetic resonance imaging as a predictor of cell density and proliferation activity of glioblastomas. Surg Neurol 63(1):56–61

    Article  Google Scholar 

  27. Bralten LBC, Kloosterhof NK, Balvers R, Sacchetti A, Lapre L, Lamfers M et al (2011) IDH1 R132H decreases proliferation of glioma cell lines in vitro and in vivo. Ann Neurol 69(3):455–463

    Article  CAS  PubMed  Google Scholar 

  28. Baldock AL, Yagle K, Born DE, Ahn S, Trister AD, Neal M et al (2014) Invasion and proliferation kinetics in enhancing gliomas predict IDH1 mutation status. Neuro Oncol 16(6):779–786

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Leu K, Ott GA, Lai A, Nghiemphu PL, Pope WB, Yong WH et al (2017) Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II–III diffuse gliomas. J Neurooncol 134(1):177–188

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Chenevert TL, Stegman LD, Taylor JMG, Robertson PL, Greenberg HS, Rehemtulla A et al (2000) Diffusion magnetic resonance imaging: an early surrogate marker of therapeutic efficacy in brain tumors. J Natl Cancer Inst 92(24):2029–2036

    Article  CAS  PubMed  Google Scholar 

  31. McConville P, Hambardzumyan D, Moody JB, Leopold WR, Kreger AR, Woolliscroft MJ et al (2007) Magnetic resonance imaging determination of tumor grade and early response to temozolomide in a genetically engineered mouse model of glioma. Clin Cancer Res 13(10):2897–2904

    Article  CAS  PubMed  Google Scholar 

  32. Gerstner ER, Chen P-J, Wen PY, Jain RK, Batchelor TT, Sorensen G (2010) Infiltrative patterns of glioblastoma spread detected via diffusion MRI after treatment with cediranib. Neuro Oncol 12(5):466–472

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Zhang M, Gulotta B, Thomas A, Kaley T, Karimi S, Gavrilovic I et al (2016) Large-volume low apparent diffusion coefficient lesions predict poor survival in bevacizumab-treated glioblastoma patients. Neuro Oncol 18(5):735–743

    Article  CAS  PubMed  Google Scholar 

  34. Wu C-C, Jain R, Radmanesh A, Poisson LM, Guo W-Y, Zagzag D 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(10):1814–1820

    Article  PubMed  PubMed Central  Google Scholar 

  35. Huisman TAGM, Loenneker T, Barta G, Bellemann ME, Hennig J, Fischer JE et al (2006) Quantitative diffusion tensor MR imaging of the brain: field strength related variance of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) scalars. Eur Radiol 16(8):1651–1658

    Article  PubMed  Google Scholar 

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Funding

S.H.P.: RSNA Research Scholar Grant (RSCH1819).

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Authors and Affiliations

  1. Department of Radiation Oncology, University of Virginia, Charlottesville, VA, 22908, USA

    Eric Aliotta

  2. Department of Radiology, University of Virginia, Charlottesville, VA, 22908, USA

    Prem P. Batchala, Jason T. Druzgal, Sugoto Mukherjee & Sohil H. Patel

  3. Department of Neurology, University of Virginia, Charlottesville, VA, 22908, USA

    David Schiff

  4. Department of Pathology (Neuropathology), University of Virginia, Charlottesville, VA, 22908, USA

    Beatriz M. Lopes

  5. Radiological Physics, University of Virginia, 1335 Lee St, Box 800375, Charlottesville, VA, 22908, USA

    Eric Aliotta

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  1. Eric Aliotta
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Correspondence to Eric Aliotta.

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Aliotta, E., Batchala, P.P., Schiff, D. et al. Increased intratumoral infiltration in IDH wild-type lower-grade gliomas observed with diffusion tensor imaging. J Neurooncol 145, 257–263 (2019). https://doi.org/10.1007/s11060-019-03291-z

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  • DOI: https://doi.org/10.1007/s11060-019-03291-z

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