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Differentiation between Glioblastoma and Solitary Metastasis: Morphologic Assessment by Conventional Brain MR Imaging and Diffusion-Weighted Imaging

  • Jung, Bo Young (Department of Radiology, Dongguk University Ilsan Hospital) ;
  • Lee, Eun Ja (Department of Radiology, Dongguk University Ilsan Hospital) ;
  • Bae, Jong Myon (Department of Preventive Medicine, Jeju National University School of Medicine) ;
  • Choi, Young Jae (Department of Radiology, Dongguk University Ilsan Hospital) ;
  • Lee, Eun Kyoung (Department of Radiology, Dongguk University Ilsan Hospital) ;
  • Kim, Dae Bong (Department of Radiology, Dongguk University Ilsan Hospital)
  • Received : 2019.12.08
  • Accepted : 2021.01.04
  • Published : 2021.03.30

Abstract

Purpose: Differentiating between glioblastoma and solitary metastasis is very important for the planning of further workup and treatment. We assessed the ability of various morphological parameters using conventional MRI and diffusion-based techniques to distinguish between glioblastomas and solitary metastases in tumoral and peritumoral regions. Materials and Methods: We included 38 patients with solitary brain tumors (21 glioblastomas, 17 solitary metastases). To find out if there were differences in the morphologic parameters of enhancing tumors, we analyzed their shape, margins, and enhancement patterns on postcontrast T1-weighted images. During analyses of peritumoral regions, we assessed the extent of peritumoral non-enhancing lesion on T2- and postcontrast T1-weighted images. We also aimed to detect peritumoral neoplastic cell infiltration by visual assessment of T2-weighted and diffusion-based images, including DWI, ADC maps, and exponential DWI, and evaluated which sequence depicted peritumoral neoplastic cell infiltration most clearly. Results: The shapes, margins, and enhancement patterns of tumors all significantly differentiated glioblastomas from metastases. Glioblastomas had an irregular shape, ill-defined margins, and a heterogeneous enhancement pattern; on the other hand, metastases had an ovoid or round shape, well-defined margins, and homogeneous enhancement. Metastases had significantly more extensive peritumoral T2 high signal intensity than glioblastomas had. In visual assessment of peritumoral neoplastic cell infiltration using T2-weighted and diffusion-based images, all sequences differed significantly between the two groups. Exponential DWI had the highest sensitivity for the diagnosis of both glioblastoma (100%) and metastasis (70.6%). A combination of exponential DWI and ADC maps was optimal for the depiction of peritumoral neoplastic cell infiltration in glioblastoma. Conclusion: In the differentiation of glioblastoma from solitary metastatic lesions, visual morphologic assessment of tumoral and peritumoral regions using conventional MRI and diffusion-based techniques can also offer diagnostic information.

Keywords

References

  1. Louis DN, Ohgaki H, Wiestler OD, et al. The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol 2007;114:97-109 https://doi.org/10.1007/s00401-007-0243-4
  2. Lee EJ, terBrugge K, Mikulis D, et al. Diagnostic value of peritumoral minimum apparent diffusion coefficient for differentiation of glioblastoma multiforme from solitary metastatic lesions. AJR Am J Roentgenol 2011;196:71-76 https://doi.org/10.2214/AJR.10.4752
  3. Law M, Cha S, Knopp EA, Johnson G, Arnett J, Litt AW. High-grade gliomas and solitary metastases: differentiation by using perfusion and proton spectroscopic MR imaging. Radiology 2002;222:715-721 https://doi.org/10.1148/radiol.2223010558
  4. Furnari FB, Fenton T, Bachoo RM, et al. Malignant astrocytic glioma: genetics, biology, and paths to treatment. Genes Dev 2007;21:2683-2710 https://doi.org/10.1101/gad.1596707
  5. Cha S, Lupo JM, Chen MH, et al. Differentiation of glioblastoma multiforme and single brain metastasis by peak height and percentage of signal intensity recovery derived from dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. AJNR Am J Neuroradiol 2007;28:1078-1084 https://doi.org/10.3174/ajnr.A0484
  6. Chiang IC, Kuo YT, Lu CY, et al. Distinction between highgrade gliomas and solitary metastases using peritumoral 3-T magnetic resonance spectroscopy, diffusion, and perfusion imagings. Neuroradiology 2004;46:619-627 https://doi.org/10.1007/s00234-004-1246-7
  7. Opstad KS, Murphy MM, Wilkins PR, Bell BA, Griffiths JR, Howe FA. Differentiation of metastases from high-grade gliomas using short echo time 1H spectroscopy. J Magn Reson Imaging 2004;20:187-192 https://doi.org/10.1002/jmri.20093
  8. Tang YM, Ngai S, Stuckey S. The solitary enhancing cerebral lesion: can FLAIR aid the differentiation between glioma and metastasis? AJNR Am J Neuroradiol 2006;27:609-611
  9. Ishimaru H, Morikawa M, Iwanaga S, Kaminogo M, Ochi M, Hayashi K. Differentiation between high-grade glioma and metastatic brain tumor using single-voxel proton MR spectroscopy. Eur Radiol 2001;11:1784-1791 https://doi.org/10.1007/s003300000814
  10. Cho SK, Na DG, Ryoo JW, et al. Perfusion MR imaging: clinical utility for the differential diagnosis of various brain tumors. Korean J Radiol 2002;3:171-179 https://doi.org/10.3348/kjr.2002.3.3.171
  11. Lee EJ, Ahn KJ, Lee EK, Lee YS, Kim DB. Potential role of advanced MRI techniques for the peritumoural region in differentiating glioblastoma multiforme and solitary metastatic lesions. Clin Radiol 2013;68:e689-697 https://doi.org/10.1016/j.crad.2013.06.021
  12. Lu S, Ahn D, Johnson G, Cha S. Peritumoral diffusion tensor imaging of high-grade gliomas and metastatic brain tumors. AJNR Am J Neuroradiol 2003;24:937-941
  13. Kelly PJ, Daumas-Duport C, Kispert DB, Kall BA, Scheithauer BW, Illig JJ. Imaging-based stereotaxic serial biopsies in untreated intracranial glial neoplasms. J Neurosurg 1987;66:865-874 https://doi.org/10.3171/jns.1987.66.6.0865
  14. Strugar J, Rothbart D, Harrington W, Criscuolo GR. Vascular permeability factor in brain metastases: correlation with vasogenic brain edema and tumor angiogenesis. J Neurosurg 1994;81:560-566 https://doi.org/10.3171/jns.1994.81.4.056
  15. Kelly PJ, Daumas-Duport C, Scheithauer BW, Kall BA, Kispert DB. Stereotactic histologic correlations of computed tomography- and magnetic resonance imaging-defined abnormalities in patients with glial neoplasms. Mayo Clin Proc 1987;62:450-459 https://doi.org/10.1016/S0025-6196(12)65470-6
  16. Al-Okaili RN, Krejza J, Wang S, Woo JH, Melhem ER. Advanced MR imaging techniques in the diagnosis of intraaxial brain tumors in adults. Radiographics 2006;26 Suppl 1:S173-189 https://doi.org/10.1148/rg.26si065513
  17. Maurer MH, Synowitz M, Badakshi H, et al. Glioblastoma multiforme versus solitary supratentorial brain metastasis: differentiation based on morphology and magnetic resonance signal characteristics. Rofo 2013;185:235-240
  18. Park YW, Ahn SJ. Comparison of contrast-enhanced T2 FLAIR and 3D T1 black-blood fast spin-echo for detection of leptomeningeal metastases. Investig Magn Reson Imaging 2018;22:86-93 https://doi.org/10.13104/imri.2018.22.2.86
  19. Burger PC, Vogel FS, Green SB, Strike TA. Glioblastoma multiforme and anaplastic astrocytoma. Pathologic criteria and prognostic implications. Cancer 1985;56:1106-1111 https://doi.org/10.1002/1097-0142(19850901)56:5<1106::AID-CNCR2820560525>3.0.CO;2-2
  20. Oh J, Cha S, Aiken AH, et al. Quantitative apparent diffusion coefficients and T2 relaxation times in characterizing contrast enhancing brain tumors and regions of peritumoral edema. J Magn Reson Imaging 2005;21:701-708 https://doi.org/10.1002/jmri.20335
  21. Smirniotopoulos JG, Murphy FM, Rushing EJ, Rees JH, Schroeder JW. Patterns of contrast enhancement in the brain and meninges. Radiographics 2007;27:525-551 https://doi.org/10.1148/rg.272065155
  22. Kunimatsu A, Kunimatsu N, Kamiya K, Watadani T, Mori H, Abe O. Comparison between glioblastoma and primary central nervous system lymphoma using MR image-based texture analysis. Magn Reson Med Sci 2018;17:50-57 https://doi.org/10.2463/mrms.mp.2017-0044
  23. VandenBerg SR. Current diagnostic concepts of astrocytic tumors. J Neuropathol Exp Neurol 1992;51:644-657 https://doi.org/10.1097/00005072-199211000-00008
  24. Fink KR, Fink JR. Imaging of brain metastases. Surg Neurol Int 2013;4:S209-219 https://doi.org/10.4103/2152-7806.111298
  25. Takei H, Rouah E, Ishida Y. Brain metastasis: clinical characteristics, pathological findings and molecular subtyping for therapeutic implications. Brain Tumor Pathol 2016;33:1-12 https://doi.org/10.1007/s10014-015-0235-3
  26. Provenzale JM, Engelter ST, Petrella JR, Smith JS, MacFall JR. Use of MR exponential diffusion-weighted images to eradicate T2 "shine-through" effect. AJR Am J Roentgenol 1999;172:537-539 https://doi.org/10.2214/ajr.172.2.9930819
  27. Engelter ST, Provenzale JM, Petrella JR, Alberts MJ, DeLong DM, MacFall JR. Use of exponential diffusion imaging to determine the age of ischemic infarcts. J Neuroimaging 2001;11:141-147 https://doi.org/10.1111/j.1552-6569.2001.tb00024.x
  28. Penn RD. Cerebral edema and neurological function: CT, evoked responses, and clinical examination. Adv Neurol 1980;28:383-394
  29. Calli C, Kitis O, Yunten N, Yurtseven T, Islekel S, Akalin T. Perfusion and diffusion MR imaging in enhancing malignant cerebral tumors. Eur J Radiol 2006;58:394-403 https://doi.org/10.1016/j.ejrad.2005.12.032
  30. Sunwoo L, Yun TJ, You SH, et al. Differentiation of glioblastoma from brain metastasis: qualitative and quantitative analysis using arterial spin labeling MR imaging. PLoS One 2016;11:e0166662 https://doi.org/10.1371/journal.pone.0166662
  31. Bauer AH, Erly W, Moser FG, Maya M, Nael K. Differentiation of solitary brain metastasis from glioblastoma multiforme: a predictive multiparametric approach using combined MR diffusion and perfusion. Neuroradiology 2015;57:697-703 https://doi.org/10.1007/s00234-015-1524-6
  32. Kwon YW, Moon WJ, Park M, et al. Dynamic susceptibility contrast (DSC) perfusion MR in the prediction of long-term survival of glioblastomas (GBM): correlation with MGMT promoter methylation and 1p/19q deletions. Investig Magn Reson Imaging 2018;22:158-167 https://doi.org/10.13104/imri.2018.22.3.158
  33. Smits M, van den Bent MJ. Imaging correlates of adult glioma genotypes. Radiology 2017;284:316-331 https://doi.org/10.1148/radiol.2017151930
  34. Yamashita K, Hiwatashi A, Togao O, et al. MR imaging-based analysis of glioblastoma multiforme: estimation of IDH1 mutation status. AJNR Am J Neuroradiol 2016;37:58-65 https://doi.org/10.3174/ajnr.A4491

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