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Differentiation of Hemangioblastoma from Metastatic Brain Tumor using Dynamic Contrast-enhanced MR Imaging

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Abstract

Purpose

The aim of this study was to differentiate hemangioblastomas from metastatic brain tumors using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and compare the diagnostic performances with diffusion-weighted imaging (DWI) and dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI).

Methods

We retrospectively reviewed 7 patients with hemangioblastoma and 15 patients with metastatic adenocarcinoma with magnetic resonance imaging (MRI) including DWI, DSC-MRI, and DCE-MRI. Apparent diffusion coefficient (ADC), relative cerebral blood volume (rCBV), and DCE-MRI parameters (K trans, k ep, v e, and v p) were compared between the two groups. The diagnostic performance of each parameter was evaluated with receiver operating characteristic (ROC) curve analysis.

Results

v p, k ep, and rCBV were significantly different between patients with hemangioblastoma and those with metastatic brain tumor (p < 0.001, p = 0.005, and p = 0.017, respectively). A v p cutoff value of 0.012 and a rCBV cutoff value of 8.0 showed the highest accuracy for differentiating hemangioblastoma from metastasis. The area under the ROC curve for v p and rCBV was 0.99 and 0.89, respectively. A v p > 0.012 showed 100 % sensitivity, 93.3 % specificity, and 95.5 % accuracy and a rCBV > 8.0 showed 85.7 % sensitivity, 93.3 % specificity, and 90.9 % accuracy for differentiating hemangioblastoma from metastatic brain tumor.

Conclusion

DCE-MRI was useful for differentiating hemangioblastoma from metastatic brain tumor.

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References

  1. Tonn J-C, Westphal M. Neuro-Oncology of CNS Tumors. Berlin: Springer; 2005.

    Google Scholar 

  2. Goo HW, Ra YS. Medullary hemangioblastoma in a child with von Hippel-Lindau disease: vascular tumor perfusion depicted by arterial spin labeling and dynamic contrast-enhanced imaging. J Neurosurg Pediatr. 2015;16(1):50–3.

    Article  PubMed  Google Scholar 

  3. Slater A, Moore NR, Huson SM. The natural history of cerebellar hemangioblastomas in von Hippel-Lindau disease. AJNR Am J Neuroradiol. 2003;24(8):1570–4.

    PubMed  Google Scholar 

  4. Richard S, Campello C, Taillandier L, Parker F, Resche F. Haemangioblastoma of the central nervous system in von Hippel-Lindau disease. French VHL Study Group. J Intern Med. 1998;243(6):547–53.

    Article  CAS  PubMed  Google Scholar 

  5. Ho VB, Smirniotopoulos JG, Murphy FM, Rushing EJ. Radiologic-pathologic correlation: hemangioblastoma. AJNR Am J Neuroradiol. 1992;13(5):1343–52.

    CAS  PubMed  Google Scholar 

  6. Quadery FA, Okamoto K. Diffusion-weighted MRI of haemangioblastomas and other cerebellar tumours. Neuroradiology. 2003;45(4):212–9.

    Article  CAS  PubMed  Google Scholar 

  7. Berkman RA, Merrill MJ, Reinhold WC, Monacci WT, Saxena A, Clark WC, Robertson JT, Ali IU, Oldfield EH. Expression of the vascular permeability factor/vascular endothelial growth factor gene in central nervous system neoplasms. J Clin Invest. 1993;91(1):153–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Le Bihan D. Diffusion MRI: what water tells us about the brain. EMBO Mol Med. 2014;6(5):569–73.

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Brandao LA, Shiroishi MS, Law M. Brain tumors: a multimodality approach with diffusion-weighted imaging, diffusion tensor imaging, magnetic resonance spectroscopy, dynamic susceptibility contrast and dynamic contrast-enhanced magnetic resonance imaging. Magn Reson Imaging Clin N Am. 2013;21(2):199–239.

    Article  PubMed  Google Scholar 

  10. Cha J, Kim ST, Kim HJ, Kim BJ, Kim YK, Lee JY, Jeon P, Kim KH, Kong DS, Nam DH. Differentiation of tumor progression from pseudoprogression in patients with posttreatment glioblastoma using multiparametric histogram analysis. AJNR Am J Neuroradiol. 2014;35(7):1309–17.

    Article  CAS  PubMed  Google Scholar 

  11. Cha J, Kim ST, Kim HJ, Kim HJ, Kim BJ, Jeon P, Kim KH, Byun HS. Analysis of the layering pattern of the apparent diffusion coefficient (ADC) for differentiation of radiation necrosis from tumour progression. Eur Radiol. 2013;23(3):879–86.

    Article  PubMed  Google Scholar 

  12. Hakyemez B, Erdogan C, Bolca N, Yildirim N, Gokalp G, Parlak M. Evaluation of different cerebral mass lesions by perfusion-weighted MR imaging. J Magn Reson Imaging. 2006;24(4):817–24.

    Article  PubMed  Google Scholar 

  13. Kumar VA, Knopp EA, Zagzag D. Magnetic resonance dynamic susceptibility-weighted contrast-enhanced perfusion imaging in the diagnosis of posterior fossa hemangioblastomas and pilocytic astrocytomas: initial results. J Comput Assist Tomogr. 2010;34(6):825–9.

    Article  PubMed  Google Scholar 

  14. Tofts PS, Brix G, Buckley DL, Evelhoch JL, Henderson E, Knopp MV, Larsson HB, Lee TY, Mayr NA, Parker GJ, Port RE, Taylor J, Weisskoff RM. Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: standardized quantities and symbols. J Magn Reson Imaging. 1999;10(3):223–32.

    Article  CAS  PubMed  Google Scholar 

  15. Ostergaard L, Weisskoff RM, Chesler DA, Gyldensted C, Rosen BR. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: mathematical approach and statistical analysis. Magn Reson Med. 1996;36(5):715–25.

    Article  CAS  PubMed  Google Scholar 

  16. Boxerman JL, Prah DE, Paulson ES, Machan JT, Bedekar D, Schmainda KM. The Role of preload and leakage correction in gadolinium-based cerebral blood volume estimation determined by comparison with MION as a criterion standard. AJNR Am J Neuroradiol. 2012;33(6):1081–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Parker GJ, Roberts C, Macdonald A, Buonaccorsi GA, Cheung S, Buckley DL, Jackson A, Watson Y, Davies K, Jayson GC. Experimentally-derived functional form for a population-averaged high-temporal-resolution arterial input function for dynamic contrast-enhanced MRI. Magn Reson Med. 2006;56(5):993–1000.

    Article  PubMed  Google Scholar 

  18. Hilario A, Ramos A, Perez-Nunez A, Salvador E, Millan JM, Lagares A, Sepulveda JM, Gonzalez-Leon P, Hernandez-Lain A, Ricoy JR. The added value of apparent diffusion coefficient to cerebral blood volume in the preoperative grading of diffuse gliomas. AJNR Am J Neuroradiol. 2012;33(4):701–7.

    Article  CAS  PubMed  Google Scholar 

  19. O’Connor JP, Jackson A, Parker GJ, Roberts C, Jayson GC. Dynamic contrast-enhanced MRI in clinical trials of antivascular therapies. Nat Rev Clin Oncol. 2012;9(3):167–77.

    Article  PubMed  Google Scholar 

  20. Chikui T, Obara M, Simonetti AW, Ohga M, Koga S, Kawano S, Matsuo Y, Kamintani T, Shiraishi T, Kitamoto E, Nakamura K, Yoshiura K. The principal of dynamic contrast enhanced MRI, the method of pharmacokinetic analysis, and its application in the head and neck region. Int J Dent. 2012;2012:480659.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Nguyen TB, Cron GO, Mercier JF, Foottit C, Torres CH, Chakraborty S, Woulfe J, Jansen GH, Caudrelier JM, Sinclair J, Hogan MJ, Thornhill RE, Cameron IG. Diagnostic accuracy of dynamic contrast-enhanced MR imaging using a phase-derived vascular input function in the preoperative grading of gliomas. AJNR Am J Neuroradiol. 2012;33(8):1539–45.

    Article  CAS  PubMed  Google Scholar 

  22. Zwick S, Brix G, Tofts PS, Strecker R, Kopp-Schneider A, Laue H, Semmler W, Kiessling F. Simulation-based comparison of two approaches frequently used for dynamic contrast-enhanced MRI. Eur Radiol. 2010;20(2):432–42.

    Article  PubMed  Google Scholar 

  23. Boxerman JL, Schmainda KM, Weisskoff RM. Relative cerebral blood volume maps corrected for contrast agent extravasation significantly correlate with glioma tumor grade, whereas uncorrected maps do not. AJNR Am J Neuroradiol. 2006;27(4):859–67.

    CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81, Irwon-ro, Gangnam-gu, 135-710, Seoul, Republic of Korea

    J. Cha, S. T. Kim, H.-J. Kim, Y. K. Kim, H. Y. Kim, G. M. Park, P. Jeon, K. H. Kim & H. S. Byun

  2. Cardiovascular and Stroke Imaging Center, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

    J. Cha

  3. Department of Neurosurgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

    D.-H. Nam & D-S. Kong

Authors
  1. J. Cha
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  2. S. T. Kim
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  3. D.-H. Nam
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  4. D-S. Kong
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  5. H.-J. Kim
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  6. Y. K. Kim
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  7. H. Y. Kim
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  8. G. M. Park
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  9. P. Jeon
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  10. K. H. Kim
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  11. H. S. Byun
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Corresponding author

Correspondence to S. T. Kim.

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Conflict of interest

The authors have no conflict of interest related to the present study.

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Cha, J., Kim, S.T., Nam, DH. et al. Differentiation of Hemangioblastoma from Metastatic Brain Tumor using Dynamic Contrast-enhanced MR Imaging. Clin Neuroradiol 27, 329–334 (2017). https://doi.org/10.1007/s00062-016-0508-1

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  • DOI: https://doi.org/10.1007/s00062-016-0508-1

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