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Clinical Neuroradiology

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01.12.2014 | Original Article

Differentiation of Primary Central Nervous System Lymphomas from High-Grade Gliomas by rCBV and Percentage of Signal Intensity Recovery Derived from Dynamic Susceptibility-Weighted Contrast-Enhanced Perfusion MR Imaging

verfasst von: Z. Xing, MD, R. X. You, MD, J. Li, MD, Y. Liu, MD, D. R. Cao, MD

Erschienen in: Clinical Neuroradiology | Ausgabe 4/2014

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Abstract

Purpose

Primary central nervous system lymphoma (PCNSL) and high-grade glioma (HGG) may have similar enhancement patterns on magnetic resonance imaging (MRI), making the differential diagnosis difficult or even impractical. Relative cerebral blood volume (rCBV) and percentage of signal intensity recovery derived from dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion MR imaging may help distinguish PCNSL from HGG. The purpose of this study was to evaluate the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of these two imaging parameters used alone or in combination for differentiating PCNSL from HGG.

Methods

A total of 12 patients with PCNSL and 26 patients with HGG were examined using a 3T scanner. rCBV and percentage of signal intensity recovery were obtained and receiver operating characteristic (ROC) analysis was performed to determine optimum thresholds for tumor differentiation. Sensitivity, specificity, PPV, NPV, and accuracy for identifying the tumor types were also calculated.

Results

The optimum threshold of 2.56 for rCBV provided sensitivity, specificity, PPV, NPV, and accuracy of 96.2, 90, 92.6, 94.7, and 93.5 %, respectively, for determining PCNSL. A threshold value of 0.89 for percentage of signal intensity recovery optimized differentiation of PCNSL and HGG with a sensitivity, specificity, PPV, NPV, and accuracy of 100, 88.5, 87, 100, and 93.5 %, respectively. Combining rCBV with the percentage of signal intensity recovery further improved the differentiation of PCNSL and HGG with a specificity of 98.5 % and an accuracy of 95.7 %.

Conclusions

The combination of rCBV measurement with percentage of signal intensity recovery can help in more accurate differentiation of PCNSL from HGG.

Koeller KK, Smirniotopoulos JG, Jones RV. Primary central nervous system lymphoma: radiologic-pathologic correlation. Radiographics. 1997;17:1497–526.PubMedCrossRef

Louis DN, Ohgaki H, Wiestler OD, Cavenee WK, Burger PC, Jouvet A, et al. The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol. 2007;114:97–109.PubMedCentralPubMedCrossRef

Buhring U, Herrlinger U, Krings T, Thiex R, Weller M, Kuker W. MRI features of primary central nervous system lymphomas at presentation. Neurology. 2001;57:393–6.PubMedCrossRef

Liu HY, Zhang XL, Chen YP, Qiu SJ. Characteristic imaging features of primary central nervous system lymphoma in comparison with pathological findings. Nan Fang Yi Ke Da Xue Xue Bao. 2009;29:333–6.PubMed

Tang YZ, Booth TC, Bhogal P, Malhotra A, Wilhelm T. Imaging of primary central nervous system lymphoma. Clin Radiol. 2011;66:768–77.PubMedCrossRef

Cha S, Knopp EA, Johnson G, Wetzel SG, Litt AW, Zagzag D. Intracranial mass lesions: dynamic contrast-enhanced susceptibility-weighted echo-planar perfusion MR imaging. Radiology. 2002;223:11–29.PubMedCrossRef

Covarrubias DJ, Rosen BR, Lev MH. Dynamic magnetic resonance perfusion imaging of brain tumors. Oncologist. 2004;9:528–37.PubMedCrossRef

Barbier EL, Lamalle L, Decorps M. Methodology of brain perfusion imaging. J Magn Reson Imaging. 2001;13:496–520.PubMedCrossRef

Cha S. Perfusion MR imaging: basic principles and clinical applications. Magn Reson Imaging Clin N Am. 2003;11:403–13.PubMedCrossRef

10.

Preul C, Kuhn B, Lang EW, Mehdorn HM, Heller M, Link J. Differentiation of cerebral tumors using multi-section echo planar MR perfusion imaging. Eur J Radiol. 2003;48:244–51.PubMedCrossRef

11.

Law M, Yang S, Babb JS, Knopp EA, Golfinos JG, Zagzag D, et al. Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade. AJNR Am J Neuroradiol. 2004;25:746–55.PubMed

12.

Bulakbasi N, Kocaoglu M, Farzaliyev A, Tayfun C, Ucoz T, Somuncu I. Assessment of diagnostic accuracy of perfusion MR imaging in primary and metastatic solitary malignant brain tumors. AJNR Am J Neuroradiol. 2005;26:2187–99.PubMed

13.

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;24:817–24.PubMedCrossRef

14.

Burger PC. Malignant astrocytic neoplasms: classification, pathologic anatomy, and response to treatment. Semin Oncol. 1986;13:16–26.PubMed

15.

Folkerth RD. Descriptive analysis and quantification of angiogenesis in human brain tumors. J Neurooncol. 2000;50:165–72.PubMedCrossRef

16.

Folkerth RD. Histologic measures of angiogenesis in human primary brain tumors. Cancer Treat Res. 2004;117:79–95.PubMedCrossRef

17.

Sharma S, Sharma MC, Gupta DK, Sarkar C. Angiogenic patterns and their quantitation in high grade astrocytic tumors. J Neurooncol. 2006;79:19–30.PubMedCrossRef

18.

Kim EY, Kim SS. Magnetic resonance findings of primary central nervous system T-cell lymphoma in immunocompetent patients. Acta Radiol. 2005;46:187–92.PubMedCrossRef

19.

Weber MA, Zoubaa S, Schlieter M, Juttler E, Huttner HB, Geletneky K, et al. Diagnostic performance of spectroscopic and perfusion MRI for distinction of brain tumors. Neurology. 2006;66:1899–906.PubMedCrossRef

20.

Lee IH, Kim ST, Kim HJ, Kim KH, Jeon P, Byun HS. Analysis of perfusion weighted image of CNS lymphoma. Eur J Radiol. 2010;76:48–51.PubMedCrossRef

21.

Cho SK, Na DG, Ryoo JW, Roh HG, Moon CH, Byun HS, et al. Perfusion MR imaging: clinical utility for the differential diagnosis of various brain tumors. Korean J Radiol. 2002;3:171–9.PubMedCentralPubMedCrossRef

22.

Hartmann M, Heiland S, Harting I, Tronnier VM, Sommer C, Ludwig R, et al. Distinguishing of primary cerebral lymphoma from high-grade glioma with perfusion-weighted magnetic resonance imaging. Neurosci Lett. 2003;338:119–22.PubMedCrossRef

23.

Liao W, Liu Y, Wang X, Jiang X, Tang B, Fang J, et al. Differentiation of primary central nervous system lymphoma and high-grade glioma with dynamic susceptibility contrast-enhanced perfusion magnetic resonance imaging. Acta Radiol. 2009;50:217–25.PubMedCrossRef

24.

Lev MH. Gliomatosis cerebri has normal relative blood volume: really?! Who cares? Should you? AJNR Am J Neuroradiol. 2002;23:345–6.PubMed

25.

Lupo JM, Cha S, Chang SM, Nelson SJ. Dynamic susceptibility-weighted perfusion imaging of high-grade gliomas: characterization of spatial heterogeneity. AJNR Am J Neuroradiol. 2005;26:1446–54.PubMed

26.

Cha S, Lupo JM, Chen MH, Lamborn KR, McDermott MW, Berger MS, 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;28:1078–84.PubMedCrossRef

27.

Wetzel SG, Cha S, Johnson G, Lee P, Law M, Kasow DL, et al. Relative cerebral blood volume measurements in intracranial mass lesions: interobserver and intraobserver reproducibility study. Radiology. 2002;224:797–803.PubMedCrossRef

28.

Heiland S, Benner T, Debus J, Rempp K, Reith W, Sartor K. Simultaneous assessment of cerebral hemodynamics and contrast agent uptake in lesions with disrupted blood-brain-barrier. Magn Reson Imaging. 1999;17:21–7.PubMedCrossRef

29.

Wang S, Kim S, Chawla S, Wolf RL, Knipp DE, Vossough A, et al. Differentiation between glioblastomas, solitary brain metastases, and primary cerebral lymphomas using diffusion tensor and dynamic susceptibility contrast-enhanced MR imaging. AJNR Am J Neuroradiol. 2011;32:507–14.PubMedCrossRef

30.

Aronen HJ, Gazit IE, Louis DN, Buchbinder BR, Pardo FS, Weisskoff RM, et al. Cerebral blood volume maps of gliomas: comparison with tumor grade and histologic findings. Radiology. 1994;191:41–51.PubMedCrossRef

31.

Sugahara T, Korogi Y, Kochi M, Ikushima I, Hirai T, Okuda T, et al. Correlation of MR imaging-determined cerebral blood volume maps with histologic and angiographic determination of vascularity of gliomas. AJR Am J Roentgenol. 1998;171:1479–86.PubMedCrossRef

32.

Knopp EA, Cha S, Johnson G, Mazumdar A, Golfinos JG, Zagzag D, et al. Glial neoplasms: dynamic contrast-enhanced T2*-weighted MR imaging. Radiology. 1999;211:791–8.PubMedCrossRef

33.

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

34.

Guo AC, Cummings TJ, Dash RC, Provenzale JM. Lymphomas and high-grade astrocytomas: comparison of water diffusibility and histologic characteristics. Radiology. 2002;224:177–83.PubMedCrossRef

35.

Barajas RF Jr., Rubenstein JL, Chang JS, Hwang J, Cha S. Diffusion-weighted MR imaging derived apparent diffusion coefficient is predictive of clinical outcome in primary central nervous system lymphoma. AJNR Am J Neuroradiol. 2010;31:60–6.PubMedCentralPubMedCrossRef

36.

Yamasaki F, Kurisu K, Satoh K, Arita K, Sugiyama K, Ohtaki M, et al. Apparent diffusion coefficient of human brain tumors at MR imaging. Radiology. 2005;235:985–91.PubMedCrossRef

37.

Kitis O, Altay H, Calli C, Yunten N, Akalin T, Yurtseven T. Minimum apparent diffusion coefficients in the evaluation of brain tumors. Eur J Radiol. 2005;55:393–400.PubMedCrossRef

38.

Toh CH, Castillo M, Wong AM, Wei KC, Wong HF, Ng SH, et al. Primary cerebral lymphoma and glioblastoma multiforme: differences in diffusion characteristics evaluated with diffusion tensor imaging. AJNR Am J Neuroradiol. 2008;29:471–5.PubMedCrossRef

39.

Server A, Kulle B, Maehlen J, Josefsen R, Schellhorn T, Kumar T, et al. Quantitative apparent diffusion coefficients in the characterization of brain tumors and associated peritumoral edema. Acta Radiol. 2009;50:682–9.PubMedCrossRef

40.

Doskaliyev A, Yamasaki F, Ohtaki M, Kajiwara Y, Takeshima Y, Watanabe Y, et al. Lymphomas and glioblastomas: differences in the apparent diffusion coefficient evaluated with high b-value diffusion-weighted magnetic resonance imaging at 3T. Eur J Radiol. 2012;81:339–44.PubMedCrossRef

41.

Harting I, Hartmann M, Jost G, Sommer C, Ahmadi R, Heiland S, et al. Differentiating primary central nervous system lymphoma from glioma in humans using localised proton magnetic resonance spectroscopy. Neurosci Lett. 2003;342:163–6.PubMedCrossRef

42.

Chawla S, Zhang Y, Wang S, Chaudhary S, Chou C, O’Rourke DM, et al. Proton magnetic resonance spectroscopy in differentiating glioblastomas from primary cerebral lymphomas and brain metastases. J Comput Assist Tomogr. 2010;34:836–41.PubMedCrossRef

43.

Lee EJ, terBrugge K, Mikulis D, Choi DS, Bae JM, Lee SK, et al. Diagnostic value of peritumoral minimum apparent diffusion coefficient for differentiation of glioblastoma multiforme from solitary metastatic lesions. AJR Am J Roentgenol. 2011;196:71–6.PubMedCrossRef

Titel: Differentiation of Primary Central Nervous System Lymphomas from High-Grade Gliomas by rCBV and Percentage of Signal Intensity Recovery Derived from Dynamic Susceptibility-Weighted Contrast-Enhanced Perfusion MR Imaging
verfasst von: Z. Xing, MD
R. X. You, MD
J. Li, MD
Y. Liu, MD
D. R. Cao, MD
Publikationsdatum: 01.12.2014
Verlag: Springer Berlin Heidelberg
Erschienen in: Clinical Neuroradiology / Ausgabe 4/2014
Print ISSN: 1869-1439
Elektronische ISSN: 1869-1447
DOI: https://doi.org/10.1007/s00062-013-0255-5

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Differentiation of Primary Central Nervous System Lymphomas from High-Grade Gliomas by rCBV and Percentage of Signal Intensity Recovery Derived from Dynamic Susceptibility-Weighted Contrast-Enhanced Perfusion MR Imaging

Abstract

Purpose

Methods

Results

Conclusions

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Abstract

Purpose

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Results

Conclusions

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