Journal of Neurology

, Volume 265, Issue 3, pp 647–658 | Cite as

New MR perfusion features in primary central nervous system lymphomas: pattern and prognostic impact

  • Stella BlaselEmail author
  • Rieke Vorwerk
  • Makoto Kiyose
  • Michel Mittelbronn
  • Uta Brunnberg
  • Hanns Ackermann
  • Martin Voss
  • Patrick N. Harter
  • Elke Hattingen
Original Communication



Some MR perfusion features predict overall survival (OS) and progression-free survival (PFS) in glioblastomas. Prognostic value of MR perfusion in primary CNS lymphomas (PCNSL) remains unexplored being the aim of this investigation.


We retrospectively analyzed 3Tesla dynamic susceptibility contrast MR perfusion in 37 pre-surgical PCNSL for normalized regional cerebral blood volume rCBVmean and rCBVmax and for a PCNSL-typical shoulder-like increase of the time–signal intensity curve (“TSIC-shoulder”), indicating moderate vessel permeability. These MR perfusion features, tumor and edema size, number of lesions and patient characteristics were correlated with OS and PFS.


Only patient’s age was prognostic for OS (p = 0.0037) and PFS (p = 0.0088). 23 PCNSL had the TSIC-shoulder, a middle-sized diameter (39.5 ± 10.8 mm), volume (15.7 ± 11.3 ml), peritumoral edema (23 ± 8.7 mm) and moderately increased rCBVmean and rCBVmax (1.7 ± 0.5; 3.9 ± 1.2). Seven PCSNL with the TSIC-shoulder presented a sun-like pattern (“rCBV-sun”) with a rim of marginally high rCBV. These unifocal PCNSL were larger (43 ± 11.2 mm; 25.62 ± 19.2 ml), with more peritumoral edema (32.8 ± 7.6 mm) and lower CBVmean (0.8 ± 0.3) and rCBVmax (2.2 ± 0.7), compared to the remaining six multifocal PCNSL without the TSIC-shoulder (26.3 ± 8.3 mm; 4.7 ± 4 ml; 16.3 ± 6.4 mm; 2.4 ± 1.6; 4.4 ± 2.3).


Only patient age was predictive for OS and PFS of PCNSL; MR perfusion parameters and features were not. Most PCNSL revealed the TSIC-shoulder, moderate size, peritumoral edema and rCBV increase. However, larger, solitary PCNSL additionally had a rCBV-sun pattern and more edema, maybe due to a centrifugal vessel proliferation, whereas smaller, multifocal PCNSL contain apparently more concentrated and less permeable blood vessels represented by higher rCBV, no TSIC-shoulder and less edema.


Primary CNS lymphoma MR perfusion rCBV Overall survival Progression-free survival Prognostic value 



M.M. would like to thank the Luxembourg National Research Fond (FNR) for the support (FNR PEARL P16/BM/11192868 Grant).


The study was not funded by external sources.

Compliance with ethical standards

Conflicts of interest

The authors declared that they have no conflict of interest.

Ethical standard statement

This study was approved by the institutional review board at Frankfurt Goethe University and was performed in accordance with the ethical standards for human subjects research. For this type of study formal consent is not required.


  1. 1.
    Olson JE, Janney CA, Rao RD et al (2002) The continuing increase in the incidence of primary central nervous system non-Hodgkin lymphoma: a surveillance, epidemiology, and end results analysis. Cancer 95:1504–1510CrossRefPubMedGoogle Scholar
  2. 2.
    Dolecek TA, Propp JM, Stroup NE, Kruchko C (2012) CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2005-2009. Neuro Oncol 14(Suppl 5):v1–v49. CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    O’Neill BP, Decker PA, Tieu C, Cerhan JR (2013) The changing incidence of primary central nervous system lymphoma is driven primarily by the changing incidence in young and middle-aged men and differs from time trends in systemic diffuse large B-cell non-Hodgkin’s lymphoma. Am J Hematol 88:997–1000. CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Schlegel U (2009) Primary CNS lymphoma. Ther Adv Neurol Disord 2:93–104. CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Grommes C, DeAngelis LM (2017) Primary CNS Lymphoma. J Clin Oncol Off J Am Soc Clin Oncol 35:2410–2418. CrossRefGoogle Scholar
  6. 6.
    Aronen HJ, Gazit IE, Louis DN et al (1994) Cerebral blood volume maps of gliomas: comparison with tumor grade and histologic findings. Radiology 191:41–51CrossRefPubMedGoogle Scholar
  7. 7.
    Chaudhry IH, O’Donovan DG, Brenchley PE et al (2001) Vascular endothelial growth factor expression correlates with tumour grade and vascularity in gliomas. Histopathology 39:409–415CrossRefPubMedGoogle Scholar
  8. 8.
    Lee SJ, Kim JH, Kim YM et al (2001) Perfusion MR imaging in gliomas: comparison with histologic tumor grade. Korean J Radiol 2:1–7CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Cha S (2004) Perfusion MR imaging of brain tumors. Top Magn Reson Imaging 15:279–289CrossRefPubMedGoogle Scholar
  10. 10.
    Law M, Yang S, Babb JS et al (2004) Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade. AJNR Am J Neuroradiol 25:746–755PubMedGoogle Scholar
  11. 11.
    Law M, Young RJ, Babb JS et al (2008) Gliomas: predicting time to progression or survival with cerebral blood volume measurements at dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Radiology 247:490–498CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Jabehdar Maralani P, Melhem ER, Wang S et al (2015) Association of dynamic susceptibility contrast-enhanced MR Perfusion parameters with prognosis in elderly patients with glioblastomas. Eur Radiol 25:2738–2744. CrossRefPubMedGoogle Scholar
  13. 13.
    Blasel S, Franz K, Ackermann H et al (2011) Stripe-like increase of rCBV beyond the visible border of glioblastomas: site of tumor infiltration growing after neurosurgery. J Neurooncol 103:575–584CrossRefPubMedGoogle Scholar
  14. 14.
    Blasel S, Franz K, Mittelbronn M et al (2010) The striate sign: peritumoral perfusion pattern of infiltrative primary and recurrence gliomas. Neurosurg Rev 33:193–204CrossRefPubMedGoogle Scholar
  15. 15.
    Chiang IC, Kuo YT, Lu CY et al (2004) Distinction between high-grade gliomas and solitary metastases using peritumoral 3-T magnetic resonance spectroscopy, diffusion, and perfusion imagings. Neuroradiology 46:619–627CrossRefPubMedGoogle Scholar
  16. 16.
    Law M, Cha S, Knopp EA et al (2002) High-grade gliomas and solitary metastases: differentiation by using perfusion and proton spectroscopic MR imaging. Radiology 222:715–721CrossRefPubMedGoogle Scholar
  17. 17.
    Blasel S, Jurcoane A, Bähr O et al (2013) MR perfusion in and around the contrast-enhancement of primary CNS lymphomas. J Neurooncol 114:127–134CrossRefPubMedGoogle Scholar
  18. 18.
    Rollin N, Guyotat J, Streichenberger N et al (2006) Clinical relevance of diffusion and perfusion magnetic resonance imaging in assessing intra-axial brain tumors. Neuroradiology 48:150–159CrossRefPubMedGoogle Scholar
  19. 19.
    Hakyemez B, Erdogan C, Bolca N et al (2006) Evaluation of different cerebral mass lesions by perfusion-weighted MR imaging. J Magn Reson Imaging 24:817–824CrossRefPubMedGoogle Scholar
  20. 20.
    Lee IH, Kim ST, Kim HJ et al (2010) Analysis of perfusion weighted image of CNS lymphoma. Eur J Radiol 76:48–51CrossRefPubMedGoogle Scholar
  21. 21.
    Calli C, Kitis O, Yunten N et al (2006) Perfusion and diffusion MR imaging in enhancing malignant cerebral tumors. Eur J Radiol 58:394–403CrossRefPubMedGoogle Scholar
  22. 22.
    Cha S, Knopp EA, Johnson G et al (2002) Intracranial mass lesions: dynamic contrast-enhanced susceptibility-weighted echo-planar perfusion MR imaging. Radiology 223:11–29CrossRefPubMedGoogle Scholar
  23. 23.
    Hartmann M, Heiland S, Harting I et al (2003) Distinguishing of primary cerebral lymphoma from high-grade glioma with perfusion-weighted magnetic resonance imaging. Neurosci Lett 338:119–122CrossRefPubMedGoogle Scholar
  24. 24.
    Liao W, Liu Y, Wang X et al (2009) Differentiation of primary central nervous system lymphoma and high-grade glioma with dynamic susceptibility contrast-enhanced perfusion magnetic resonance imaging. Acta Radiol 50:217–225CrossRefPubMedGoogle Scholar
  25. 25.
    Sugahara T, Korogi Y, Shigematsu Y et al (1999) Perfusion-sensitive MRI of cerebral lymphomas: a preliminary report. J Comput Assist Tomogr 23:232–237CrossRefPubMedGoogle Scholar
  26. 26.
    Kickingereder P, Wiestler B, Sahm F et al (2014) Primary central nervous system lymphoma and atypical glioblastoma: multiparametric differentiation by using diffusion-, perfusion-, and susceptibility-weighted MR imaging. Radiology 272:843–850. CrossRefPubMedGoogle Scholar
  27. 27.
    Wang S, Kim S, Chawla S et al (2011) Differentiation between glioblastomas, solitary brain metastases, and primary cerebral lymphomas using diffusion tensor and dynamic susceptibility contrast-enhanced MR imaging. AJNR Am J Neuroradiol 32:507–514. CrossRefPubMedGoogle Scholar
  28. 28.
    Toh CH, Wei K-C, Chang C-N et al (2013) Differentiation of primary central nervous system lymphomas and glioblastomas: comparisons of diagnostic performance of dynamic susceptibility contrast-enhanced perfusion MR imaging without and with contrast-leakage correction. AJNR Am J Neuroradiol 34:1145–1149. CrossRefPubMedGoogle Scholar
  29. 29.
    Nakajima S, Okada T, Yamamoto A et al (2015) Primary central nervous system lymphoma and glioblastoma: differentiation using dynamic susceptibility-contrast perfusion-weighted imaging, diffusion-weighted imaging, and (18)F-fluorodeoxyglucose positron emission tomography. Clin Imaging 39:390–395. CrossRefPubMedGoogle Scholar
  30. 30.
    Mangla R, Kolar B, Zhu T et al (2011) Percentage signal recovery derived from MR dynamic susceptibility contrast imaging is useful to differentiate common enhancing malignant lesions of the brain. AJNR Am J Neuroradiol 32:1004–1010CrossRefPubMedGoogle Scholar
  31. 31.
    Küker W, Nägele T, Korfel A et al (2005) Primary central nervous system lymphomas (PCNSL): MRI features at presentation in 100 patients. J Neurooncol 72:169–177. CrossRefPubMedGoogle Scholar
  32. 32.
    Louis DN, Ohgaki H, Wiestler OD et al (2007) The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol 114:97–109CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Schlegel U, Illerhaus G (2015) Leitlinien für Diagnostik und Therapie in der Neurologie: Primäre ZNS-Lymphome (PZNSL). Accessed 13 Dec 2017
  34. 34.
    Fritsch K, Kasenda B, Schorb E et al (2017) High-dose methotrexate-based immuno-chemotherapy for elderly primary CNS lymphoma patients (PRIMAIN study). Leukemia 31:846–852. CrossRefPubMedGoogle Scholar
  35. 35.
    Fritsch K, Kasenda B, Hader C et al (2011) Immunochemotherapy with rituximab, methotrexate, procarbazine, and lomustine for primary CNS lymphoma (PCNSL) in the elderly. Ann Oncol 22:2080–2085. CrossRefPubMedGoogle Scholar
  36. 36.
    Illerhaus G, Muller F, Feuerhake F et al (2008) High-dose chemotherapy and autologous stem-cell transplantation without consolidating radiotherapy as first-line treatment for primary lymphoma of the central nervous system. Haematologica 93:147–148. CrossRefPubMedGoogle Scholar
  37. 37.
    Ferreri AJM, Cwynarski K, Pulczynski E et al (2016) Chemoimmunotherapy with methotrexate, cytarabine, thiotepa, and rituximab (MATRix regimen) in patients with primary CNS lymphoma: results of the first randomisation of the International Extranodal Lymphoma Study Group-32 (IELSG32) phase 2 trial. Lancet Haematol 3:e217–e227. CrossRefPubMedGoogle Scholar
  38. 38.
    Patel TR, McHugh BJ, Bi WL et al (2011) A comprehensive review of MR imaging changes following radiosurgery to 500 brain metastases. AJNR Am J Neuroradiol 32:1885–1892. CrossRefPubMedGoogle Scholar
  39. 39.
    Tung GA, Julius BD, Rogg JM (2003) MRI of intracerebral hematoma: value of vasogenic edema ratio for predicting the cause. Neuroradiology 45:357–362. CrossRefPubMedGoogle Scholar
  40. 40.
    Rosen BR, Belliveau JW, Vevea JM, Brady TJ (1990) Perfusion imaging with NMR contrast agents. Magn Reson Med 14:249–265CrossRefPubMedGoogle Scholar
  41. 41.
    Ostergaard L, Weisskoff RM, Chesler DA et al (1996) High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: mathematical approach and statistical analysis. Magn Reson Med 36:715–725CrossRefPubMedGoogle Scholar
  42. 42.
    Lev MH, Rosen BR (1999) Clinical applications of intracranial perfusion MR imaging. Neuroimaging Clin N Am 9:309–331PubMedGoogle Scholar
  43. 43.
    Abrey LE, Ben-Porat L, Panageas KS et al (2006) Primary central nervous system lymphoma: the Memorial Sloan-Kettering Cancer Center prognostic model. J Clin Oncol Off J Am Soc Clin Oncol 24:5711–5715. CrossRefGoogle Scholar
  44. 44.
    Gutman SI, Piper M, Grant MD et al (2013) Progression-free survival: what does it mean for psychological well-being or quality of life? Agency for Healthcare Research and Quality, Rockville. Accessed 10 Dec 2017
  45. 45.
    Law M, Saindane AM, Ge Y et al (2004) Microvascular abnormality in relapsing-remitting multiple sclerosis: perfusion MR imaging findings in normal-appearing white matter. Radiology 231:645–652CrossRefPubMedGoogle Scholar
  46. 46.
    Di Stefano AL, Bergsland N, Berzero G et al (2014) Facing contrast-enhancing gliomas: perfusion MRI in grade III and grade IV gliomas according to tumor area. Biomed Res Int 2014:154350. PubMedPubMedCentralGoogle Scholar
  47. 47.
    Scatliff JH, Radcliffe WB, Pittman HH, Park CH (1969) Vascular structure of glioblastomas. Am J Roentgenol Radium Ther Nucl Med 105:795–805CrossRefPubMedGoogle Scholar
  48. 48.
    Scatliff JH, Guinto FC, Radcliffe WB (1971) Vascular patterns in cerebral neoplasms and their differential diagnosis. Semin Roentgenol 6:59–69CrossRefPubMedGoogle Scholar
  49. 49.
    Jiddane M, Nicoli F, Diaz P et al (1986) Intracranial malignant lymphoma. Report of 30 cases and review of the literature. J Neurosurg 65:592–599CrossRefPubMedGoogle Scholar
  50. 50.
    Hakyemez B, Erdogan C, Gokalp G et al (2010) Solitary metastases and high-grade gliomas: radiological differentiation by morphometric analysis and perfusion-weighted MRI. Clin Radiol 65:15–20CrossRefPubMedGoogle Scholar
  51. 51.
    Xing Z, You RX, Li J et al (2014) 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. Clin Neuroradiol 24:329–336. CrossRefPubMedGoogle Scholar
  52. 52.
    Ferreri AJM, Blay J-Y, Reni M et al (2003) Prognostic scoring system for primary CNS lymphomas: the International Extranodal Lymphoma Study Group experience. J Clin Oncol Off J Am Soc Clin Oncol 21:266–272. CrossRefGoogle Scholar
  53. 53.
    Roth P, Martus P, Kiewe P et al (2012) Outcome of elderly patients with primary CNS lymphoma in the G-PCNSL-SG-1 trial. Neurology 79:890–896. CrossRefPubMedGoogle Scholar
  54. 54.
    Valles FE, Perez-Valles CL, Regalado S et al (2013) Combined diffusion and perfusion MR imaging as biomarkers of prognosis in immunocompetent patients with primary central nervous system lymphoma. AJNR Am J Neuroradiol 34:35–40. CrossRefPubMedGoogle Scholar
  55. 55.
    Koeller KK, Smirniotopoulos JG, Jones RV (1997) Primary central nervous system lymphoma: radiologic-pathologic correlation. Radiographics 17:1497–1526CrossRefPubMedGoogle Scholar
  56. 56.
    Roser F, Saini M, Meliss R et al (2004) Apoptosis, vascularity, and proliferation in primary central nervous system lymphomas (PCNSL): a histopathological study. Surg Neurol 62:393–399CrossRefPubMedGoogle Scholar
  57. 57.
    Sugita Y, Takase Y, Mori D et al (2007) Endoglin (CD 105) is expressed on endothelial cells in the primary central nervous system lymphomas and correlates with survival. J Neurooncol 82:249–256CrossRefPubMedGoogle Scholar
  58. 58.
    Takeuchi H, Matsuda K, Kitai R et al (2007) Angiogenesis in primary central nervous system lymphoma (PCNSL). J Neurooncol 84:141–145CrossRefPubMedGoogle Scholar
  59. 59.
    D’Haene N, Catteau X, Maris C et al (2008) Endothelial hyperplasia and endothelial galectin-3 expression are prognostic factors in primary central nervous system lymphomas. Br J Haematol 140:402–410CrossRefPubMedGoogle Scholar
  60. 60.
    Heiland S, Benner T, Debus J et al (1999) Simultaneous assessment of cerebral hemodynamics and contrast agent uptake in lesions with disrupted blood-brain-barrier. Magn Reson Imaging 17:21–27CrossRefPubMedGoogle Scholar
  61. 61.
    Heiland S, Hartmann M, Sartor K (2000) Is perfusion MRI feasible in lesions with disrupted blood-brain barrier? Pitfalls and possible solutions. Rofo 172:812–816CrossRefPubMedGoogle Scholar
  62. 62.
    Rorden C, Brett M (2000) Stereotaxic display of brain lesions. Behav Neurol 12:191–200CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Stella Blasel
    • 1
    Email author
  • Rieke Vorwerk
    • 1
  • Makoto Kiyose
    • 1
    • 3
  • Michel Mittelbronn
    • 5
    • 8
    • 9
    • 10
    • 11
  • Uta Brunnberg
    • 12
  • Hanns Ackermann
    • 13
  • Martin Voss
    • 4
  • Patrick N. Harter
    • 5
    • 6
    • 7
  • Elke Hattingen
    • 1
    • 2
  1. 1.Institute of NeuroradiologyGoethe-University Hospital FrankfurtFrankfurtGermany
  2. 2.Neuroradiology, RadiologyUniversity Clinics BonnBonnGermany
  3. 3.Epilepsy Center Frankfurt Rhine-Main, Institute of NeurologyGoethe-University Hospital FrankfurtFrankfurtGermany
  4. 4.Dr. Senckenberg Institute of NeurooncologyGoethe-University Hospital FrankfurtFrankfurtGermany
  5. 5.Edinger Institute, Institute of NeurologyGoethe-University FrankfurtFrankfurtGermany
  6. 6.German Cancer Consortium DKTK Partner SiteFrankfurt/MainzGermany
  7. 7.German Cancer Research Center DKFZHeidelbergGermany
  8. 8.Luxembourg Centre of Neuropathology (LCNP)DudelangeLuxembourg
  9. 9.Department of PathologyLaboratoire National de Santé (LNS)DudelangeLuxembourg
  10. 10.Luxembourg Centre for Systems Biomedicine (LCSB)University of LuxembourgEsch-sur-AlzetteLuxembourg
  11. 11.NORLUX Neuro-Oncology Laboratory, Department of OncologyLuxembourg Institute of Health (L.I.H.)LuxembourgLuxembourg
  12. 12.Department of Hematology and OncologyGoethe-University Hospital FrankfurtFrankfurtGermany
  13. 13.Institute of Biostatistics and Mathematical ModellingGoethe-University Hospital FrankfurtFrankfurtGermany

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