, Volume 52, Issue 4, pp 307–317 | Cite as

Perfusion MRI of brain tumours: a comparative study of pseudo-continuous arterial spin labelling and dynamic susceptibility contrast imaging

  • Hanna Järnum
  • Elena G. Steffensen
  • Linda Knutsson
  • Ernst-Torben Fründ
  • Carsten Wiberg Simonsen
  • Søren Lundbye-Christensen
  • Ajit Shankaranarayanan
  • David C. Alsop
  • Finn Taagehøj Jensen
  • Elna-Marie Larsson
Diagnostic Neuroradiology



The purpose of this study was to compare the non-invasive 3D pseudo-continuous arterial spin labelling (PC ASL) technique with the clinically established dynamic susceptibility contrast perfusion magnetic resonance imaging (DSC-MRI) for evaluation of brain tumours.


A prospective study of 28 patients with contrast-enhancing brain tumours was performed at 3 T using DSC-MRI and PC ASL with whole-brain coverage. The visual qualitative evaluation of signal enhancement in tumour was scored from 0 to 3 (0 = no signal enhancement compared with white matter, 3 = pronounced signal enhancement with equal or higher signal intensity than in grey matter/basal ganglia). The extent of susceptibility artefacts in the tumour was scored from 0 to 2 (0 = no susceptibility artefacts and 2 = extensive susceptibility artefacts (maximum diameter > 2 cm)). A quantitative analysis was performed with normalised tumour blood flow values (ASL nTBF, DSC nTBF): mean value for region of interest (ROI) in an area with maximum signal enhancement/the mean value for ROIs in cerebellum.


There was no difference in total visual score for signal enhancement between PC ASL and DSC relative cerebral blood flow (p = 0.12). ASL had a lower susceptibility-artefact score than DSC-MRI (p = 0.03). There was good correlation between DSC nTBF and ASL nTBF values with a correlation coefficient of 0.82.


PC ASL is an alternative to DSC-MRI for the evaluation of perfusion in brain tumours. The method has fewer susceptibility artefacts than DSC-MRI and can be used in patients with renal failure because no contrast injection is needed.


Magnetic resonance imaging Perfusion ASL DSC-MRI Brain neoplasms 



This study was supported in part by NIH grant, 5 R01 CA115745 (D.C. Alsop).

Conflict of interest statement

E. T. Fründ is employed at Aalborg Hospital, Department of Radiology with association to GE Healthcare—Applied Science Lab Europe. A. Shankaranarayanan is employed at GE Healthcare, Applied Science Lab, Menlo Park, California. D. C. Alsop is an inventor on several patents related to ASL and to the ASL sequence in this manuscript. This author receives research support from GE Healthcare and Merck & Co. and works as a paid consultant for Merck & Co.


  1. 1.
    Ohgaki H, Kleihues P (2005) Population-based studies on incidence, survival rates, and genetic alterations in astrocytic and oligodendroglial gliomas. J Neuropathol Exp Neurol 64:479–489PubMedGoogle Scholar
  2. 2.
    Tourdias T, Rodrigo S, Oppenheim C et al (2008) Pulsed arterial spin labeling applications in brain tumors: practical review. J Neuroradiol 35:79–89CrossRefPubMedGoogle Scholar
  3. 3.
    Zhang H, Rodiger LA, Shen T, Miao J, Oudkerk M (2008) Preoperative subtyping of meningiomas by perfusion MR imaging. Neuroradiology 50:835–840CrossRefPubMedGoogle Scholar
  4. 4.
    Jenkinson MD, Smith TS, Joyce KA et al (2006) Cerebral blood volume, genotype and chemosensitivity in oligodendroglial tumours. Neuroradiology 48:703–713CrossRefPubMedGoogle Scholar
  5. 5.
    Zonari P, Baraldi P, Crisi G (2007) Multimodal MRI in the characterization of glial neoplasms: the combined role of single-voxel MR spectroscopy, diffusion imaging and echo-planar perfusion imaging. Neuroradiology 49:795–803CrossRefPubMedGoogle Scholar
  6. 6.
    Hakyemez B, Erdogan C, Ercan I, Ergin N, Uysal S, Atahan S (2005) High-grade and low-grade gliomas: differentiation by using perfusion MR imaging. Clin Radiol 60:493–502CrossRefPubMedGoogle Scholar
  7. 7.
    Shin JH, Lee HK, Kwun BD et al (2002) Using relative cerebral blood flow and volume to evaluate the histopathologic grade of cerebral gliomas: preliminary results. AJR Am J Roentgenol 179:783–789PubMedGoogle Scholar
  8. 8.
    Wolf RL, Detre JA (2007) Clinical neuroimaging using arterial spin-labeled perfusion magnetic resonance imaging. Neurotherapeutics 4:346–359CrossRefPubMedGoogle Scholar
  9. 9.
    Petersen ET, Zimine I, Ho YC, Golay X (2006) Non-invasive measurement of perfusion: a critical review of arterial spin labelling techniques. Br J Radiol 79:688–701CrossRefPubMedGoogle Scholar
  10. 10.
    Kimura H, Takeuchi H, Koshimoto Y et al (2006) Perfusion imaging of meningioma by using continuous arterial spin-labeling: comparison with dynamic susceptibility-weighted contrast-enhanced MR images and histopathologic features. AJNR Am J Neuroradiol 27:85–93PubMedGoogle Scholar
  11. 11.
    Warmuth C, Gunther M, Zimmer C (2003) Quantification of blood flow in brain tumors: comparison of arterial spin labeling and dynamic susceptibility-weighted contrast-enhanced MR imaging. Radiology 228:523–532CrossRefPubMedGoogle Scholar
  12. 12.
    Weber MA, Thilmann C, Lichy MP et al (2004) Assessment of irradiated brain metastases by means of arterial spin-labeling and dynamic susceptibility-weighted contrast-enhanced perfusion MRI: initial results. Invest Radiol 39:277–287CrossRefPubMedGoogle Scholar
  13. 13.
    Kim HS, Kim SY (2007) A prospective study on the added value of pulsed arterial spin-labeling and apparent diffusion coefficients in the grading of gliomas. AJNR Am J Neuroradiol 28:1693–1699CrossRefPubMedGoogle Scholar
  14. 14.
    Essig M, Wenz F, Scholdei R et al (2002) Dynamic susceptibility contrast-enhanced echo-planar imaging of cerebral gliomas. Effect of contrast medium extravasation. Acta Radiol 43:354–359CrossRefPubMedGoogle Scholar
  15. 15.
    Ostergaard L, Weisskoff RM, Chesler DA, Gyldensted C, Rosen BR (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
  16. 16.
    Rosen BR, Belliveau JW, Vevea JM, Brady TJ (1990) Perfusion imaging with NMR contrast agents. Magn Reson Med 14:249–265CrossRefPubMedGoogle Scholar
  17. 17.
    Boxerman JL, Schmainda KM, Weisskoff RM (2006) 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 27:859–867PubMedGoogle Scholar
  18. 18.
    Dai W, Garcia D, de Bazelaire C, Alsop DC (2008) Continuous flow-driven inversion for arterial spin labeling using pulsed radio frequency and gradient fields. Magn Reson Med 60:1488–1497CrossRefPubMedGoogle Scholar
  19. 19.
    Alsop DC, Detre JA (1996) Reduced transit-time sensitivity in noninvasive magnetic resonance imaging of human cerebral blood flow. J Cereb Blood Flow Metab 16:1236–1249CrossRefPubMedGoogle Scholar
  20. 20.
    Wang J, Zhang Y, Wolf RL, Roc AC, Alsop DC, Detre JA (2005) Amplitude-modulated continuous arterial spin-labeling 3.0-T perfusion MR imaging with a single coil: feasibility study. Radiology 235:218–228CrossRefPubMedGoogle Scholar
  21. 21.
    Lu H, Clingman C, Golay X, van Zijl PC (2004) Determining the longitudinal relaxation time (T1) of blood at 3.0 Tesla. Magn Reson Med 52:679–682CrossRefPubMedGoogle Scholar
  22. 22.
    Herscovitch P, Raichle ME (1985) What is the correct value for the brain–blood partition coefficient for water? J Cereb Blood Flow Metab 5:65–69PubMedGoogle Scholar
  23. 23.
    Garcia DM, Duhamel G, Alsop DC (2005) Efficiency of inversion pulses for background suppressed arterial spin labeling. Magn Reson Med 54:366–372CrossRefPubMedGoogle Scholar
  24. 24.
    Emblem KE, Nedregaard B, Nome T et al (2008) Glioma grading by using histogram analysis of blood volume heterogeneity from MR-derived cerebral blood volume maps. Radiology 247:808–817CrossRefPubMedGoogle Scholar
  25. 25.
    Bland JM, Altman DG (1999) Measuring agreement in method comparison studies. Stat Methods Med Res 8:135–160CrossRefPubMedGoogle Scholar
  26. 26.
    Appignani B, Wong ET, Hackney DB, Alsop DC (2006) Comparison of arterial spin labeling and dynamic susceptibility contrast imaging in glioma. Proc Intl Soc Mag Reson Med 14Google Scholar
  27. 27.
    Wang J, Alsop DC, Li L et al (2002) Comparison of quantitative perfusion imaging using arterial spin labeling at 1.5 and 4.0 Tesla. Magn Reson Med 48:242–254CrossRefPubMedGoogle Scholar
  28. 28.
    Ye FQ, Berman KF, Ellmore T et al (2000) H(2)(15)O PET validation of steady-state arterial spin tagging cerebral blood flow measurements in humans. Magn Reson Med 44:450–456CrossRefPubMedGoogle Scholar
  29. 29.
    Arbab AS, Aoki S, Toyama K et al (2001) Brain perfusion measured by flow-sensitive alternating inversion recovery (FAIR) and dynamic susceptibility contrast-enhanced magnetic resonance imaging: comparison with nuclear medicine technique. Eur Radiol 11:635–641CrossRefPubMedGoogle Scholar
  30. 30.
    Carvalho PA, Schwartz RB, Alexander E 3rd et al (1992) Detection of recurrent gliomas with quantitative thallium-201/technetium-99 m HMPAO single-photon emission computerized tomography. J Neurosurg 77:565–570CrossRefPubMedGoogle Scholar
  31. 31.
    Ulmer S, Helle M, Jansen O, Mehdorn HM, Nabavi A (2009) Intraoperative dynamic susceptibility contrast weighted magnetic resonance imaging (iDSC-MRI)—technical considerations and feasibility. Neuroimage 45:38–43CrossRefPubMedGoogle Scholar
  32. 32.
    Chawla S, Wang S, Wolf RL et al (2007) Arterial spin-labeling and MR spectroscopy in the differentiation of gliomas. AJNR Am J Neuroradiol 28:1683–1689CrossRefPubMedGoogle Scholar
  33. 33.
    Senturk S, Oguz KK, Cila A (2009) Dynamic contrast-enhanced susceptibility-weighted perfusion imaging of intracranial tumors: a study using a 3 T MR scanner. Diagn Interv Radiol 15:3–12PubMedGoogle Scholar
  34. 34.
    Knutsson L, van Westen D, Petersen ET et al (2009) Absolute quantification of cerebral blood flow: correlation between dynamic susceptibility contrast MRI and model-free arterial spin labeling. Magn Reson Imaging, doi: 10.1016/j.mri.2009.06.006
  35. 35.
    Petersen ET, Mouridsen K, Golay X, on behalf of all named co-authors of the QUASAR test–retest study (2009) The QUASAR reproducibility study, part II: results from a multi-center arterial spin labeling test–retest study. Neuroimage, doi: 10.1016/j.neuroimage.2009.07.068
  36. 36.
    Andersen C (1997) In vivo estimation of water content in cerebral white matter of brain tumour patients and normal individuals: towards a quantitative brain oedema definition. Acta Neurochir (Wien) 139:249–255 discussion 255–6CrossRefGoogle Scholar
  37. 37.
    Nagesh V, Tsien CI, Chenevert TL et al (2008) Radiation-induced changes in normal-appearing white matter in patients with cerebral tumors: a diffusion tensor imaging study. Int J Radiat Oncol Biol Phys 70:1002–1010PubMedGoogle Scholar
  38. 38.
    Leenders KL, Perani D, Lammertsma AA et al (1990) Cerebral blood flow, blood volume and oxygen utilization. Normal values and effect of age. Brain 113(Pt 1):27–47CrossRefPubMedGoogle Scholar
  39. 39.
    van Gelderen P, de Zwart JA, Duyn JH (2008) Pittfalls of MRI measurement of white matter perfusion based on arterial spin labeling. Magn Reson Med 59:788–795CrossRefPubMedGoogle Scholar
  40. 40.
    Paulson ES, Schmainda KM (2008) Comparison of dynamic susceptibility-weighted contrast-enhanced MR methods: recommendations for measuring relative cerebral blood volume in brain tumors. Radiology 249:601–613CrossRefPubMedGoogle Scholar
  41. 41.
    Zhang H, Rodiger LA, Shen T, Miao J, Oudkerk M (2008) Perfusion MR imaging for differentiation of benign and malignant meningiomas. Neuroradiology 50:525–530CrossRefPubMedGoogle Scholar
  42. 42.
    Weber MA, Zoubaa S, Schlieter M et al (2006) Diagnostic performance of spectroscopic and perfusion MRI for distinction of brain tumors. Neurology 66:1899–1906CrossRefPubMedGoogle Scholar
  43. 43.
    Wolf RL, Wang J, Wang S et al (2005) Grading of CNS neoplasms using continuous arterial spin labeled perfusion MR imaging at 3 Tesla. J Magn Reson Imaging 22:475–482CrossRefPubMedGoogle Scholar
  44. 44.
    Ludemann L, Grieger W, Wurm R, Budzisch M, Hamm B, Zimmer C (2001) Comparison of dynamic contrast-enhanced MRI with WHO tumor grading for gliomas. Eur Radiol 11:1231–1241CrossRefPubMedGoogle Scholar
  45. 45.
    Weber MA, Gunther M, Lichy MP et al (2003) Comparison of arterial spin-labeling techniques and dynamic susceptibility-weighted contrast-enhanced MRI in perfusion imaging of normal brain tissue. Invest Radiol 38:712–718CrossRefPubMedGoogle Scholar
  46. 46.
    Young R, Babb J, Law M, Pollack E, Johnson G (2007) Comparison of region-of-interest analysis with three different histogram analysis methods in the determination of perfusion metrics in patients with brain gliomas. J Magn Reson Imaging 26:1053–1063CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Hanna Järnum
    • 1
  • Elena G. Steffensen
    • 1
  • Linda Knutsson
    • 2
  • Ernst-Torben Fründ
    • 1
    • 3
  • Carsten Wiberg Simonsen
    • 1
  • Søren Lundbye-Christensen
    • 4
  • Ajit Shankaranarayanan
    • 5
  • David C. Alsop
    • 6
  • Finn Taagehøj Jensen
    • 1
  • Elna-Marie Larsson
    • 1
    • 7
  1. 1.Department of RadiologyAalborg Hospital/Århus University HospitalAalborgDenmark
  2. 2.Department of Medical Radiation PhysicsLund UniversityLundSweden
  3. 3.GE Healthcare—Applied Science Lab EuropeAalborgDenmark
  4. 4.Department of Cardiology, Center for Cardiovascular ResearchAalborg Hospital/Århus University HospitalAalborgDenmark
  5. 5.GE HealthcareGlobal Applied Science LabMenlo ParkUSA
  6. 6.Beth Israel Deaconess Medical Center and Harvard Medical SchoolBostonUSA
  7. 7.Department of RadiologyUppsala University HospitalUppsalaSweden

Personalised recommendations