MR venography of the human brain using susceptibility weighted imaging at very high field strength

  • Peter J. Koopmans
  • Rashindra Manniesing
  • Wiro J. Niessen
  • Max A. Viergever
  • Markus Barth
Research Article

Abstract

Objective

We investigate the implications of high magnetic field strength on MR venography based on susceptibility-weighted imaging (SWI) and estimate the optimum echo time to obtain maximum contrast between blood and brain tissue.

Materials and methods

We measured tissue contrast and T2* relaxation times at 7 T of gray matter, white matter, and venous blood in vivo.

Results

T2* relaxation times of gray matter, white matter, and venous blood in vivo yielded 32.9 ± 2.3, 27.7 ± 4.3, and 7.4 ± 1.4 ms, respectively. Optimum TE was found to be 15 ms which is supported by theoretical considerations. Using this optimum TE, we acquired 3D high resolution datasets with a large volume coverage in a short measurement time that show very detailed microanatomical structures of the human brain such as intracortical veins and laminar cortical substructures.

Conclusions

By applying optimised vessel filters (vesselness filter and vessel enhancing diffusion) whole brain MR venograms can be obtained at 7 T with a significantly reduced measurement time compared to 3 T.

Keywords

Neuroimaging Venography 3 T 7 T Parallel imaging Vessel segmentation Vessel enhancing diffusion Transverse relaxation times 

References

  1. 1.
    Haacke EM, Xu Y, Cheng YC, Reichenbach JR (2004) Susceptibility weighted imaging (SWI). Magn Reson Med 52(3): 612–618CrossRefPubMedGoogle Scholar
  2. 2.
    Ogawa S, Lee TM, Nayak AS, Glynn P (1990) Oxygenation-sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields. Magn Reson Med 14(1): 68–78CrossRefPubMedGoogle Scholar
  3. 3.
    Reichenbach JR, Essig M, Haacke EM, Lee BC, Przetak C, Kaiser WA, Schad LR (1998) High-resolution venography of the brain using magnetic resonance imaging. Magn Reson Mater Phys (MAGMA) 6(1): 62–69CrossRefGoogle Scholar
  4. 4.
    Reichenbach JR, Haacke EM (2001) High-resolution BOLD venographic imaging: a window into brain function. NMR Biomed 14(7–8): 453–467CrossRefPubMedGoogle Scholar
  5. 5.
    Reichenbach JR, Venkatesan R, Schillinger DJ, Kido DK, Haacke EM (1997) Small vessels in the human brain: MR venography with deoxyhemoglobin as an intrinsic contrast agent. Radiology 204(1): 272–277PubMedGoogle Scholar
  6. 6.
    Barth M, Nobauer-Huhmann IM, Reichenbach JR, Mlynarik V, Schoggl A, Matula C, Trattnig S (2003) High-resolution three-dimensional contrast-enhanced blood oxygenation level-dependent magnetic resonance venography of brain tumors at 3 Tesla: first clinical experience and comparison with 1.5 Tesla. Invest Radiol 38(7): 409–414CrossRefPubMedGoogle Scholar
  7. 7.
    Rauscher A, Sedlacik J, Fitzek C, Walter B, Hochstetter A, Kalff R, Kaiser WA, Reichenbach JR (2005) High resolution susceptibility weighted MR-imaging of brain tumors during the application of a gaseous agent. Rofo 177(8): 1065–1069PubMedGoogle Scholar
  8. 8.
    Sehgal V, Delproposto Z, Haddar D, Haacke EM, Sloan AE, Zamorano LJ, Barger G, Hu J, Xu Y, Prabhakaran KP, Elangovan IR, Neelavalli J, Reichenbach JR (2006) Susceptibility-weighted imaging to visualize blood products and improve tumor contrast in the study of brain masses. J Magn Reson Imaging 24(1): 41–51CrossRefPubMedGoogle Scholar
  9. 9.
    Noebauer-Huhmann IM, Pinker K, Barth M, Mlynarik V, Ba-Ssalamah A, Saringer WF, Weber M, Benesch T, Witoszynskyj S, Rauscher A, Reichenbach JR, Trattnig S (2006) Contrast-enhanced, high-resolution, susceptibility-weighted magnetic resonance imaging of the brain: dose-dependent optimization at 3 tesla and 1.5 tesla in healthy volunteers. Invest Radiol 41(3): 249–255CrossRefPubMedGoogle Scholar
  10. 10.
    Tong KA, Ashwal S, Holshouser BA, Shutter LA, Herigault G, Haacke EM, Kido DK (2003) Hemorrhagic shearing lesions in children and adolescents with posttraumatic diffuse axonal injury: improved detection and initial results. Radiology 227(2): 332–339CrossRefPubMedGoogle Scholar
  11. 11.
    Hermier M, Nighoghossian N (2004) Contribution of susceptibility-weighted imaging to acute stroke assessment. Stroke 35(8): 1989–1994CrossRefPubMedGoogle Scholar
  12. 12.
    Tan IL, van Schijndel RA, Pouwels PJ, van Walderveen MA, Reichenbach JR, Manoliu RA, Barkhof F (2000) MR venography of multiple sclerosis. AJNR Am J Neuroradiol 21(6): 1039–1042PubMedGoogle Scholar
  13. 13.
    Barth M, Norris DG (2007) Very high-resolution three-dimensional functional MRI of the human visual cortex with elimination of large venous vessels. NMR Biomed 20(5): 477–484CrossRefPubMedGoogle Scholar
  14. 14.
    Wiesinger F, Van de Moortele PF, Adriany G, De Zanche N, Ugurbil K, Pruessmann KP (2006) Potential and feasibility of parallel MRI at high field. NMR Biomed 19(3): 368–378CrossRefPubMedGoogle Scholar
  15. 15.
    Yablonskiy DA, Haacke EM (1994) Theory of NMR signal behavior in magnetically inhomogeneous tissues: the static dephasing regime. Magn Reson Med 32(6): 749–763CrossRefPubMedGoogle Scholar
  16. 16.
    Griswold MA, Jakob PM, Heidemann RM, Nittka M, Jellus V, Wang J, Kiefer B, Haase A (2002) Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med 47(6): 1202–1210CrossRefPubMedGoogle Scholar
  17. 17.
    Rauscher A, Barth M, Reichenbach JR, Stollberger R, Moser E (2003) Automated unwrapping of MR phase images applied to BOLD MR-venography at 3 Tesla. J Magn Reson Imaging 18(2): 175–180CrossRefPubMedGoogle Scholar
  18. 18.
    Witoszynskyj S, Rauscher A, Reichenbach JR, Barth M (2005) Automated phase unwrapping of MR images at different field strengths using multiple quality maps. In: Proceedings of the ISMRM, p 2249Google Scholar
  19. 19.
    Witoszynskyj S, Rauscher A, Reichenbach JR, Barth M (2007) Φ UN (Φ ase UNwrapping)—validation of a 2D region-growing phase unwrapping program. In: Proceedings of the ISMRM, p 3436Google Scholar
  20. 20.
    Frangi AF, Niessen WJ, Vincken KL, Viergever MA (1998) Multiscale vessel enhancement filtering. In: Wells WM (ed) III ACFCaSD, LNCS, pp 130–137Google Scholar
  21. 21.
    Manniesing R, Viergever MA, Niessen WJ (2006) Vessel enhancing diffusion—a scale space representation of vessel structures. Med Image Anal 10(6): 815–825CrossRefPubMedGoogle Scholar
  22. 22.
    Koopmans PJ, Manniesing R, Norris DG, Viergever M, Niessen WJ, Barth M (2006) Vein segmentation from 3D high resolution MR venograms by using vessel enhancing diffusion. European Society for Magnetic Resonance in Medicine and Biology, Warsaw, p 361Google Scholar
  23. 23.
    Peters AM, Brookes MJ, Hoogenraad FG, Gowland PA, Francis ST, Morris PG, Bowtell R (2007) T(2)* measurements in human brain at 1.5, 3 and 7 T. Magn Reson Imaging 25(6): 748–753CrossRefPubMedGoogle Scholar
  24. 24.
    Reichenbach JR, Barth M, Haacke EM, Klarhofer M, Kaiser WA, Moser E (2000) High-resolution MR venography at 3.0 Tesla. J Comput Assist Tomogr 24(6): 949–957CrossRefPubMedGoogle Scholar
  25. 25.
    Haacke EM, Lai S, Yablonskiy DA, Lin W (1995) In vivo validation of the BOLD mechanism: a review of signal changes in gradient echo functional MRI in the presence of flow. Int J Imaging Syst Technol 6: 153–163CrossRefGoogle Scholar
  26. 26.
    Pawlik G, Rackl A, Bing RJ (1981) Quantitative capillary topography and blood flow in the cerebral cortex of cats: an in vivo microscopic study. Brain Res 208(1): 35–58CrossRefPubMedGoogle Scholar
  27. 27.
    Spees WM, Yablonskiy DA, Oswood MC, Ackerman JJ (2001) Water proton MR properties of human blood at 1.5 Tesla: magnetic susceptibility, T(1), T(2), T*(2), and non-Lorentzian signal behavior. Magn Reson Med 45(4): 533–542CrossRefPubMedGoogle Scholar
  28. 28.
    Xu Y, Haacke EM (2006) The role of voxel aspect ratio in determining apparent vascular phase behavior in susceptibility weighted imaging. Magn Reson Imaging 24(2): 155–160CrossRefPubMedGoogle Scholar
  29. 29.
    Sedlacik J, Rauscher A, Reichenbach JR (2007) Obtaining Blood Oxygenation Levels from MR Signal Behaviour in the Presence of Single Venous Vessels. Magn Reson Med 58(5): 1035–44CrossRefPubMedGoogle Scholar
  30. 30.
    Duyn JH, Van Gelderen P, Li TQ, de Zwart JA, Koretsky AP, Fukunaga M (2007) High-field MRI of brain cortical substructure based on signal phase. Proc Natl Acad Sci USA 104: 11796–11801CrossRefPubMedGoogle Scholar
  31. 31.
    Deistung A, Kocinski M, Szczypinski P, Materka A, Reichenbach JR (2006) Segmentation of venous vessels using multi-scale vessel enhancement filtering in susceptibility weighted imaging. In: Proceedings of the ISMRM, ISMRM, Seattle, p 1948Google Scholar
  32. 32.
    Rauscher A, Sedlacik J, Barth M, Mentzel HJ, Reichenbach JR (2005) Magnetic susceptibility-weighted MR phase imaging of the human brain. AJNR Am J Neuroradiol 26(4): 736–742PubMedGoogle Scholar
  33. 33.
    Haacke EM, Cheng NY, House MJ, Liu Q, Neelavalli J, Ogg RJ, Khan A, Ayaz M, Kirsch W, Obenaus A (2005) Imaging iron stores in the brain using magnetic resonance imaging. Magn Reson Imaging 23(1): 1–25CrossRefPubMedGoogle Scholar
  34. 34.
    Ogg RJ, Langston JW, Haacke EM, Steen RG, Taylor JS (1999) The correlation between phase shifts in gradient-echo MR images and regional brain iron concentration. Magn Reson Imaging 17(8): 1141–1148CrossRefPubMedGoogle Scholar
  35. 35.
    Bolan PJ, Yacoub E, Garwood M, Ugurbil K, Harel N (2006) In vivo micro-MRI of intracortical neurovasculature. Neuroimage 32(1): 62–69CrossRefPubMedGoogle Scholar
  36. 36.
    Pfeuffer J, Merkle H, Beyerlein M, Steudel T, Logothetis NK (2004) Anatomical and functional MR imaging in the macaque monkey using a vertical large-bore 7 Tesla setup. Magn Reson Imaging 22(10): 1343–1359CrossRefPubMedGoogle Scholar
  37. 37.
    Chien D, Levin DL, Anderson CM (1994) MR gradient echo imaging of intravascular blood oxygenation: T 2* determination in the presence of flow. Magn Reson Med 32(4): 540–545CrossRefPubMedGoogle Scholar
  38. 38.
    Barth M, Moser E (1997) Proton NMR relaxation times of human blood samples at 1.5 T and implications for functional MRI. Cell Mol Biol 43(5): 783–791PubMedGoogle Scholar
  39. 39.
    Yacoub E, Shmuel A, Pfeuffer J, VanDe Moortele PF, Adriany G, Andersen P, Vaughan JT, Merkle H, Ugurbil K, Hu X (2001) Imaging brain function in humans at 7 Tesla. Magn Reson Med 45(4): 588–594CrossRefPubMedGoogle Scholar
  40. 40.
    Kruger G, Kastrup A, Glover GH (2001) Neuroimaging at 1.5 T and 3.0 T: comparison of oxygenation-sensitive magnetic resonance imaging. Magn Reson Med 45(4): 595–604CrossRefPubMedGoogle Scholar
  41. 41.
    Wansapura JP, Holland SK, Dunn RS, Ball WS (1999) NMR relaxation times in the human brain at 3.0 T. J Magn Reson Imaging 9(4): 531–538CrossRefPubMedGoogle Scholar
  42. 42.
    Li TQ, van Gelderen P, Merkle H, Talagala L, Koretsky AP, Duyn J (2006) Extensive heterogeneity in white matter intensity in high-resolution T2*-weighted MRI of the human brain at 7.0 T. Neuroimage 32(3): 1032–1040CrossRefPubMedGoogle Scholar
  43. 43.
    Blockley NP, Francis ST, Gowland PA (2006) Dependence of R2* on oxygenation and contrast agent concentration in human blood at 3 T. In: Proceedings of the ISMRM, Seattle, p 2516Google Scholar

Copyright information

© ESMRMB 2008

Authors and Affiliations

  • Peter J. Koopmans
    • 1
  • Rashindra Manniesing
    • 2
  • Wiro J. Niessen
    • 2
  • Max A. Viergever
    • 3
  • Markus Barth
    • 1
    • 4
  1. 1.F.C. Donders Centre for Cognitive NeuroimagingRadboud University NijmegenNijmegenThe Netherlands
  2. 2.Department of Medical Informatics and RadiologyRotterdamThe Netherlands
  3. 3.Image Sciences InstituteUniversity Medical CenterUtrechtThe Netherlands
  4. 4.Erwin L. Hahn Institute for Magnetic Resonance ImagingUniversity Duisburg-EssenEssenGermany

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