Magnetic Resonance Imaging
Volume 24, Issue 5 , Pages 619-623 , June 2006

Correcting the effects of background microcirculation in the measurement of arterial input functions using dynamic susceptibility contrast MRI of the brain

  • Robert J. Thornton

      Affiliations

    • Department of Radiology, Baylor College of Medicine, Houston, TX 77030, USA
    • Edward B. Singleton Department of Diagnostic Imaging, Texas Children's Hospital, Houston, TX 77030, USA
    • ,
  • Jeremy Y. Jones

      Affiliations

    • Department of Radiology, Baylor College of Medicine, Houston, TX 77030, USA
    • Edward B. Singleton Department of Diagnostic Imaging, Texas Children's Hospital, Houston, TX 77030, USA
    • ,
  • Zhiyue J. Wang

      Affiliations

    • Department of Radiology, Baylor College of Medicine, Houston, TX 77030, USA
    • Edward B. Singleton Department of Diagnostic Imaging, Texas Children's Hospital, Houston, TX 77030, USA
    • Corresponding Author InformationCorresponding author. Department of Diagnostic Imaging, Texas Children's Hospital, 6621 Fannin St., MC2-2521, Houston, TX 77030, USA. Tel.: +1 832 824 5338; fax: +1 832 825 5241.

Received 6 June 2005 ,Revised 6 December 2005 ,Accepted 6 December 2005.

References 

  1. Rosen BR, Belliveau JW, Aronen HJ, et al. Susceptibility contrast imaging of cerebral blood volume: human experience. Magn Reson Med. 1991;22:293–299
  2. Kiselev VG. On the theoretical bases of perfusion measurements by dynamic susceptibility contrast MRI. Magn Reson Med. 2001;46:1113–1122
  3. Lev MH, Rosen BR. Clinical applications of intracranial perfusion MR imaging. Neuroimaging Clin N Am. 1999;9:309–331
  4. Cha S. Perfusion MR imaging: basic principles and clinical applications. Magn Reson Imaging Clin N Am. 2003;11:403–413
  5. Grandin CB. Assessment of brain perfusion with MRI: methodology and application to acute stroke. Neuroradiology. 2003;45:755–766
  6. Covarrubias DJ, Rosen BR, Lev MH. Dynamic magnetic resonance perfusion imaging of brain tumors. The Oncologist. 2004;9:528–537
  7. Calamente F, Gadian DG, Connelly A. Quantification of perfusion using bolus tracking magnetic resonance imaging in stroke: assumptions, limitations, and potential implications for clinical use. Stroke. 2002;33:1146–1151
  8. van Osch MJ, Vonken EJ, Viergever MA, van der Grond J, Bakker CJ. Measuring the arterial input function with gradient echo sequences. Magn Reson Med. 2003;49:1067–1076
  9. Ostergaard L, Sorensen A, Kwong K, Weisskoff R, Gyldensted C, Rosen B. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages: Part II. Experimental comparison and preliminary results. Magn Reson Med. 1996;36:726–736
  10. Rausch M, Scheffler K, Rudin M, Radü EW. Analysis of input functions from different arterial branches with gamma variate functions and cluster analysis for quantitative blood volume measurements. Magn Reson Imaging. 2000;18:1235–1243
  11. Duhamel G, de Bazelaire M, Alsop DC. Input function from echoplanar hemodynamic studies using dynamic susceptibility contrast: A numerical model compared to in vivo results. Proc Intl Soc Mag Reson Med. 2003;11:2199
  12. Butman JA, Tasciyan T. Automated computation of the arterial input function for dynamic susceptibility bolus tracking brain perfusion MRI. Proc Intl Soc Magn Reson Med. 2005;13:1126
  13. Murase K, Kikuchi K, Miki H, Shimizu T, Ikezoe J. Determination of arterial input functions using fuzzy clustering for quantification of cerebral blood flow with dynamic susceptibility contrast-enhanced MR imaging. J Magn Reson Imaging. 2001;13:797–806
  14. Calemente F, Gadian DG, Connelly A. Delay and dispersion effects in dynamic susceptibility contrast MRI: simulations using singular value decomposition. Magn Reson Med. 2000;44:466–473
  15. Wu O, Ostergaard L, Koroshetz WJ, et al. Effects of tracer arrival time on flow estimates in MR perfusion-weighted imaging. Magn Reson Med. 2003;50:856–864
  16. Calamente F, Yim PJ, Cebral JR. Estimation of bolus dispersion effects in perfusion MRI using image-based computational fluid dynamics. NeuroImage. 2003;19:341–353
  17. Liu HL, Pu Y, Liu Y, et al. Cerebral blood flow measurement by dynamic contrast MRI using singular value decomposition with an adaptive threshold. Magn Reson Med. 1999;42:167–172
  18. Ostergaard L. Cerebral perfusion imaging by bolus tracking. Top Magn Reson Imaging. 2004;3–9
  19. Perkio J, Aronen HJ, Kangasmaki A, et al. Evaluation of four postprocessing methods for determination of cerebral blood volume and mean transit time by dynamic susceptibility contrast imaging. Magn Reson Med. 2002;47:973–981
  20. Takahashi T, Shirane R, Sato S, Yoshimoto T. Developmental changes of cerebral blood flow and oxygen metabolism in children. Am J Neuroradiol. 1999;20:917–922
  21. Ibaraki M, Shimosegawa E, Toyoshima H, Takahashi K, Miura S, Kanno I. Tracer delay correction of cerebral blood flow with dynamic susceptibility contrast-enhanced MRI. J Cereb Blood Flow Metab. 2005;25:378–390
  22. Wu O, Ostergaard L, Weisskoff RM, Benner T, Rosen BR, Sorensen AG. Tracer arrival timing-insensitive technique for estimating flow in MR perfusion-weighted imaging using singular value decomposition with a block-circulant deconvolution matrix. Magn Reson Med. 2003;50:164–174
  23. Knutsson L, Stahlberg F, Wirestam R. Aspects on the accuracy of cerebral perfusion parameters obtained by dynamic susceptibility contrast MRI: a simulation study. Magn Reson Imaging. 2004;22:789–798

PII: S0730-725X(06)00008-7

doi: 10.1016/j.mri.2005.09.014

Magnetic Resonance Imaging
Volume 24, Issue 5 , Pages 619-623 , June 2006

Article Tools

* Image Usage & Resolution