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Qualitative and Quantitative Perfusion Parameters Determined by 3D Single-Shot GRASE ASL MR Imaging

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DOI: 10.4236/ojmi.2012.21001    3,263 Downloads   6,268 Views   Citations


Rationale and Objectives: A particular arterial spin (ASL) labeling technique, called 3D-single-shot GRASE ASL is discussed with respect to the ability and limits of quantifying perfusion parameters. Materials and Methods: The technique enables the acquisition of perfusion weighted signal at multiple delay times (TI) in one scan. The readout part is a gradient and spin-echo combination (GRASE) that uses switched gradient rephrasing of signals to produce several times as many signals as turbo-spin-echo, which translates into faster imaging time and higher signal-to-noise ratio (SNR) per imaging time. The technique provides the possibility for model based quantification of cerebral blood flow and the determination of the bolus arrival information without use of contrast agent and thus the characterization and determina-tion of regions that are supported by collaterals. Results: Whereas for a quantification of the permeability using ASL the SNR is not high enough, at least qualitative permeability maps can be determined, if an optimal homogenous SNR was guaranteed. This was accomplished in brain regions with a high blood supply, typically given in tumors, and by using a correction for coil sensitivity at the highest possible additional scaling. Conclusion: The single-shot 3D GRASE ASL can provide information about the principal blood supply, the transit delay of the blood flow due to a stenosis or collaterals and a qualitative measure of the permeability.

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C. Kiefer, F. Kellner-Weldon, M. El-Koussy, M. Hauf and G. Schroth, "Qualitative and Quantitative Perfusion Parameters Determined by 3D Single-Shot GRASE ASL MR Imaging," Open Journal of Medical Imaging, Vol. 2 No. 1, 2012, pp. 1-9. doi: 10.4236/ojmi.2012.21001.


[1] J. A. Detre, W. G. Zhang, D. A. Roberts, A. C. Silva, D. S. Williams, D. J. Grandis, A. P. Koretsky and J. S. Leigh, “Tissue Specific Perfusion Imaging Using Arterial Spin Labeling,” NMR in Biomedicine, Vol. 7, No. 1-2, 1994, pp. 75-82. doi:10.1002/nbm.1940070112
[2] E. C. Wong, R. B. Buxton and L. R. Frank, “A Theoretical and Experimental Comparison of Continuous and Pulsed Arterial Spin Labeling Techniques for Quantitative Perfusion Imaging,” Magnetic Resonance in Medicine, Vol. 40, No. 3, 1998, pp. 348-355. doi:10.1002/mrm.1910400303
[3] W. C. Wu, M. Fernandez-Seara, J. A. Detre, et al. “A Theoretical and Experimental Investigation of the Tagging Efficiency of Pseudocontinuous Arterial Spin Labeling,” Magnetic Resonance in Medicine, Vol. 58, No. 5, 2007, pp. 1020-1027. doi:10.1002/mrm.21403
[4] T. Mildner, H. E. Moller, W. Driesel, et al. “Continuous Arterial Spin Labeling at the Human Common Carotid Artery: the Influence of Transit Times,” NMR in Biomedicine, Vol. 18, No. 1, 2005, pp. 19-23. doi:10.1002/nbm.917
[5] D. C. Alsop and J. A. Detre, “Reduced Transit Time Sensitivity in Noninvasive Magnetic Resonance Imaging of Human Cerebral Blood Flow,” Journal of Cerebral Blood Flow & Metabolism, Vol. 16, No. 6, 1996, pp. 1236-1249. doi:10.1097/00004647-199611000-00019
[6] M. Guenther, K. Oshio and D. A. Feinberg, “Single-Shot 3D Imaging Techniques Improve Arterial Spin Labeling Perfusion Measurements,” Magnetic Resonance in Medicine, Vol. 54, No. 2, 2005, pp. 491-498. doi:10.1002/mrm.20580
[7] L. M. Parkes and P. S. Tofts, “Improved Accuracy of Human Cerebral Blood Perfusion Measurements Using Arterial Spin Labeling: Accounting for Capillary Water Permeability,” Magnetic Resonance in Medicine, Vol. 48, No. 1, 2005, pp. 27-41. doi:10.1002/mrm.10180
[8] F. Q. Ye, J. A. Frank, D. R. Weinberger, et al., “Noise Reduction in 3D Perfusion Imaging by Attenuating the Static Signal in Arterial Spin Tagging (ASSIST),” Magnetic Resonance in Medicine, Vol. 44, No. 1, 2000, pp. 92-100. doi:10.1002/1522-2594(200007)44:1<92::AID-MRM14>3.0.CO;2-M
[9] S. Mani, J. Pauly, S. Conolly, et al., “Background Suppression with Multiple Inversion Recovery Nulling: Applications to Projective Angiography,” Magnetic Resonance in Medicine, Vol. 37, No. 6, 1997, pp. 898-905. doi:10.1002/mrm.1910370615
[10] S. G. Kim, “Quantification of Relative Cerebral Blood Flow Change by Flow-Sensitive Alternating Inversion Recovery (FAIR) Technique: Application to Functionalmapping,” Magnetic Resonance in Medicine, Vol. 34, No. 3, 1995, pp. 293-301. doi:10.1002/mrm.1910340303
[11] O. B. Paulson, M. M. Hertz, T. G. Bolwig, et al., “Filtration and Diffusion of Water across the Blood-Brain Barrier in Man,” Microvascular Research, Vol. 13, No. 1, 1997, pp. 113-124. doi:10.1016/0026-2862(77)90120-0
[12] Nordic Software.
[13] J. L. oxerman, K. M. Schmainda and R. M. Weisskoff, “Relative Cerebral Blood Volume Maps Corrected for Contrast Agent Extravasation Significantly Correlate with Glioma Tumor Grade, Whereas Uncorrected Maps Do Not,” American Journal of Neuroradiology, Vol. 27, No. 4, 2006, pp. 859-867.
[14] R. Pohmann, “Accurate, Localized Quantification of White Matter Perfusion with Single-Voxel ASL,” Magnetic Resonance in Medicine, Vol. 64, No. 4, 2010, pp. 1109-1113. doi:10.1016/0026-2862(77)90120-0
[15] J. P. Carr, D. L. Buckley, J. Tessier, et al., “What Levels of Precision Are Achievable for Quantification of Perfusion and Capillary Permeability Surface Area Product Using ASL?” Magnetic Resonance in Medicine, Vol. 58, No. 2, 2007, pp. 281-289. doi:10.1002/mrm.21317

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