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Regional effects of magnetization dispersion on quantitative perfusion imaging for pulsed and continuous arterial spin labeling

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons83849

Cavusoglu,  M
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84145

Pohmann,  R
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons83841

Burger,  HC
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84269

Uludag,  K
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Cavusoglu, M., Pohmann, R., Burger, H., & Uludag, K. (2013). Regional effects of magnetization dispersion on quantitative perfusion imaging for pulsed and continuous arterial spin labeling. Magnetic Resonance in Medicine, 69(2), 524–530. doi:10.1002/mrm.24278.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-B504-7
Zusammenfassung
Most experiments assume a global transit delay time with blood flowing from the tagging region to the imaging slice in plug flow without any dispersion of the magnetization. However, because of cardiac pulsation, nonuniform cross-sectional flow profile, and complex vessel networks, the transit delay time is not a single value but follows a distribution. In this study, we explored the regional effects of magnetization dispersion on quantitative perfusion imaging for varying transit times within a very large interval from the direct comparison of pulsed, pseudo-continuous, and dual-coil continuous arterial spin labeling encoding schemes. Longer distances between tagging and imaging region typically used for continuous tagging schemes enhance the regional bias on the quantitative cerebral blood flow measurement causing an underestimation up to 37 when plug flow is assumed as in the standard model.