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Improved calculation of the equilibrium magnetization of arterial blood in arterial spin labeling

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PURPOSE: To propose and assess an improved method for calculating the equilibrium magnetization of arterial blood ( M0a), used for calibration of perfusion estimates in arterial spin labeling.

METHODS: Whereas standard M0a calculation is based on dividing a proton density-weighted image by an average brain-blood partition coefficient, the proposed method exploits partial-volume data to adjust this ratio. The nominator is redefined as the magnetization of perfused tissue, and the denominator is redefined as a weighted sum of tissue-specific partition coefficients. Perfusion data were acquired with a pseudo-continuous arterial spin labeling sequence, and partial-volume data were acquired using a rapid saturation recovery sequence with the same readout module. Results from 7 healthy volunteers were analyzed and compared with the conventional method.

RESULTS: The proposed method produced improved M0a homogeneity throughout the brain in all subjects. The mean gray matter perfusion was significantly higher with the proposed method compared with the conventional method: 61.2 versus 56.3 mL/100 g/minute (+8.7%). Although to a lesser degree, the corresponding white matter values were also significantly different: 20.8 versus 22.0 mL/100 g/minute (-5.4%). The spatial and quantitative differences between the 2 methods were similar in all subjects.

CONCLUSION: Compared with the conventional approach, the proposed method produced more homogenous M0a maps, corresponding to a more accurate calibration. The proposed method also yielded significantly different perfusion values across the whole brain, and performed consistently in all subjects. The new M0a method improves quantitative perfusion estimation with arterial spin labeling, and can therefore be of considerable value in perfusion imaging applications.

Original languageEnglish
JournalMagnetic Resonance in Medicine
Volume80
Issue number5
Pages (from-to)2223-2231
ISSN0740-3194
DOIs
Publication statusPublished - Nov 2018

    Research areas

  • Journal Article

ID: 53548351