Oxygen metabolism is altered in brain tumor regions and is quantified by the cerebral metabolic rate of oxygen consumption (CMRO). Direct dynamic O MRI with inhalation of isotopically enriched O gas can be used to quantify CMRO; however, pixel-wise CMRO quantification in human brain is challenging due to low natural abundance of O isotope and, thus, the low signal-to-noise ratio (SNR) of O MR images. To test the feasibility CMRO mapping at a clinical 3 T MRI system, a new iterative reconstruction was proposed, which uses the edge information contained in a co-registered H gradient image to construct a non-homogeneous anisotropic diffusion (AD) filter. AD-constrained reconstruction of O MR images was compared to conventional Kaiser-Bessel gridding without and with Hanning filtering, and to iterative reconstruction with a total variation (TV) constraint. For numerical brain phantom and in two in vivo data sets of one healthy volunteer, AD-constrained reconstruction provided O images with improved resolution of fine brain structures and resulted in higher SNR. CMRO values of 0.78 - 1.55µmol/g/min (white brain matter) and 1.03 - 2.01µmol/g/min (gray brain matter) as well as the CMRO maps are in a good agreement with the results of O-PET and O MRI at 7 T and at 9.4 T. In conclusion, the proposed AD-constrained reconstruction enabled calculation of 3D CMRO maps at 3 T MRI system, which is an essential step towards clinical translation of O MRI for non-invasive CMRO quantification in tumor patients.

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http://dx.doi.org/10.1016/j.neuroimage.2017.05.029DOI Listing

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Oxygen metabolism is altered in brain tumor regions and is quantified by the cerebral metabolic rate of oxygen consumption (CMRO). Direct dynamic O MRI with inhalation of isotopically enriched O gas can be used to quantify CMRO; however, pixel-wise CMRO quantification in human brain is challenging due to low natural abundance of O isotope and, thus, the low signal-to-noise ratio (SNR) of O MR images. To test the feasibility CMRO mapping at a clinical 3 T MRI system, a new iterative reconstruction was proposed, which uses the edge information contained in a co-registered H gradient image to construct a non-homogeneous anisotropic diffusion (AD) filter.

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