QSM with a minimal variation in ventricular CSF is viable to provide a consistent zero reference while improving image quality. Magn Reson Med 79:2795-2803, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Quantitative CMRO mapping that fits the entire complex GRE data is feasible by combining QSM analysis of phase and qBOLD analysis of magnitude.

Purpose: To improve the accuracy of QSM plus quantitative blood oxygen leveldependent magnitude (QSM + qBOLD or QQ)-based mapping of the oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO 2 ) using cluster analysis of time evolution (CAT). Methods: 3D multi-echo gradient echo and arterial spin labeling images were acquired in 11 healthy subjects and 5 ischemic stroke patients. DWI was also carried out on patients. CAT was developed for analyzing signal evolution over TE.QQ-based OEF and CMRO 2 were reconstructed with and without CAT, and results were compared using region of interest analysis and a paired t-test. Results: Simulations demonstrated that CAT substantially reduced noise error in QQ-based OEF. In healthy subjects, QQ-based OEF appeared less noisy and more uniform with CAT than without CAT; average OEF with and without CAT in cortical gray matter was 32.7 ± 4.0% and 37.9 ± 4.5%, with corresponding CMRO 2 of 148.4 ± 23.8 and 171.4 ± 22.4 μmol/100 g/min, respectively. In patients, regions of low OEF were confined within the ischemic lesions defined on DWI when using CAT, which was not observed without CAT. Conclusion: The cluster analysis of time evolution (CAT) significantly improves the robustness of QQ-based OEF against noise. K E Y W O R D Scerebral metabolic rate of oxygen, cluster analysis of time evolution, K-means, machine learning, oxygen extraction fraction, quantitative blood oxygenation level-dependent imaging, quantitative susceptibility mapping

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The underestimation originates from the signal formation in a voxel, which can be described by the voxel sensitivity function. The amount of underestimation is thus affected by imaging resolution, magnitude contrast, image filtering, and details of the susceptibility inclusions such as the susceptibility value and geometry. High-resolution imaging is therefore needed for accurate reconstruction of QSM values, especially at higher susceptibilities. Magn Reson Med 78:1080-1086, 2017. © 2016 International Society for Magnetic Resonance in Medicine.