Direct estimation of 17 O MR images (DIESIS) for quantification of oxygen metabolism in the human brain with partial volume correction

Abstract

Purpose: To provide a data post-processing method that corrects for partial volume effects (PVE) and fast $T_2^{*}$ decay in dynamic ¹⁷ O MRI for the mapping of cerebral metabolic rates of oxygen consumption (CMRO₂ ).

Methods: CMRO₂ is altered in neurodegenerative diseases and tumors and can be measured after ¹⁷ O gas inhalation using dynamic ¹⁷ O MRI. CMRO₂ quantification is difficult because of PVE. To correct for PVE, a direct estimation of the MR images (DIESIS) method is proposed and used in 4 dynamic ¹⁷ O MRI data sets of a healthy volunteer acquired on a 3T MRI system. With DIESIS, ¹⁷ O MR signal time curves in selected regions were directly estimated based on parcellation of a coregistered ¹ H MPRAGE image.

Results: Profile likelihood analysis of the DIESIS method showed identifiability of CMRO₂ . In white matter (WM), DIESES reduced CMRO₂ from 0.97 ± 0.25 µmol/g_tissue /min with Kaiser-Bessel gridding reconstruction to 0.85 ± 0.21 µmol/g_tissue /min, whereas in gray matter (GM) it increases from 1.3 ± 0.31 µmol/g_tissue /min to 1.86 ± 0.36 µmol/g_tissue /min; both values are closer to the literature values from the ¹⁵ O-PET studies.

Conclusion: DIESIS provided an increased separation of CMRO₂ values in GM and WM brain regions and corrected for partial volume effects in ¹⁷ O-MRI inhalation experiments. DIESIS could also be applied to more heterogeneous tissues such as glioblastomas if subregions of the tumor can be represented as additional parcels.

Keywords: 17O MRI; cerebral metabolic rate of oxygen consumption (CMRO2); non-proton MRI; oxygen metabolism; partial volume correction.