Voxel-wise partial volume correction method for accurate estimation of tissue sodium concentration in 23 Na-MRI at 7 T.

Sodium is crucial for the maintenance of cell physiology, and its regulation of the sodium-potassium pump has implications for various neurological conditions. The distribution of sodium concentrations in tissue can be quantitatively evaluated by means of sodium MRI (23 Na-MRI). Despite its usefulness in diagnosing particular disease conditions, tissue sodium concentration (TSC) estimated from 23 Na-MRI can be strongly biased by partial volume effects (PVEs) that are induced by broad point spread functions (PSFs) as well as tissue fraction effects. In this work, we aimed to propose a robust voxel-wise partial volume correction (PVC) method for 23 Na-MRI. The method is based on a linear regression (LR) approach to correct for tissue fraction effects, but it utilizes a 3D kernel combined with a modified least trimmed square (3D-mLTS) method in order to minimize regression-induced inherent smoothing effects. We acquired 23 Na-MRI data with conventional Cartesian sampling at 7 T, and spill-over effects due to the PSF were considered prior to correcting for tissue fraction effects using 3D-mLTS. In the simulation, we found that the TSCs of gray matter (GM) and white matter (WM) were underestimated by 20% and 11% respectively without correcting tissue fraction effects, but the differences between ground truth and PVE-corrected data after the PVC using the 3D-mLTS method were only approximately 0.6% and 0.4% for GM and WM, respectively. The capability of the 3D-mLTS method was further demonstrated with in vivo 23 Na-MRI data, showing significantly lower regression errors (ie root mean squared error) as compared with conventional LR methods (p < 0.001). The results of simulation and in vivo experiments revealed that 3D-mLTS is superior for determining under- or overestimated TSCs while preserving anatomical details. This suggests that the 3D-mLTS method is well suited for the accurate determination of TSC, especially in small focal lesions associated with pathological conditions.

Assessment of mesoscopic properties of deep gray matter iron through a model-based simultaneous analysis of magnetic susceptibility and R2* - A pilot study in patients with multiple sclerosis and normal controls.

Most studies of brain iron relied on the effect of the iron on magnetic resonance (MR) relaxation properties, such as R2∗, and bulk tissue magnetic susceptibility, as measured by quantitative susceptibility mapping (QSM). The present study exploited the dependence of R2∗ and magnetic susceptibility on physical interactions at different length-scales to retrieve information about the tissue microenvironment, rather than the iron concentration. We introduce a method for the simultaneous analysis of brain tissue magnetic susceptibility and R2∗ that aims to isolate those biophysical mechanisms of R2∗ -contrast that are associated with the micro- and mesoscopic distribution of iron, referred to as the Iron Microstructure Coefficient (IMC). The present study hypothesized that changes in the deep gray matter (DGM) magnetic microenvironment associated with aging and pathological mechanisms of multiple sclerosis (MS), such as changes of the distribution and chemical form of the iron, manifest in quantifiable contributions to the IMC. To validate this hypothesis, we analyzed the voxel-based association between R2∗ and magnetic susceptibility in different DGM regions of 26 patients with multiple sclerosis and 33 age- and sex-matched normal controls. Values of the IMC varied significantly between anatomical regions, were reduced in the dentate and increased in the caudate of patients compared to controls, and decreased with normal aging, most strongly in caudate, globus pallidus and putamen.