This study (1) presents a method how to investigate electric conductivity of deep gray matter nuclei, and (2) reports conductivity values of deep gray matter nuclei of healthy volunteers as reference for corresponding future clinical studies.Deep gray matter nuclei (DGMN) in the human brain play an important role for numerous diseases like Alzheimer’s, Parkinson's, or Huntington’s disease. Thus, the characterization of DGMN in the framework of the multiple MR-based physiologic parameters (like magnetic susceptibility or electric conductivity) is expected to be helpful for understanding these diseases. This study investigates the electric conductivity of DGMN in healthy volunteers, applying phase-based “Electric Properties Tomography” (EPT) [1].Electric conductivity can be derived from the MR phase image, as long as this phase is only related to B₁ effects and not affected by B₀ effects (i.e., main field inhomogeneity or off-resonance) [1]. This condition is fulfilled, e.g., for spin-echo-based sequences and for steady-state-free-precession (SSFP) sequences. Due to their superior SNR efficiency, SSFP sequences outperform spin-echo-based sequences, and thus, are frequently used for phase-based EPT [2,3]. On the other hand, conductivity reconstruction benefits from including a-priori knowledge about delineation of different tissue areas, since EPT is typically undefined along tissue boundaries [1]. Unfortunately, DGMN yield very weak contrast on SSFP images, hampering a reliable delineation of these areas. Contrast of DGMN is much higher on quantitative susceptibility maps due to their varying iron content [4]. Thus, this study utilizes quantitative susceptibility mapping (QSM) for delineation of DGMN as geometric input for conductivity reconstructions based on SSFP phase images.The study investigated 18 healthy volunteers (all male, age 33-60, informed consent obtained) with a commercial 3T system (Philips Ingenia, Best, The Netherlands). For all volunteers, SSFP scans were performed to obtain the B₁-related phase (TR/TE = 3.3/1.6 ms, flip angle 25°, voxel size 0.9×0.9×1.0 mm³). Additionally, susceptibility maps were acquired based on 7-echo Fast-Field-Echo (FFE) scans (TR/TE/ΔTE = 30/3/4 ms, flip angle 14°, voxel size 0.6×0.6×1.0 mm³) for all volunteers. Quantitative susceptibilities maps were reconstructed using an algorithm jointly performing background field removal and dipole inversion [5], and registered to the SSFP scan of the corresponding volunteer. With φ the image phase, μ₀ the magnetic vacuum permeability, and ω the Larmor frequency, conductivity σ was reconstructed via $$$ σ = {\nabla}^2φ/(2μ_0ω) $$$ and a subsequent median filter [1,6]. Kernel size of both, numerical differentiation and median filter, was locally adapted not to cross tissue boundaries [6,7]. In a first run, these tissue boundaries were identified by a Sobel filter from the SSFP magnitude image of each individual volunteer. In a second run, tissue boundaries were additionally identified by a Sobel filter from calculated susceptibility maps of each individual volunteer, and combined with the boundaries obtained from the SSFP magnitude images of the first run.As expected, applying tissue boundaries from SSFP magnitude images yields a very weak conductivity contrast for the DGMN, but additionally including tissue boundaries from susceptibility maps yields a clear conductivity contrast for the DGMN (see Fig. 1 for one of the volunteers). Conductivities averaged over the 18 volunteers for six DGMN are shown in Fig. 2. The SSFP-based delineation yields a rather constant conductivity of 0.64-0.78 S/m for all DGMN. Including the susceptibility-based delineation yields conductivity values of 0.58-0.90 S/m, thus distinguishing different DGMN more clearly. - A comparison of mean conductivity and mean susceptibility values did not show any correlation, i.e., conductivity and susceptibility appear as independent parameters.To the best of our knowledge, this is the first time that conductivity of deep gray matter nuclei (DGMN) has been determined quantitatively in vivo. The conductivity determination was boosted by utilizing geometrical a-priori knowledge from quantitative susceptibility maps. In combination with the additional information from the susceptibility maps, a more comprehensive characterization of these diagnostically important brain regions is obtained. Instead applying two different scans to measure B₁ phase and QSM as in the current study, combined scans can be applied as suggested in [8]. Such combined scans might help to confirm the findings of the current study.