A dedicated phantom for exploring the interplay of fat and paramagnetic substances in quantitative susceptibility mapping.

OBJECTIVE

Accurate quantitative tissue characterization in organs with considerable fat content, like the liver, requires thorough understanding of fat's influence on the MR signal. To continue the investigations into the use of quantitative susceptibility mapping (QSM) in abdominal regions, we present a dedicated phantom that replicates liver-like conditions in terms of effective transverse relaxation rates (R*) and proton density fat fractions.

MATERIALS AND METHODS

The spherical agar phantom consists of nine smaller spheres (diameter: 3 cm) doped with a paramagnetic substance (iron nanoparticles or manganese chloride) and fat (peanut oil), embedded in a large agar sphere (diameter: 14 cm), ensuring no barriers exist between the enclosed spheres and their surrounding medium. Concentrations were selected to represent both healthy and pathologic conditions. 3T MRI measurements for relaxometry, fat-water imaging, and QSM were conducted with the head coil and for H-spectroscopy with the knee coil at three time points, including a scan-rescan assessment and a follow-up measurement 14 months later.

RESULTS

The phantoms' relaxation and magnetic properties are in similar range as reported for liver tissue. Substantial alterations in local field and susceptilibty maps were observed in regions with elevated fat and iron content, where fat correction of the local field via chemical shift-encoded reconstruction effectively reduced streaking artifacts in susceptibility maps and substantially increased susceptibility values. Linear regression analysis revealed a consistent linear relationship between R* and magnetic susceptibility, as well as iron concentration and magnetic susceptibility. The relaxation, fat, and susceptibility measurements remained stable across scan-rescan assessment and long-term follow-up.

DISCUSSION

We developed a versatile phantom to study fat-iron interactions in abdominal imaging, facilitating the optimization and comparison of susceptibility processing methods in future research.