Repeatability of Susceptibility Source Separation Methods in Human Brain: A Single-Site Study at 3 T

Susceptibility source separation offers new subvoxel insights into iron and myelin distribution in the human brain, overcoming a known limitation of conventional quantitative susceptibility mapping (QSM), which is sensitive only to the net effect of the iron and myelin mixture. Several algorithms have been developed to perform susceptibility separation; however, their repeatability has not been thoroughly evaluated. The repeatability of three R₂'-based algorithms (χ-Separation, χ-SepNet, and APART) was investigated using 3-T scan-rescan data from 21 healthy subjects. Repeatability was assessed using intraclass correlation coefficient (ICC) and repeatability coefficient (RC). Additionally, the average value of the generated maps was used to evaluate the contrast produced by different algorithms. Results showed that repeatability varied between methods and across regions, with better performance achieved by APART and χ-SepNet. The obtained paramagnetic (χ⁺) and diamagnetic (χ^-) maps had an overall moderate to good reliability, lower than that of conventional QSM primarily because of the lower reliability of the R₂' input. Region-wise, repeatability was lower in the frontal lobe and near air-tissue interfaces. The average RC for APART was 4 ppb, except for iron-rich regions on χ⁺ maps, where it was 7 ppb. For χ-SepNet, the average RC was 5 ppb and 10 ppb for χ⁺ in iron-rich regions. APART maps had the lowest average susceptibility values, but this was highly dependent on the method used to calculate the initial QSM input. In conclusion, susceptibility source separation showed moderate to good repeatability in most brain regions; however, results were greatly influenced by the algorithm used.