T1, T2 and T2* relaxations in MRI based on Gd5Si4 nanoparticles of varying sizes

Our previous study has shown that ferromagnetic gadolinium silicide (Gd5Si4) nanoparticles (NP) could be potentially efficient T2 CA for MRI with significantly reduced echo time (TE) compared to Superparamagnetic Iron Oxide Nanoparticles (SPION) [1]. T2 CA are defined by their relaxivity, r2, which is dependent on both the saturation magnetization (Ms) and size of the NPs [1,2,4]. In this study, effect of Gd5Si4 NPs of varying sizes and concentrations are investigated on T1, T2 and T2* (effective/observed T2) relaxations times. Gd5Si4 NPs categorized into three fractions (named S1, S2 and S3) based on average sizes of 586 nm, 287 nm and 135 nm respectively as analyzed from SEM images (Fig. 1). XRD analysis on the combined samples shows that Gd5Si4 is the major phase while GdSi and Gd5Si3 are present as the minor phases in all fractions (Fig. 1). Magnetic properties measured in VSM reveal that the Curie temperature (Tc) decreases for Gd5Si4 phase from 312 K for S1 to 304 K for S2 and is undetectable in S3. The M-H curves at 300 K exhibits ferromagnetic behavior descending to paramagnetic as we move from S1 to S3 fraction (Fig. 1). MR data were acquired on the 21.1 T (900 MHz) magnet. The results shown in Table 1 indicate that higher concentrations of NPs shorten the T2 and T2* relaxation times and the contrast disappears rapidly at higher dilutions. The S2 fraction at 1/20 dilution shows notably shortened T1 and T2 relaxation times compared to the other two fractions. Although S1 has higher Gd5Si4 phase volume fraction and larger average particle size compared to S2, further investigation is needed inorder to establish the reason for shortened relaxation times compared to the S1 fraction. Acknowledgements Work at the Ames Lab was supported by DOE (contract No. DE-AC02-07CH11358). Work at VCU was partially funded by NSF, Award No.: 1610967. Work performed at the NHMFL is supported by the State of Florida and the NSF (agreement No. DMR-1157490). This paper was presented at the ICM 2018, San Francisco.