  Tracking the migration of superparamagnetic iron oxide (SPIO) labeled immune
cells in vivo is valuable for understanding the immunogenic response to cancer
and therapies. Quantitative cell tracking using compressed sensing
TurboSPI-based R2* mapping is a promising development to improve accuracy in
longitudinal studies on immune recruitment. The phase-encoded TurboSPI sequence
provides high fidelity relaxation data in the form of signal time-courses with
high temporal resolution. However, early in vivo applications of this method
revealed that simple mono-exponential R2* fitting performs poorly due to the
contaminant fat signal in voxels surrounding regions of interest, such as flank
tumors and lymph nodes adjacent to adipose tissue. This is especially
problematic if there is poor infiltration to the tumor such that immune cells
remain near the periphery. The presence of an off-resonance fat isochromat
results in modulations in the signal time-course can be erroneously fit as R2*
signal decay, thereby overestimating the density of SPIO labeled cells. Simply
excluding any voxel with fat-typical modulations results in underestimates in
voxels that have mixed content. We propose using a more comprehensive
dual-decay (R2f* and R2w*) Dixon-based signal model that accounts for the
potential presence of fat in a voxel to better estimate SPIO induced
de-phasing. In silico single voxel simulations illustrate how the proposed
signal model provides stable R2w* estimates that are invariant to fat content.
The proposed dual-decay model outperforms previous methods when applied to in
vitro samples of SPIO labeled cells and oil prepared with oil content >15%.
Preliminary in vivo results show that, compared to previous methods, the
dual-decay Dixon model improves the balance of R2* specificity versus
sensitivity, which in turn will result in more reliable analysis in future cell
tracking studies.
