Cell Density Quantification with TurboSPI: R2* Mapping with Compensation for Off-Resonance Fat Modulation

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