Strategies Towards Standardizing Calibration Methods for Magnetic Particle Imaging (MPI) Signal Quantification: Solution vs. Cellular Environments

Le résumé fourni par la source

Magnetic Particle Imaging (MPI) is a powerful technique for non-invasive imaging and iron quantification using superparamagnetic iron oxide nanoparticles (SPIONs), with applications ranging from in in vivo cell tracking to tracer distribution and biodistribution studies. As the MPI community continues to grow and diversify, there is an increasing recognition of the need for standardized approaches in signal quantification to ensure reproducibility, comparability, and reliable interpretation of results across studies. A key area where standardization is particularly needed is in the construction of calibration curves for quantitative MPI. Traditional MPI signal quantification methods typically rely on calibration curves constructed using SPIONs in solution, assuming that signal response remains consistent across environments. This overlooks key factors such as interparticle interactions and changes in the SPION magnetic behaviour that can occur in complex biological contexts, such as inside cells. In these environments, SPIONs may aggregate, experience restricted motion, or interact with intracellular structures, all of which can alter their MPI signal characteristic and affect quantification accuracy. In this study, we demonstrate that calibration curves derived from SPIONs in solution differ markedly from those obtained in cellular environments. We therefore propose calibrating MPI signal against the number of labelled cells, a strategy that accounts for altered SPION behaviours in the cellular environment and enables more accurate estimation of intracellular iron content. Another critical but often overlooked factor in MPI quantification is the influence of SPION concentration and their spatial distribution within the sample. We show that even modest variations in concentration can significantly affect MPI signal intensity challenging the commonly assumed linear relationship between signal and iron content. Our findings reveal that variations in concentration can introduce nonlinearities in signal response, thereby altering calibration curves and impacting the accuracy and reproducibility of MPI-based quantification. These observations highlight the importance of accounting for dilution effects, particularly when evaluating or comparing novel MPI tracers. By systematically examining the effects of environmental context and SPION concentration, our study provides a framework for biologically relevant MPI calibration strategies and supports the development of more standardized, reproducible quantification protocols.

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