Development of Iron Oxide Nanochains as a Sensitive Magnetic Particle Imaging Tracer for Cancer Detection.

The advancement of imaging technologies plays a crucial role in improving the diagnosis and monitoring of diseases, including cancer. This study introduces a new design of iron oxide-based nanoparticles specifically developed for magnetic particle imaging (MPI), aimed at tracking and diagnosing breast cancer more effectively. By precisely controlling the size, shape, and magnetic properties of these nanoparticles, we enhance the responsiveness of MPI, resulting in an increased signal. In our research, we established a novel synthetic route for fabricating iron oxide nanochains (FeONCs) characterized by their uniform shape and size, which contribute to high magnetic properties suitable for MPI applications. Initial results indicate these FeONCs exhibit superior magnetic properties compared to conventional spherical superparamagnetic iron oxide nanoparticles, nanocubes, and reported nanoworm-type structures. Magnetic relaxometry studies revealed that FeONCs provide higher sensitivity than the commonly used VivoTrax Synomag D50 and D70 in MPI. Further, the size and shape of FeONCs significantly influence cellular uptake. In vivo experiments using orthotopic breast cancer mouse models allow us to assess the biocompatibility and magnetic characteristics of the nanoparticles, confirming their imaging efficacy. Furthermore, by conjugating these nanoparticles with the RGD peptide, we enhance their ability to specifically target breast cancer, establishing them as promising tracers for in vivo MPI applications characterized by high sensitivity. Thus, our findings highlight that FeONCs significantly improve imaging quality, facilitating the early detection and accurate monitoring of breast cancer. This paves the way for innovative diagnostic strategies and personalized treatment options. Future research will focus on fine-tuning the surface chemistry of these nanoparticles to further enhance the targeting efficiency and optimization of their practice in clinical applications, particularly for MPI-based hyperthermia therapy.