Multi-tracer Magnetic Particle Imaging (MMPI): Tracer Design and Multi-tracer Guided Image Reconstruction - PROJECT SUMMARY Multi-tracer medical imaging improves diagnostics by assessing multiple biological processes simultaneously, providing a more comprehensive view of diseases like cancer, neurological disorders, and cardiac conditions. While current magnetic particle imaging (MPI) offers excellent contrast and sensitivity, it is limited to single-tracer imaging, which can only assess one physiological process at a time. Multi-tracer MPI (MMPI) faces technical challenges due to the spectral overlapping of different tracers’ harmonics in the frequency domain (for system matrix-based image reconstruction method) and the indistinguishable point spread functions (PSF) of different tracers (for x-space image convolution method). The goal of our proposal is to achieve MMPI by using customized tracers and a spectral-separation algorithm for multi-channel, system matrix-based image reconstruction. The PI has demonstrated both theoretically and experimentally a colorization algorithm that separates spectral signals from different tracers using a magnetic particle spectroscopy (MPS) system. MPS is a 0D MPI system without selection or focus fields, creating a field- free region (FFR) to characterize tracers. With successful spectral-separation, tracer harmonics can be divided into separate channels, allowing the Kaczmarz algorithm to be applied for image reconstruction in each channel. Using tracers with distinct magnetic properties, reflected in the differing shapes/slopes of their magnetic hysteresis and Q-factors in the PSF, enhances spectral-separation accuracy and reduces channel leakage. Most magnetic nanoparticle (MNP) tracers on the market have iron oxide cores, leading to similar magnetic properties that cause significant channel leakage, and poor spectral-separation, thus, worsening MMPI performance. To address this, we will design and customize cost-effective, rare-earth element-free, biocompatible spinel ferrite MNP tracers with high magnetic moments. By doping divalent metals like Zn2+, Mn2+, and Mg2+ into Fe3O4, we can alter the cation distribution and overall magnetic moments. The tunable magnetic properties of spinel ferrites allow the creation of tracers with distinct magnetic hysteresis and PSF, which are expected to solve the MMPI challenges for both system matrix-based image reconstruction and x-space image convolution methods. Additionally, we will coat the tracers with red blood cell (RBC) membranes to further enhance biocompatibility and prolong blood circulation time for potential in vivo applications. For a preliminary demonstration of MMPI performance, we will 3D print magnetic phantoms containing multiple tracers (N = 1, 2, 3, and 4) with varying tracer amounts, line widths, and gaps along the x, y, and z axes. These phantoms are designed to assess spatial resolution in resolving multiple tracers in a single scan. The MMPI demonstration will take place at our collaborator’s lab at NIST. A key advantage of this MMPI approach is its compatibility with the existing MPI platform concerning signal collection and for each separated channel, the traditional Kaczmarz algorithm can still be used for image reconstruction.
