Fifty-sixth annual meeting of the American association of physicists in medicine
TU-A-9A-08: Alternative Magnetic Particle Imaging Methods
Magnetic particle imaging (MPI) is being actively developed for applications where truly quantitative maps of the magnetic nanoparticle distribution are required. The applications include thermal therapies and cell tracking applications. Our Objectives: is to demonstrate the preliminary feasibility of alternative methods of imaging magnetic nanoparticles.
Current MPI methods use an alternating magnetic field (AMF) to induce a magnetization and a static field gradient to localize their position. The magnetization is in the same direction as the AMF so only the harmonics of the magnetization can be isolated from the AMF by recording the signal at the harmonic frequencies. We recently introduced a method of using a small static field to induce a component of the magnetization in the direction perpendicular to the AMF for spectroscopic sensing applications. The perpendicular magnetization is geometrically as well as spectrally isolated from the AMF. Here we used equilibrium, Langevin function simulations to show that the perpendicular magnetization can be used to image nanoparticles using two gradient geometries. Simulations used 100nm iron oxide nanoparticles and a 75mT gradient over the field of view.
The perpendicular magnetization is entirely in the even harmonics as opposed to the current MPI methods where the magnetization is entirely in the odd harmonics. Localization can be achieved with static gradient fields in either the direction perpendicular to the AMF or in the same direction as the AMF. Using a stepped field in combination with a 2mT sinusoidal field and perpendicular gradients, a condition number of 8 can be achieved. Using an 80mT sinusoidal field and in-line gradients, a condition number of 5 can be achieved with faster imaging.
The perpendicular magnetization at the even harmonics can be used to produce low noise images with reasonably conditioned reconstructions.