Analysis of noise sources in a human-scale fMPI imager

Abstract

High sensitivity is a key benefit of magnetic particle imaging (MPI) and drives many of its application, including functional neuroimaging (fMPI). Since the thermal noise levels expected from the preamplifier and coil resistance are quite low, it is crucial to identify, characterize and remove any sources of "noise" generated from system instabilities. These include fluctuations in the gain or production of genuine harmonics originating from the SPIONs as well as nuisance fluctuations of empty-bore signals at each harmonic frequency. While stable empty-bore harmonic signals can be calibrated and subtracted from the detected data, uncontrolled variance in their levels appears as "noise" and can ultimately limit the achievable signal-to-noise ratio (SNR) of the scanner. Here, we present a characterization of these noise source mechanisms in our human-scale field-free line (FFL) fMPI scanner. Currently, the shift amplifier, which is responsible for the translation of the FFL across the field of view (FOV), is the dominant source of noise. Eliminating the shift noise and improving the system’s stability would improve our sensitivity from our current detection limit of 150 ng to 15 ng of iron, a 10× improvement.