Development and application of a new computational model of realistic noise related to AC Biosusceptometry

Abstract

Alternating Current Biosusceptometry (ACB) is a low-cost and portable biomagnetic technique that utilizes induction coils to magnetize magnetic tracers (MT) in biological environments. ACB has proven effective in evaluating physiological and pharmacotechnical parameters in various contexts, including in vitro, in vivo, and ex vivo assays. Recent studies have employed an inverse problem approach to enhance spatial resolution and obtain quantitative images, along with simulations of the ACB. Aiming to achieve sensitivity, realism, and precision in these simulations, it is essential to incorporate realistic noises based on the characteristics of the real ACB system. We developed new methodologies to incorporate realistic noise in Mono-channel ACB (MC-ACB) simulations, assessing their effect on spatial resolution, sensitivity, and quantitative reconstructions of MT spatial distribution. Results showed a partial agreement with experimental sensitivity values, but further improvements are necessary to address positional errors and achieve better agreement with experimental data. These findings highlight the ongoing requirement to enhance and refine the utilized models for increased precision and reliability in the results.