Characterization of noise and background signals in a magnetic particle imaging system

Abstract

Magnetic particle imaging (MPI) is a novel technology, which opens new possibilities for promising biomedical applications. MPI uses magnetic fields to generate a specific response from magnetic nanoparticles (MNPs), to determine their spatial location non-invasively and without using ionizing radiation. One open challenge of MPI is to achieve further improvements in terms of sensitivity to translate the currently preclinical performed research into clinical applications. In this work, we study the noise and background signals of our preclinical MPI system, to identify and characterize disturbing signal contributions. The current limit of detection achieved with our device was determined previously to be 20 ng of iron. Based on the results presented in this work, we describe possible hardware and software improvements and estimate that the limit of detection could be lowered to about 1–2 ng. Additionally, a long-term analysis of the scanner performance over the last 3 years is presented, which proved to be an easy and effective way to monitor possible changes or damage of hardware components. All the presented results were obtained by analysing empty scanner measurements and the presented methodology can easily be adapted for different scanner types, to compare their performances.

The Reconstruction of Magnetic Particle Imaging: Current Approaches Based on the System Matrix

“…Consistent with other imaging methods, the imaging quality of MPI is affected by background signals, which may originate from the thermal process of the scanner electronics, such as the amplifier, filter, coils, or the contamination of ferromagnetic tracers [ 67 , 68 ]. The standard measurement method of the background is measuring the SM and system response separately without the tracer, and then subtracting the background signal from the system response measured with the tracer.…”

Magnetic particle imaging: tracer development and the biomedical applications of a radiation-free, sensitive, and quantitative imaging modality

“…44,233 In terms of instrumentation, advancements in sensitivity have most frequently been from developments in coil design. 37,74,78,79,234,235 Regarding tracer development for enhanced sensitivity, the signal intensity is governed by the physical and inherent magnetic properties of the tracer, as with spatial resolution, but is mostly dependent on the Ms. 16,18,55 Although the detection sensitivity of MPI is strong currently, through significant advancement it has the potential to become comparable with that of exceptionally sensitive nuclear imaging techniques. 234 Given what has been discussed, the development of SPIONs with optimal sensitivity and spatial resolution performance has become a crucial part of MPI research.…”

“…[378][379][380] Despite these obstacles, there has been sustained work on the translation and hardware scale-up. 42,43,79,235,381,382 In the design of a functional MPI brain imager, Mason et al developed simulation studies that demonstrated promising capabilities for human-scale systems. 383 In an alternative approach Graeser et al successfully presented a human-sized MPI hardware set-up, tailored for brain applications, that has low technical requirements for fast and flexible operation in a clinical environment.…”

TranSMS: Transformers for Super-Resolution Calibration in Magnetic Particle Imaging

“…Noise in MPI systems originates from resistive components (thermal noise) and varies as a function of the sampled frequency component [34]. Thus, the additive noise in Eq.…”

“…Thus, the additive noise in Eq. ( 2) can be taken as colored Gaussian [34,35], where the standard deviation depends on the traversed trajectory and gradient strengths. It is common to pre-measure noise levels during background measurements, and perform noise whitening [33,[35][36][37].…”