International Journal on Magnetic Particle Imaging (IJMPI)
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Quantitative magnetic particle imaging monitors pulmonary vascular permeability in vivo
No full textIncreased pulmonary vascular permeability is a characteristic feature of acute lung injury and some chronic lung diseases. Currently there are no established methods to visualize pulmonary vascular permeability change in vivo in in both research and clinical settings. Terminal assays such as Evans Blue test, lung wet/dry ratio, and bronchoalveolar lavage fluid (BALF) total protein test lack the capability of monitoring the dynamics of vascular injury during disease progression. In this study, we used magnetic particle imaging (MPI)-CT dual-modality imaging combined with quantitative image analysis to noninvasively visualize and evaluate pulmonary vascular permeability in vivo in animal models. Oleic acid (OA) induced acute respiratory distress syndrome (ARDS) model was used for imaging. Based on the in vivo 3D MPI-CT images, we defined pulmonary SPIO extravasation index (SEI) to evaluate the vascular permeability. Significantly increased SEI was observed in the ARDS mice, which correlated well with ex vivo imaging findings. Moreover, quantitative imaging results were validated by ex vivo Evans Blue test, lung wet/dry ratio, BALF total protein concentration measurements and H&E histology. Our results suggest that 3D quantitative MPI-CT can be used to evaluate pulmonary vascular permeability, providing a noninvasive tool to monitor the dynamic change of pulmonary injury in vivo
Fast system matrix calibration for open-sided FFL-MPI based on rotation invariance of the system function
No full textIn recent years, the rapid development of magnetic particle imaging technology has provided a good imaging tool for many preclinical applications. Open-sided field free line magnetic particle imaging (FFL-MPI) is not only highly sensitive to magnetic nanoparticles (MNPs), but also suitable for applications such as interventional therapy. When the image is reconstructed based on the system matrix, the system matrices need to be measured at all angles by rotating FFL magnetic field (rFFL), which is complicated and time-consuming. In this paper, We find that the system function of open-sided FFL-MPI is rotation invariant. Then, a method for fast estimating the system matrices at other angles by rotating system function (rSF) at the initial angle is proposed. Finally, the simulation experiments show that the reconstructed results of rSF and rFFL are highly consistent under ideal fields, which proves that our research can greatly reduce the time required for system matrices calibration in open-sided FFL-MPI
A deep learning solution to improve the spatial resolution of magnetic particle imaging
No full textMagnetic particle imaging (MPI) is a rapidly evolving tomography modality. It has been proven to be potential in many biomedical fields for its high sensitivity and high image depth, but its spatial resolution is far from satisfactory. Deep learning may improve the spatial resolution of MPI, but it is limited by the need for large amount of training data. In order to conquer the above challenge, we propose a new deep learning solution to improve the spatial resolution of MPI in this work. The key of our method is to use a single system matrix to acquire the training data. which are further utilized to drive the deep learning model to improve the MPI spatial resolution. Firstly, some high-resolution (HR) images are used as the real magnetic particle distribution. Then, these HR images are downsampled to obtain the low-resolution (LR) particle distribution. To the end, the signal can be acquired by multiplying the LR particle distribution maps and LR system matrix. Hence, we can acquire the paired training data including the HR particle distribution maps and the signal data obtained with LR images. The results show that the data obtained through our proposed method can drive the deep learning model to achieve better performance in term of the spatial resolution than the bicubic interpolation
Study on duty ratio of handheld Magnetic Particle Imaging system
No full textThis paper investigates the effect of duty ratio on the background signal of handheld magnetic particle imaging (MPI) system. The background signal is the most influential noise signal in MPI system. Hand-held MPI systems need to be used continuously for long periods of time, so they are susceptible to interference from background signals. By adjusting the duty ratio and single detection time used by the system, a set of parameters with minimal background signal variation is determined. During the experiment, we summarized testing procedures to determine the most appropriate duty ratio for the MPI system, which can be tried on other MPI systems
VOMMPI - a tool for merging of MPI multi-patch data
No full textThe method of magnetic particle imaging (MPI) is substantially limited by a rather small field of view (FOV) even in preclinical imaging. To cover a bigger FOV, a multi-patch approach – i.e., scanning of a series of small FOVs (patches) shifted in the space - is necessary. Here, we present a simple software tool for merging of patches into a final 3D volume data of the scanned object. The software reads reconstructed data produced by a field-free point scanner (MPI 25/20FF, Bruker BioSpin MRI GmbH, Germany), merges them, averages data overlapped in the space, and export them in DICOM format. The software is free for non-commercial use
Multi-purpose deep learning framework for MPI based on contrastive learning
No full textDeep learning can be used in many tasks for MPI, prominently to reduce the calibration time of system matrix (SM)-based reconstruction by recovering undersampled SMs or directly reconstructing measurements without an SM. The success of supervised machine learning methods depends on the used training data, which should have high quality, match the distribution of the desired test cases and be cleanly labeled. For MPI, such data rarely exists. To find robust features in complex input data, the unsupervised method contrastive learning can be used. In this work, we show its applicability to MPI voltage signals and that the learned features improve the performance of tasks like SM recovery and direct reconstruction of real MPI data in 2D. SM recovery is performed by predicting voltage signals of samples placed in the MPI FOV, which could also provide an alternative to classic simulation frameworks that cannot match real MPI measurements
Projection X-space Image Reconstruction for Open-sided FFL Magnetic Particle Imaging
No full textMagnetic particle imaging is a novel tracer-based biomedical imaging modality with high sensitivity and linear quantitative properties. FFL-based magnetic particle imaging improves the sensitivity by an order of magnitude, but the quality of its tomographic images is susceptible to the reconstruction method. In this paper, we investigate the projection x-space reconstruction algorithm for an open-side field-free-line magnetic particle imaging device with partial field-of-view (pFOV), then reconstruct the projection data into tomographic images. In simulation study, we analyze the image in 1D to show the effect of fundamental frequency recovery and in 2D to evaluate the performance of the filtered back-projection algorithm. The overlapping portions of pFOV can be used to recover the offset constant, called the smoothness constraint. 1D profiles are superimposed by pFOVs after fundamental frequency recovery, and the overlapped parts were averaged. Different filters are used to process the image data in filtered back-projection. The results show that the effect of fundamental frequency recovery is significant. The filter in filtered back-projection works similarly to the effect of deconvolution in x-space, with Hann and Hamming filtering being the most effective and least noisy
Magnetic Particle Imaging for the Evaluation of Gastrointestinal Health by Measuring Gastrointestinal Permeability
No full textVarious diseases and immune-related issues have been associated with the gastrointestinal system’s health. Gastrointestinal permeability - a measure of transport across the GI tract’s cell lining from the lumen - is a functional parameter that is affected and is a viable factor in GI health assessment. Current diagnosis of GI-related disease involves the use of invasive exploratory surgery to minimally invasive colonoscopy. Magnetic particle imaging (MPI) is a non-radioactive and highly sensitive tracer imaging modality. The nanoparticle tracers used for MPI are FDA approved and can readily be translated into the clinic. In this research, we provide the first proof-of-concept using MPI to evaluate GI permeability in an in vitro model of the epithelial barrier lining of the GI tract
Single-sided magnetic particle imaging devices using ferrite core to improve penetration depth
No full textSingle-sided MPI devices provide an object unrestricted to the scanned area, but the inadequate penetration depth limits the application scenarios of single-sided MPI devices. In order to solve this problem, we propose adding a ferrite core to the coil to enhance the magnetic flux density. To improve the performance of the receiver coil, we use a spiral receiving coil to improve the sensitivity of the system. In addition, this work uses the Halbach array permanent magnets with adjustable magnetic block angle to generate a variable gradient magnetic field and move the FFP position. The single-sided MPI system we designed in this work is a portable device, which is expected to achieve more accurate detection of tumor location and minimal removal of normal cells during breast-conserving surgery. The feasibility of the device proposed in this work is verified through the analysis of simulation and measurement results
Temperature-Dependent Changes in Resolution and Coercivity of Superparamagnetic and Superferromagnetic Iron Oxide Nanoparticles
No full textMagnetic Particle Imaging (MPI) is a tracer-based imaging modality with immense promise as a radiation-free alternative to nuclear medicine imaging techniques. Nuclear medicine requires "hot chemistry" wherein radioactive tracers must be synthesized on-site, requiring expensive infrastructure and labor costs. MPI\u27s magnetic nanoparticles, superparamagnetic iron oxide nanoparticles (SPIOs), have no significant signal decay over time which removes cost barriers associated with nuclear medicine studies such as FDG-PET. While SPIOs are the current industry standard MPI tracer, recent developments in synthesizing superferromagnetic iron oxide nanoparticles (SFMIOs) and high resolution SPIOs (HR-SPIOs), a new class of nanoparticle with almost zero coercivity, have yielded a 30-fold improvement in resolution (0.4 mT) and SNR. To better understand the long-term performance of these new nanoparticles, this investigation reports changes in SPIO (VivoTrax Plus), HR-SPIO, and SFMIO resolution, along with SFMIO coercivity, at low temperatures (-2, 2 °C) and room temperature (18-22 °C) over 12 weeks. We find that changes in HR-SPIO resolution are more sensitive to storage temperature than SFMIOs. Additionally, we observe no appreciable difference in SFMIO coercivity between the two temperatures over time. These results can inform research on optimizing tracer synthesis while lending practical information to future hospitals about the highly accessible conditions for the transit and storage of tracers