Magnetic particle imaging of islet transplantation in the liver and under the kidney capsule in mouse models

Magnetic Particle Imaging Reveals that Iron-Labeled Extracellular Vesicles Accumulate in Brains of Mice with Metastases

The incidence of breast cancer remains high worldwide and is associated with a significant risk of metastasis to the brain that can be fatal; this is due, in part, to the inability of therapeutics to cross the blood-brain barrier (BBB). Extracellular vesicles (EVs) have been found to cross the BBB and further have been used to deliver drugs to tumors. EVs from different cell types appear to have different patterns of accumulation and retention as well as the efficiency of bioactive cargo delivery to recipient cells in the body. Engineering EVs as delivery tools to treat brain metastases, therefore, will require an understanding of the timing of EV accumulation and their localization relative to metastatic sites. Magnetic particle imaging (MPI) is a sensitive and quantitative imaging method that directly detects superparamagnetic iron. Here, we demonstrate MPI as a novel tool to characterize EV biodistribution in metastatic disease after labeling EVs with superparamagnetic iron oxide (SPIO) nanoparticles. Iron-labeled EVs (FeEVs) were collected from iron-labeled parental primary 4T1 tumor cells and brain-seeking 4T1BR5 cells, followed by injection into the mice with orthotopic tumors or brain metastases. MPI quantification revealed that FeEVs were retained for longer in orthotopic mammary carcinomas compared to SPIOs. MPI signal due to iron could only be detected in brains of mice bearing brain metastases after injection of FeEVs, but not SPIOs, or FeEVs when mice did not have brain metastases. These findings indicate the potential use of EVs as a therapeutic delivery tool in primary and metastatic tumors.

Magnetic Particle Imaging: From Tracer Design to Biomedical Applications in Vasculature Abnormality

Magnetic particle imaging (MPI) is an emerging non-invasive tomographic technique based on the response of magnetic nanoparticles (MNPs) to oscillating drive fields at the center of a static magnetic gradient. In contrast to magnetic resonance imaging (MRI), which is driven by uniform magnetic fields and projects the anatomic information of the subjects, MPI directly tracks and quantifies MNPs in vivo without background signals. Moreover, it does not require radioactive tracers and has no limitations on imaging depth. This article first introduces the basic principles of MPI and important features of MNPs for imaging sensitivity, spatial resolution, and targeted biodistribution. The latest research aiming to optimize the performance of MPI tracers is reviewed based on their material composition, physical properties, and surface modifications. While the unique advantages of MPI have led to a series of promising biomedical applications, recent development of MPI in investigating vascular abnormalities in cardiovascular and cerebrovascular systems, and cancer are also discussed. Finally, recent progress and challenges in the clinical translation of MPI are discussed to provide possible directions for future research and development.

Shape Anisotropy-Governed High-Performance Nanomagnetosol for In Vivo Magnetic Particle Imaging of Lungs

Caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease 2019 (COVID-19) has shown extensive lung manifestations in vulnerable individuals, putting lung imaging and monitoring at the forefront of early detection and treatment. Magnetic particle imaging (MPI) is an imaging modality, which can bring excellent contrast, sensitivity, and signal-to-noise ratios to lung imaging for the development of new theranostic approaches for respiratory diseases. Advances in MPI tracers would offer additional improvements and increase the potential for clinical translation of MPI. Here, a high-performance nanotracer based on shape anisotropy of magnetic nanoparticles is developed and its use in MPI imaging of the lung is demonstrated. Shape anisotropy proves to be a critical parameter for increasing signal intensity and resolution and exceeding those properties of conventional spherical nanoparticles. The 0D nanoparticles exhibit a 2-fold increase, while the 1D nanorods have a > 5-fold increase in signal intensity when compared to VivoTrax. Newly designed 1D nanorods displayed high signal intensities and excellent resolution in lung images. A spatiotemporal lung imaging study in mice revealed that this tracer offers new opportunities for monitoring disease and guiding intervention.

Inter-user Comparison for Quantification of Superparamagnetic Iron Oxides with Magnetic Particle Imaging Across Two Institutions Highlights a Need for Standardized Approaches

PURPOSE

Magnetic particle imaging (MPI) is being explored in biological contexts that require accurate and reproducible quantification of superparamagnetic iron oxide nanoparticles (SPIONs). While many groups have focused on improving imager and SPION design to improve resolution and sensitivity, a few have focused on improving quantification and reproducibility of MPI. The aim of this study was to compare MPI quantification results by two different systems and the accuracy of SPION quantification performed by multiple users at two institutions.

PROCEDURES

Six users (3 from each institute) imaged a known amount of Vivotrax + (10 μg Fe), diluted in a small (10 μL) or large (500 μL) volume. These samples were imaged with or without calibration standards in the field of view, to create a total of 72 images (6 users × triplicate samples × 2 sample volumes × 2 calibration methods). These images were analyzed by the respective user with two region of interest (ROI) selection methods. Image intensities, Vivotrax + quantification, and ROI selection were compared across users, within and across institutions.

RESULTS

MPI imagers at two different institutes produce significantly different signal intensities, that differ by over 3 times for the same concentration of Vivotrax + . Overall quantification yielded measurements that were within [Formula: see text] 20% from ground truth; however, SPION quantification values obtained at each laboratory were significantly different. Results suggest that the use of different imagers had a stronger influence on SPION quantification compared to differences arising from user error. Lastly, calibration conducted from samples in the imaging field of view gave the same quantification results as separately imaged samples.

CONCLUSIONS

This study highlights that there are many factors that contribute to the accuracy and reproducibility of MPI quantification, including variation between MPI imagers and users, despite pre-defined experimental setup, image acquisition parameters, and ROI selection analysis.

Inter-user comparison for quantification of superparamagnetic iron oxides with magnetic particle imaging across two institutions highlights a need for standardized approaches

Purpose

Magnetic particle imaging (MPI) is being explored in biological contexts that require accurate and reproducible quantification of superparamagnetic iron oxide nanoparticles (SPIONs). While many groups have focused on improving imager and SPION design to improve resolution and sensitivity, few have focused on improving quantification and reproducibility of MPI. The aim of this study was to compare MPI quantification results by two different systems and the accuracy of SPION quantification performed by multiple users at two institutions.

Procedures

Six users (3 from each institute) imaged a known amount of Vivotrax+ (10 μg Fe), diluted in a small (10 μL) or large (500 μL) volume. These samples were imaged with or without calibration standards in the field of view, to create a total of 72 images (6 users x triplicate samples x 2 sample volumes x 2 calibration methods). These images were analyzed by the respective user with two region of interest (ROI) selection methods. Image intensities, Vivotrax+ quantification, and ROI selection was compared across users, within and across institutions.

Results

MPI imagers at two different institutes produce significantly different signal intensities, that differ by over 3 times for the same concentration of Vivotrax+. Overall quantification yielded measurements that were within ± 20% from ground truth, however SPION quantification values obtained at each laboratory were significantly different. Results suggest that the use of different imagers had a stronger influence on SPION quantification compared to differences arising from user error. Lastly, calibration conducted from samples in the imaging field of view gave the same quantification results as separately imaged samples.

Conclusions

This study highlights that there are many factors that contribute to the accuracy and reproducibility of MPI quantification, including variation between MPI imagers and users, despite pre-defined experimental set up, image acquisition parameters, and ROI selection analysis.

Magnetic Particle Imaging in Vascular Imaging, Immunotherapy, Cell Tracking, and Noninvasive Diagnosis

Magnetic particle imaging (MPI) is a new tracer-based imaging modality that is useful in diagnosing various pathophysiology related to the vascular system and for sensitive tracking of cytotherapies. MPI uses nonradioactive and easily assimilated nanometer-sized iron oxide particles as tracers. MPI images the nonlinear Langevin behavior of the iron oxide particles and has allowed for the sensitive detection of iron oxide-labeled therapeutic cells in the body. This review will provide an overview of MPI technology, the tracer, and its use in vascular imaging and cytotherapies using molecular targets.

First Superferromagnetic Remanence Characterization and Scan Optimization for Super-Resolution Magnetic Particle Imaging

Magnetic particle imaging (MPI) is a sensitive, high-contrast tracer modality that images superparamagnetic iron oxide nanoparticles, enabling radiation-free theranostic imaging. MPI resolution is currently limited by scanner and particle constraints. Recent tracers have experimentally shown 10× resolution and signal improvements with dramatically sharper M-H curves. Experiments show a dependence on interparticle interactions, conforming to literature definitions of superferromagnetism. We thus call our tracers superferromagnetic iron oxide nanoparticles (SFMIOs). While SFMIOs provide excellent signal and resolution, they exhibit hysteresis with non-negligible remanence and coercivity. We provide the first quantitative measurements of SFMIO remanence decay and reformation using a novel multiecho pulse sequence. We characterize MPI scanning with remanence decay and coercivity and describe an SNR-optimized pulse sequence for SFMIOs under human electromagnetic safety limitations. The resolution from SFMIOs could enable clinical MPI with 10× reduced scanner selection fields, reducing hardware costs by up to 100×.

Magnetic Particle Imaging of Transplanted Human Islets Using a Machine Learning Algorithm

Human islet transplantation is a promising therapy to restore normoglycemia for type 1 diabetes (T1D). Despite recent advances, human islet transplantation remains suboptimal due to significant islet graft loss after transplantation. Various immunological and nonimmunological factors contribute to this loss therefore signifying a need for strategies and approaches for visualizing and monitoring transplanted human islet grafts. One such imaging approach is magnetic particle imaging (MPI), an emerging imaging modality that detects the magnetization of iron oxide nanoparticles. MPI is known for its specificity due to its high image contrast and sensitivity. MPI through its noninvasive nature provides the means for monitoring transplanted human islets in real time. Here we summarize an approach to track transplanted human islets using MPI. We label human islet from donors with dextran-coated ferucarbotran iron oxide nanoparticles, transplant the labeled human islet into under the left kidney capsule, and image graft cells using an MPI scanner. We engineer a K-means++, clustering-based unsupervised machine learning algorithm for standardized image segmentation and iron quantification of the MPI, which solves problems with selection bias and indiscriminate signal boundary that accompanies this newer imaging modality. In this chapter, we summarize the methods of this emerging imaging modality of MPI in conjunction with unsupervised machine learning to monitor and visualize islets after transplantation.

Nanotechnology in Kidney and Islet Transplantation: An Ongoing, Promising Field

Organ transplantation has evolved rapidly in recent years as a reliable option for patients with end-stage organ failure. However, organ shortage, surgical risks, acute and chronic rejection reactions and long-term immunosuppressive drug applications and their inevitable side effects remain extremely challenging problems. The application of nanotechnology in medicine has proven highly successful and has unique advantages for diagnosing and treating diseases compared to conventional methods. The combination of nanotechnology and transplantation brings a new direction of thinking to transplantation medicine. In this article, we provide an overview of the application and progress of nanotechnology in kidney and islet transplantation, including nanotechnology for renal pre-transplantation preservation, artificial biological islets, organ imaging and drug delivery.

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

Magnetic particle imaging (MPI) is an emerging tracer-based modality that enables real-time three-dimensional imaging of the non-linear magnetisation produced by superparamagnetic iron oxide nanoparticles (SPIONs), in the presence of an external oscillating magnetic field. As a technique, it produces highly sensitive radiation-free tomographic images with absolute quantitation. Coupled with a high contrast, as well as zero signal attenuation at-depth, there are essentially no limitations to where that can be imaged within the body. These characteristics enable various biomedical applications of clinical interest. In the opening sections of this review, the principles of image generation are introduced, along with a detailed comparison of the fundamental properties of this technique with other common imaging modalities. The main feature is a presentation on the up-to-date literature for the development of SPIONs tailored for improved imaging performance, and developments in the current and promising biomedical applications of this emerging technique, with a specific focus on theranostics, cell tracking and perfusion imaging. Finally, we will discuss recent progress in the clinical translation of MPI. As signal detection in MPI is almost entirely dependent on the properties of the SPION employed, this work emphasises the importance of tailoring the synthetic process to produce SPIONs demonstrating specific properties and how this impacts imaging in particular applications and MPI's overall performance.

Imaging in experimental models of diabetes

Translational medicine, experimental medicine and experimental animal models, in particular mice and rats, represent a multidisciplinary field that has made it possible to achieve, in the last decades, important scientific progress. In this review, we have summarized the most frequently used imaging animal models, such as ultrasound (US), micro-CT, MRI and the optical imaging methods, and their main implications in diagnostic and therapeutic fields, with a particular focus on diabetes mellitus, a multifactorial disease extremely widespread among the general population.

MRI monitoring of transplanted neonatal porcine islets labeled with polyvinylpyrrolidone-coated superparamagnetic iron oxide nanoparticles in a mouse model

Islet transplantation is a potential treatment option for certain patients with type 1 diabetes; however, it still faces barriers to widespread use, including the lack of tools to monitor islet grafts post-transplantation. This study investigates whether labeling neonatal porcine islets (NPI) with polyvinylpyrrolidone-coated superparamagnetic iron oxide nanoparticles (PVP-SPIO) affects their function, and whether this nanoparticle can be utilized to monitor NPI xenografts with magnetic resonance imaging (MRI) in a mouse model. In vitro, PVP-SPIO-labeled NPI in an agarose gel was visualized clearly by MRI. PVP-SPIO-labeled islets were then transplanted under the kidney capsules of immunodeficient nondiabetic and diabetic mice. All diabetic mice that received transplantation of PVP-SPIO-labeled islets reached normoglycemia. Grafts appeared as hypo-intense areas on MRI and were distinguishable from the surrounding tissues. Following injection of spleen cells from immunocompetent mice, normoglycemic recipient mice became diabetic and islet grafts showed an increase in volume, accompanied by a mixed signal on MRI. Overall, this study demonstrates that PVP-SPIO did not affect the function of NPI that PVP-SPIO-labeled islets were easily seen on MRI, and changes in MRI signals following rejection suggest a potential use of PVP-SPIO-labeled islets to monitor graft viability.

A method for the efficient iron-labeling of patient-derived xenograft cells and cellular imaging validation

There is momentum towards implementing patient-derived xenograft models (PDX) in cancer research to reflect the histopathology, tumor behavior, and metastatic properties observed in the original tumor. To study PDX cells preclinically, we used both bioluminescence imaging (BLI) to evaluate cell viability and magnetic particle imaging (MPI), an emerging imaging technology to allow for detection and quantification of iron nanoparticles. The goal of this study was to develop the first successful iron labeling method of breast cancer cells derived from patient brain metsastases and validate this method with imaging during tumor development. The overall workflow of this labeling method is as follows: adherent and non-adherent luciferase expressing human breast cancer PDX cells (F2-7) are dissociated and concurrently labeled after incubation with micron-sized iron oxide particles (MPIO; 25 μg Fe/ml), with labeling validated by cellular imaging with MPI and BLI. In this study, NOD/SCID/ILIIrg^-/- (n = 5) mice Received injections of 1 × 10⁶ iron-labeled F2-7 cells into the fourth mammary fat pad (MFP). BLI was performed longitudinally to day 49 and MPI was performed up to day 28. In vivo BLI revealed that signal increased over time with tumor development. MPI revealed decreasing signal in the tumors over time. Here, we demonstrate the first application of MPI to monitor the growth of a PDX MFP tumor and the first successful labeling of PDX cells with iron oxide particles. Imaging of PDX cells provides a powerful system to better develop personalized therapies targeting breast cancer brain metastasis.

Iron Oxide Nanoparticles in Regenerative Medicine and Tissue Engineering

In recent years, many promising nanotechnological approaches to biomedical research have been developed in order to increase implementation of regenerative medicine and tissue engineering in clinical practice. In the meantime, the use of nanomaterials for the regeneration of diseased or injured tissues is considered advantageous in most areas of medicine. In particular, for the treatment of cardiovascular, osteochondral and neurological defects, but also for the recovery of functions of other organs such as kidney, liver, pancreas, bladder, urethra and for wound healing, nanomaterials are increasingly being developed that serve as scaffolds, mimic the extracellular matrix and promote adhesion or differentiation of cells. This review focuses on the latest developments in regenerative medicine, in which iron oxide nanoparticles (IONPs) play a crucial role for tissue engineering and cell therapy. IONPs are not only enabling the use of non-invasive observation methods to monitor the therapy, but can also accelerate and enhance regeneration, either thanks to their inherent magnetic properties or by functionalization with bioactive or therapeutic compounds, such as drugs, enzymes and growth factors. In addition, the presence of magnetic fields can direct IONP-labeled cells specifically to the site of action or induce cell differentiation into a specific cell type through mechanotransduction.

3D in vivo Magnetic Particle Imaging of Human Stem Cell-Derived Islet Organoid Transplantation Using a Machine Learning Algorithm

Stem cell-derived islet organoids constitute a promising treatment of type 1 diabetes. A major hurdle in the field is the lack of appropriate in vivo method to determine graft outcome. Here, we investigate the feasibility of in vivo tracking of transplanted stem cell-derived islet organoids using magnetic particle imaging (MPI) in a mouse model. Human induced pluripotent stem cells-L1 were differentiated to islet organoids and labeled with superparamagnetic iron oxide nanoparticles. The phantoms comprising of different numbers of labeled islet organoids were imaged using an MPI system. Labeled islet organoids were transplanted into NOD/scid mice under the left kidney capsule and were then scanned using 3D MPI at 1, 7, and 28 days post transplantation. Quantitative assessment of the islet organoids was performed using the K-means++ algorithm analysis of 3D MPI. The left kidney was collected and processed for immunofluorescence staining of C-peptide and dextran. Islet organoids expressed islet cell markers including insulin and glucagon. Image analysis of labeled islet organoids phantoms revealed a direct linear correlation between the iron content and the number of islet organoids. The K-means++ algorithm showed that during the course of the study the signal from labeled islet organoids under the left kidney capsule decreased. Immunofluorescence staining of the kidney sections showed the presence of islet organoid grafts as confirmed by double staining for dextran and C-peptide. This study demonstrates that MPI with machine learning algorithm analysis can monitor islet organoids grafts labeled with super-paramagnetic iron oxide nanoparticles and provide quantitative information of their presence in vivo.

Magnetic microspheres can be used for magnetic particle imaging of cancer cells arrested in the mouse brain

PURPOSE

Magnetic particle imaging (MPI) is a new imaging modality that sensitively and specifically detects superparamagnetic iron oxide nanoparticles (SPIOs). MRI cell tracking with SPIOs has very high sensitivity, but low specificity and quantification is difficult. MPI could overcome these limitations. There are no reports of micron-sized iron oxide particles (MPIO) for cell tracking by MPI. Therefore, the goal was to evaluate if MPIO can be used for in vivo detection and quantification of cancer cells distributed in the mouse brain by MPI.

METHODS

In the first experiment mice were injected with either 2.5 × 10⁵ or 5.0 × 10⁵ MPIO-labeled cancer cells and MPI was performed ex vivo. In a second experiment, mice received either 2.5 × 10⁵ or 5.0 × 10⁴ MPIO-labeled cells and MPI was performed in vivo. In a third experiment, mice were injected with 5.0 × 10⁴ cells, labeled with either MPIO or ferucarbotran, and MPI was performed in vivo.

RESULTS

MPIO-labeled cells were visible in all MPI images of the mouse brain. The MPI signal and iron content measurements were greater for brains of mice that were injected with higher numbers of MPIO-labeled cells. Ferucarbotran-labeled cells were not detected in the brain by MPI.

CONCLUSION

This is the first example of the use of MPIO for cell tracking with MPI. With an intracardiac cell injection, ~15% of cells will arrest in the brain vasculature. For our lowest cell injection of 5.0 × 10⁴ cells, this was ~10 000 cells, distributed throughout the brain.

A concise review: the synergy between artificial intelligence and biomedical nanomaterials that empowers nanomedicine

Nanomedicine has recently experienced unprecedented growth and development. However, the complexity of operations at the nanoscale introduces a layer of difficulty in the clinical translation of nanodrugs and biomedical nanotechnology. This problem is further exacerbated when engineering and optimizing nanomaterials for biomedical purposes. To navigate this issue, artificial intelligence (AI) algorithms have been applied for data analysis and inference, allowing for a more applicable understanding of the complex interaction amongst the abundant variables in a system involving the synthesis or use of nanomedicine. Here, we report on the current relationship and implications of nanomedicine and AI. Particularly, we explore AI as a tool for enabling nanomedicine in the context of nanodrug screening and development, brain-machine interfaces and nanotoxicology. We also report on the current state and future direction of nanomedicine and AI in cancer, diabetes, and neurological disorder therapy.

Iron Oxide Nanoparticles as Theranostic Agents in Cancer Immunotherapy

Starting from the mid-1990s, several iron oxide nanoparticles (NPs) were developed as MRI contrast agents. Since their sizes fall in the tenths of a nanometer range, after i.v. injection these NPs are preferentially captured by the reticuloendothelial system of the liver. They have therefore been proposed as liver-specific contrast agents. Even though their unfavorable cost/benefit ratio has led to their withdrawal from the market, innovative applications have recently prompted a renewal of interest in these NPs. One important and innovative application is as diagnostic agents in cancer immunotherapy, thanks to their ability to track tumor-associated macrophages (TAMs) in vivo. It is worth noting that iron oxide NPs may also have a therapeutic role, given their ability to alter macrophage polarization. This review is devoted to the most recent advances in applications of iron oxide NPs in tumor diagnosis and therapy. The intrinsic therapeutic effect of these NPs on tumor growth, their capability to alter macrophage polarization and their diagnostic potential are examined. Innovative strategies for NP-based drug delivery in tumors (e.g., magnetic resonance targeting) will also be described. Finally, the review looks at their role as tracers for innovative, and very promising, imaging techniques (magnetic particle imaging-MPI).

Engineering of magnetic nanoparticles as magnetic particle imaging tracers

Magnetic particle imaging (MPI) has recently emerged as a promising non-invasive imaging technique because of its signal linearly propotional to the tracer mass, ability to generate positive contrast, low tissue background, unlimited tissue penetration depth, and lack of ionizing radiation. The sensitivity and resolution of MPI are highly dependent on the properties of magnetic nanoparticles (MNPs), and extensive research efforts have been focused on the design and synthesis of tracers. This review examines parameters that dictate the performance of MNPs, including size, shape, composition, surface property, crystallinity, the surrounding environment, and aggregation state to provide guidance for engineering MPI tracers with better performance. Finally, we discuss applications of MPI imaging and its challenges and perspectives in clinical translation.

Magnetic Particle Imaging: Current and Future Applications, Magnetic Nanoparticle Synthesis Methods and Safety Measures

Magnetic nanoparticles (MNPs) have a wide range of applications; an area of particular interest is magnetic particle imaging (MPI). MPI is an imaging modality that utilizes superparamagnetic iron oxide particles (SPIONs) as tracer particles to produce highly sensitive and specific images in a broad range of applications, including cardiovascular, neuroimaging, tumor imaging, magnetic hyperthermia and cellular tracking. While there are hurdles to overcome, including accessibility of products, and an understanding of safety and toxicity profiles, MPI has the potential to revolutionize research and clinical biomedical imaging. This review will explore a brief history of MPI, MNP synthesis methods, current and future applications, and safety concerns associated with this newly emerging imaging modality.

The impact of chemical engineering and technological advances on managing diabetes: present and future concepts

Monitoring blood glucose levels for diabetic patients is critical to achieve tight glycaemic control. As none of the current antidiabetic treatments restore lost functional β-cell mass in diabetic patients, insulin injections and the use of insulin pumps are most widely used in the management of glycaemia. The use of advanced and intelligent chemical engineering, together with the incorporation of micro- and nanotechnological-based processes have lately revolutionized diabetic management. The start of this concept goes back to 1974 with the description of an electrode that repeatedly measures the level of blood glucose and triggers insulin release from an infusion pump to enter the blood stream from a small reservoir upon need. Next to the insulin pumps, other drug delivery routes, including nasal, transdermal and buccal, are currently investigated. These processes necessitate competences from chemists, engineers-alike and innovative views of pharmacologists and diabetologists. Engineered micro and nanostructures hold a unique potential when it comes to drug delivery applications required for the treatment of diabetic patients. As the technical aspects of chemistry, biology and informatics on medicine are expanding fast, time has come to step back and to evaluate the impact of technology-driven chemistry on diabetics and how the bridges from research laboratories to market products are established. In this review, the large variety of therapeutic approaches proposed in the last five years for diabetic patients are discussed in an applied context. A survey of the state of the art of closed-loop insulin delivery strategies in response to blood glucose level fluctuation is provided together with insights into the emerging key technologies for diagnosis and drug development. Chemical engineering strategies centered on preserving and regenerating functional pancreatic β-cell mass are evoked in addition as they represent a permanent solution for diabetic patients.

Emerging Biomedical Applications Based on the Response of Magnetic Nanoparticles to Time-Varying Magnetic Fields

Magnetic nanoparticles are of interest for biomedical applications because of their biocompatibility, tunable surface chemistry, and actuation using applied magnetic fields. Magnetic nanoparticles respond to time-varying magnetic fields via physical particle rotation or internal dipole reorientation, which can result in signal generation or conversion of magnetic energy to heat. This dynamic magnetization response enables their use as tracers in magnetic particle imaging (MPI), an emerging biomedical imaging modality in which signal is quantitative of tracer mass and there is no tissue background signal or signal attenuation. Conversion of magnetic energy to heat motivates use in nanoscale thermal cancer therapy, magnetic actuation of drug release, and rapid rewarming of cryopreserved organs. This review introduces basic concepts of magnetic nanoparticle response to time-varying magnetic fields and presents recent advances in the field, with an emphasis on MPI and conversion of magnetic energy to heat.

Flow velocity quantification by exploiting the principles of the Doppler effect and magnetic particle imaging

Changes in blood flow velocity play a crucial role during pathogenesis and progression of cardiovascular diseases. Imaging techniques capable of assessing flow velocities are clinically applied but are often not accurate, quantitative, and reliable enough to assess fine changes indicating the early onset of diseases and their conversion into a symptomatic stage. Magnetic particle imaging (MPI) promises to overcome these limitations. Existing MPI-based techniques perform velocity estimation on the reconstructed images, which restricts the measurable velocity range. Therefore, we developed a novel velocity quantification method by adapting the Doppler principle to MPI. Our method exploits the velocity-dependent frequency shift caused by a tracer motion-induced modulation of the emitted signal. The fundamental theory of our method is deduced and validated by simulations and measurements of moving phantoms. Overall, our method enables robust velocity quantification within milliseconds, with high accuracy, no radiation risk, no depth-dependency, and extended range compared to existing MPI-based velocity quantification techniques, highlighting the potential of our method as future medical application.

Non-radioactive and sensitive tracking of neutrophils towards inflammation using antibody functionalized magnetic particle imaging tracers

White blood cells (WBCs) are a key component of the mammalian immune system and play an essential role in surveillance, defense, and adaptation against foreign pathogens. Apart from their roles in the active combat of infection and the development of adaptive immunity, immune cells are also involved in tumor development and metastasis. Antibody-based therapeutics have been developed to regulate (i.e. selectively activate or inhibit immune function) and harness immune cells to fight malignancy. Alternatively, non-invasive tracking of WBC distribution can diagnose inflammation, infection, fevers of unknown origin (FUOs), and cancer. Magnetic Particle Imaging (MPI) is a non-invasive, non-radioactive, and sensitive medical imaging technique that uses safe superparamagnetic iron oxide nanoparticles (SPIOs) as tracers. MPI has previously been shown to track therapeutic stem cells for over 87 days with a ~200 cell detection limit. In the current work, we utilized antibody-conjugated SPIOs specific to neutrophils for in situ labeling, and non-invasive and radiation-free tracking of these inflammatory cells to sites of infection and inflammation in an in vivo murine model of lipopolysaccharide-induced myositis. MPI showed sensitive detection of inflammation with a contrast-to-noise ratio of ~8-13.

Artificial Intelligence Analysis of Magnetic Particle Imaging for Islet Transplantation in a Mouse Model

PURPOSE

Current approaches to quantification of magnetic particle imaging (MPI) for cell-based therapy are thwarted by the lack of reliable, standardized methods of segmenting the signal from background in images. This calls for the development of artificial intelligence (AI) systems for MPI analysis.

PROCEDURES

We utilize a canonical algorithm in the domain of unsupervised machine learning, known as K-means++, to segment the regions of interest (ROI) of images and perform iron quantification analysis using a standard curve model. We generated in vitro, in vivo, and ex vivo data using islets and mouse models and applied the AI algorithm to gain insight into segmentation and iron prediction on these MPI data. In vitro models included imaging the VivoTrax-labeled islets in varying numbers. In vivo mouse models were generated through transplantation of increasing numbers of the labeled islets under the kidney capsule of mice. Ex vivo data were obtained from the MPI images of excised kidney grafts.

RESULTS

The K-means++ algorithms segmented the ROI of in vitro phantoms with minimal noise. A linear correlation between the islet numbers and the increasing prediction of total iron value (TIV) in the islets was observed. Segmentation results of the ROI of the in vivo MPI scans showed that with increasing number of transplanted islets, the signal intensity increased with linear trend. Upon segmenting the ROI of ex vivo data, a linear trend was observed in which increasing intensity of the ROI yielded increasing TIV of the islets. Through statistical evaluation of the algorithm performance via intraclass correlation coefficient validation, we observed excellent performance of K-means++-based model on segmentation and quantification analysis of MPI data.

CONCLUSIONS

We have demonstrated the ability of the K-means++-based model to provide a standardized method of segmentation and quantification of MPI scans in an islet transplantation mouse model.

In Vivo Imaging of Pancreatic Islet Grafts in Diabetes Treatment

Transplantation of pancreatic islets has potential to offer life-long blood glucose management in type I diabetes and severe type II diabetes without the need of exogenous insulin administration. However, islet cell therapy suffers from autoimmune and allogeneic rejection as well as non-immune related factors. Non-invasive techniques to monitor and evaluate the fate of cell implants in vivo are essential to understand the underlying causes of graft failure, and hence to improve the precision and efficacy of islet therapy. This review describes how imaging technology has been employed to interrogate the distribution, number or volume, viability, and function of islet implants in vivo. To date, fluorescence imaging, PET, SPECT, BLI, MRI, MPI, and ultrasonography are the many imaging modalities being developed to fulfill this endeavor. We outline here the advantages, limitations, and clinical utility of each particular imaging approach.

A Perspective on Cell Tracking with Magnetic Particle Imaging

Many labs have been developing cellular magnetic resonance imaging (MRI), using both superparamagnetic iron oxide nanoparticles (SPIONs) and fluorine-19 (19F)-based cell labels, to track immune and stem cells used for cellular therapies. Although SPION-based MRI cell tracking has very high sensitivity for cell detection, SPIONs are indirectly detected owing to relaxation effects on protons, producing negative magnetic resonance contrast with low signal specificity. Therefore, it is not possible to reliably quantify the local tissue concentration of SPION particles, and cell number cannot be determined. 19F-based cell tracking has high specificity for perfluorocarbon-labeled cells, and 19F signal is directly related to cell number. However, 19F MRI has low sensitivity. Magnetic particle imaging (MPI) is a new imaging modality that directly detects SPIONs. SPION-based cell tracking using MPI displays great potential for overcoming the challenges of MRI-based cell tracking, allowing for both high cellular sensitivity and specificity, and quantification of SPION-labeled cell number. Here we describe nanoparticle and MPI system factors that influence MPI sensitivity and resolution, quantification methods, and give our perspective on testing and applying MPI for cell tracking.

Beta Cell Imaging-From Pre-Clinical Validation to First in Man Testing

There are presently no reliable ways to quantify human pancreatic beta cell mass (BCM) in vivo, which prevents an accurate understanding of the progressive beta cell loss in diabetes or following islet transplantation. Furthermore, the lack of beta cell imaging hampers the evaluation of the impact of new drugs aiming to prevent beta cell loss or to restore BCM in diabetes. We presently discuss the potential value of BCM determination as a cornerstone for individualized therapies in diabetes, describe the presently available probes for human BCM evaluation, and discuss our approach for the discovery of novel beta cell biomarkers, based on the determination of specific splice variants present in human beta cells. This has already led to the identification of DPP6 and FXYD2ga as two promising targets for human BCM imaging, and is followed by a discussion of potential safety issues, the role for radiochemistry in the improvement of BCM imaging, and concludes with an overview of the different steps from pre-clinical validation to a first-in-man trial for novel tracers.

Current Progress and Perspective: Clinical Imaging of Islet Transplantation

Islet transplantation has great potential as a cure for type 1 diabetes. At present; the lack of a clinically validated non-invasive imaging method to track islet grafts limits the success of this treatment. Some major clinical imaging modalities and various molecular probes, which have been studied for non-invasive monitoring of transplanted islets, could potentially fulfill the goal of understanding pathophysiology of the functional status and viability of the islet grafts. In this current review, we summarize the recent clinical studies of a variety of imaging modalities and molecular probes for non-invasive imaging of transplanted beta cell mass. This review also includes discussions on in vivo detection of endogenous beta cell mass using clinical imaging modalities and various molecular probes, which will be useful for longitudinally detecting the status of islet transplantation in Type 1 diabetic patients. For the conclusion and perspectives, we highlight the applications of multimodality and novel imaging methods in islet transplantation.

Challenges in the development of nanoparticle-based imaging agents: Characterization and biology

Despite imaging agents being some of the earliest nanomedicines in clinical use, the vast majority of current research and translational activities in the nanomedicine field involves therapeutics, while imaging agents are severely underrepresented. The reasons for this lack of representation are several fold, including difficulties in synthesis and scale-up, biocompatibility issues, lack of suitable tissue/disease selective targeting ligands and receptors, and a high bar for regulatory approval. The recent focus on immunotherapies and personalized medicine, and development of nanoparticle constructs with better tissue distribution and selectivity, provide new opportunities for nanomedicine imaging agent development. This manuscript will provide an overview of trends in imaging nanomedicine characterization and biocompatibility, and new horizons for future development. This article is categorized under: Diagnostic Tools > in vivo Nanodiagnostics and Imaging Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials Toxicology and Regulatory Issues in Nanomedicine > Regulatory and Policy Issues in Nanomedicine.

Optimization of Drive Parameters for Resolution, Sensitivity and Safety in Magnetic Particle Imaging

Magnetic Particle Imaging is an emerging tracer imaging modality with zero background signal and zero ionizing radiation, high contrast and high sensitivity with quantitative images. While there is recent work showing that the low amplitude or low frequency drive parameters can improve MPI's spatial resolution by mitigating relaxation losses, the concomitant decrease of the MPI's tracer sensitivity due to the lower drive slew rates was not fully addressed. There has yet to be a wide parameter space, multi-objective optimization of MPI drive parameters for high resolution, high sensitivity and safety. In a large-scale study, we experimentally test 5 different nanoparticles ranging from multi to single-core across 18.5 nm to 32.1 nm core sizes and across an expansive drive parameter range of 0.4 - 416 kHz and 0.5 - 40 mT/ μ0 to assess spatial resolution, SNR, and safety. In addition, we analyze how drive-parameter-dependent shifts in harmonic signal energy away and towards the discarded first harmonic affect effective SNR in this optimization study. The results show that when optimizing for all four factors of resolution, SNR, discarded-harmonic-energy and safety, the overall trends are no longer monotonic and clear optimal points emerge. We present drive parameters different from conventional preclinical MPI showing ~ 2-fold improvement in spatial resolution while remaining within safety limits and addressing sensitivity by minimizing the typical SNR loss involved. Finally, validation of the optimization results with 2D images of phantoms was performed.

Using magnetic particle imaging systems to localize and guide magnetic hyperthermia treatment: tracers, hardware, and future medical applications

Magnetic fluid hyperthermia (MFH) treatment makes use of a suspension of superparamagnetic iron oxide nanoparticles, administered systemically or locally, in combination with an externally applied alternating magnetic field, to ablate target tissue by generating heat through a process called induction. The heat generated above the mammalian euthermic temperature of 37°C induces apoptotic cell death and/or enhances the susceptibility of the target tissue to other therapies such as radiation and chemotherapy. While most hyperthermia techniques currently in development are targeted towards cancer treatment, hyperthermia is also used to treat restenosis, to remove plaques, to ablate nerves and to alleviate pain by increasing regional blood flow. While RF hyperthermia can be directed invasively towards the site of treatment, non-invasive localization of heat through induction is challenging. In this review, we discuss recent progress in the field of RF magnetic fluid hyperthermia and introduce a new diagnostic imaging modality called magnetic particle imaging that allows for a focused theranostic approach encompassing treatment planning, treatment monitoring and spatially localized inductive heating.

Islet Transplantation Imaging in vivo

Although islet transplantation plays an effective and powerful role in the treatment of diabetes, a large amount of islet grafts are lost at an early stage due to instant blood-mediated inflammatory reactions, immune rejection, and β-cell toxicity resulting from immunosuppressive agents. Timely intervention based on the viability and function of the transplanted islets at an early stage is crucial. Various islet transplantation imaging techniques are available for monitoring the conditions of post-transplanted islets. Due to the development of various imaging modalities and the continuous study of contrast agents, non-invasive islet transplantation imaging in vivo has made great progress. The tracing and functional evaluation of transplanted islets in vivo have thus become possible. However, most studies on contrast agent and imaging modalities are limited to animal experiments, and long-term toxicity and stability need further evaluation. Accordingly, the clinical application of the current achievements still requires a large amount of effort. In this review, we discuss the contrast agents for MRI, SPECT/PET, BLI/FI, US, MPI, PAI, and multimodal imaging. We further summarize the advantages and limitations of various molecular imaging methods.

Nucleic acid-based theranostics in type 1 diabetes

Application of RNAi interference for type 1 diabetes (T1D) therapy bears tremendous potential. This review will discuss vehicles for oligonucleotide delivery, imaging modalities used for delivery monitoring, therapeutic targets, and different theranostic strategies that can be applied for T1D treatment.

Magnetic Particle Imaging: Current Applications in Biomedical Research

Magnetic particle imaging (MPI) is a new imaging modality with the potential for high-resolution imaging while retaining the noninvasive nature of other current modalities such as magnetic resonance imaging (MRI) and positron emission tomography (PET). It is able to track location and quantities of special superparamagnetic iron oxide nanoparticles without tracing any background signal. MPI utilizes the unique, intrinsic aspects of the nanoparticles: how they react in the presence of the magnetic field, and the subsequent turning off of the field. The current group of nanoparticles that are used in MPI are usually commercially available for MRI. Special MPI tracers are in development by many groups that utilize an iron-oxide core encompassed by various coatings. These tracers would solve the current obstacles by altering the size and material of the nanoparticles to what is required by MPI. In this review, the theory behind and the development of these tracers are discussed. In addition, applications such as cell tracking, oncology imaging, neuroimaging, and vascular imaging, among others, stemming from the implementation of MPI into the standard are discussed. Level of Evidence: 5 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2020;51:1659-1668.

Biodistribution of Glial Progenitors in a Three Dimensional-Printed Model of the Piglet Cerebral Ventricular System

White matter damage persists in hypoxic-ischemic newborns even when treated with hypothermia. We have previously shown that intraventricular delivery of human glial progenitors (GPs) at the neonatal stage is capable of replacing abnormal host glia and rescuing the lifespan of dysmyelinated mice. However, such transplantation in the human brain poses significant challenges as related to high-volume ventricles and long cell migration distances. These challenges can only be studied in large animal model systems. In this study, we developed a three dimensional (3D)-printed model of the ventricular system sized to a newborn pig to investigate the parameters that can maximize a global biodistribution of injected GPs within the ventricular system, while minimizing outflow to the subarachnoid space. Bioluminescent imaging and magnetic resonance imaging were used to image the biodistribution of luciferase-transduced GPs in simple fluid containers and a custom-designed, 3D-printed model of the piglet ventricular system. Seven independent variables were investigated. The results demonstrated that a low volume (0.1 mL) of cell suspension is essential to keep cells within the ventricular system. If higher volumes (1 mL) are needed, a very slow infusion speed (0.01 mL/min) is necessary. Real-time magnetic resonance imaging demonstrated that superparamagnetic iron oxide (SPIO) labeling significantly alters the rheological properties of the GP suspension, such that, even at high speeds and high volumes, the outflow to the subarachnoid space is reduced. Several other factors, including GP species (human vs. mouse), type of catheter tip (end hole vs. side hole), catheter length (0.3 vs. 7.62 m), and cell concentration, had less effect on the overall distribution of GPs. We conclude that the use of a 3D-printed phantom model represents a robust, reproducible, and cost-saving alternative to in vivo large animal studies for determining optimal injection parameters.

Superparamagnetic iron oxides as MPI tracers: A primer and review of early applications

Magnetic particle imaging (MPI) has recently emerged as a non-invasive, whole body imaging technique that detects superparamagnetic iron oxide (SPIO) nanoparticles similar as those used in magnetic resonance imaging (MRI). Based on tracer "hot spot" detection instead of providing contrast on MRI scans, MPI has already proven to be truly quantitative. Without the presence of endogenous background signal, MPI can also be used in certain tissues where the endogenous MRI signal is too low to provide contrast. After an introduction to the history and simplified principles of MPI, this review focuses on early MPI applications including MPI cell tracking, multiplexed MPI, perfusion and tumor MPI, lung MPI, functional MPI, and MPI-guided hyperthermia. While it is too early to tell if MPI will become a mainstay imaging technique with the (theoretical) sensitivity that it promises, and if it can successfully compete with SPIO-based ¹H MRI and perfluorocarbon-based ¹⁹F MRI, it provides unprecedented opportunities for exploring new nanoparticle-based imaging applications.

New Strategies and In Vivo Monitoring Methods for Stem Cell-Based Anticancer Therapies

Cancer is a devastating disease and the second cause of death in the developed world. Despite significant advances in recent years, such as the introduction of targeted therapies such as receptor tyrosine kinase inhibitors and immunotherapy, current approaches are insufficient to stop the advance of the disease and many cancer types remain largely intractable. In this review, we describe the latest and most revolutionary stem cell-based approaches for the treatment of cancer. We also summarize the emerging imaging modalities being applied for monitoring anticancer stem cell therapy success and discuss the implications of these novel technologies for precision medicine.

Magnetic particle imaging for radiation-free, sensitive and high-contrast vascular imaging and cell tracking

Magnetic particle imaging (MPI) is an emerging ionizing radiation-free biomedical tracer imaging technique that directly images the intense magnetization of superparamagnetic iron oxide nanoparticles (SPIOs). MPI offers ideal image contrast because MPI shows zero signal from background tissues. Moreover, there is zero attenuation of the signal with depth in tissue, allowing for imaging deep inside the body quantitatively at any location. Recent work has demonstrated the potential of MPI for robust, sensitive vascular imaging and cell tracking with high contrast and dose-limited sensitivity comparable to nuclear medicine. To foster future applications in MPI, this new biomedical imaging field is welcoming researchers with expertise in imaging physics, magnetic nanoparticle synthesis and functionalization, nanoscale physics, and small animal imaging applications.

A perspective on a rapid and radiation-free tracer imaging modality, magnetic particle imaging, with promise for clinical translation

Magnetic particle imaging (MPI), introduced at the beginning of the twenty-first century, is emerging as a promising diagnostic tool in addition to the current repertoire of medical imaging modalities. Using superparamagnetic iron oxide nanoparticles (SPIOs), that are available for clinical use, MPI produces high contrast and highly sensitive tomographic images with absolute quantitation, no tissue attenuation at-depth, and there are no view limitations. The MPI signal is governed by the Brownian and Néel relaxation behavior of the particles. The relaxation time constants of these particles can be utilized to map information relating to the local microenvironment, such as viscosity and temperature. Proof-of-concept pre-clinical studies have shown favourable applications of MPI for better understanding the pathophysiology associated with vascular defects, tracking cell-based therapies and nanotheranostics. Functional imaging techniques using MPI will be useful for studying the pathology related to viscosity changes such as in vascular plaques and in determining cell viability of superparamagnetic iron oxide nanoparticle labeled cells. In this review article, an overview of MPI is provided with discussions mainly focusing on MPI tracers, applications of translational capabilities ranging from diagnostics to theranostics and finally outline a promising path towards clinical translation.