Immune rejection after pancreatic islet cell transplantation: in vivo dual contrast-enhanced MR imaging in a mouse model

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.

Immunoregulatory Sertoli Cell Allografts Engineered to Express Human Insulin Survive Humoral-Mediated Rejection

An effective treatment and possible cure for type 1 diabetes is transplantation of pancreatic islets. Unfortunately, transplanted islets are rejected by the immune system with humoral-mediated responses being an important part of rejection. Sertoli cells (SC), an immune regulatory cell shown to survive as allografts long-term without immunosuppressants, have the potential to be used as a cell-based gene therapy vehicle to deliver endogenous insulin-a possible alternative to islets. Previously, we transduced a mouse SC line to produce human insulin. After transplantation into diabetic mice, these cells consistently produced low levels of insulin with graft survival of 75% at 50 days post-transplantation. The object of this study was to assess humoral immune regulation by these engineered SC. Both nontransduced and transduced SC survived exposure to human serum with complement in vitro. Analysis of allografts in vivo at 20 and 50 days post-transplantation revealed that despite IgG antibody detection, complement factor deposition was low and grafts survived through 50 days post-transplantation. Furthermore, the transduced SC secreted elevated levels of the complement inhibitor C1q binding protein. Overall, this suggests SC genetically engineered to express insulin maintain their ability to prevent complement-mediated killing. Since inhibiting complement-mediated rejection is important for graft survival, further studies of how SC modifies the immune response could be utilized to advance the use of genetically engineered SC or to prolong islet allograft survival to improve the treatment of diabetes.

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.

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.

Radiological Advances in Pancreatic Islet Transplantation

Type 1 diabetes mellitus (T1DM) is characterized by hyperglycemia, owing to the loss of pancreatic β cells in response to an autoimmune reaction leading to a state of absolute insulin deficiency. T1DM treatment is shifting from exogenous insulin replacement therapy toward pancreatic β-cell replacement, to restore physiologically responsive insulin secretion to variations in blood glucose levels. β-cell replacement strategies include human whole pancreas transplantation, islet transplantation with cell encapsulation and bioengineered pancreas. Interventional radiology and imaging modalities including positron emission tomography, single-photon emission computed tomography, magnetic resonance imaging, ultrasonography, and molecular imaging are imperative to enable successful β-cell replacement. Herein, the role of radiological modalities in the treatment of T1DM and its prospective use for noninvasive post-transplantation graft monitoring is discussed.

Polymeric Scaffolds for Pancreatic Tissue Engineering: A Review

In recent years, there has been an alarming increase in the incidence of diabetes, with one in every eleven individuals worldwide suffering from this debilitating disease. As the available treatment options fail to reduce disease progression, novel avenues such as the bioartificial pancreas are being given serious consideration. In the past decade, the research focus has shifted towards the field of tissue engineering, which helps to design biological substitutes for repair and replacement of non-functional or damaged organs. Scaffolds constitute an integral part of tissue engineering; they have been shown to mimic the native extracellular matrix, thereby supporting cell viability and proliferation. This review offers a novel compilation of the recent advances in polymeric scaffolds, which are used for pancreatic tissue engineering. Furthermore, in this article, the design strategies for bioartificial pancreatic constructs and their future applications in cell-based therapy are discussed.

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

Background

Islet transplantation (Tx) represents the most promising therapy to restore normoglycemia in type 1 diabetes (T1D) patients to date. As significant islet loss has been observed after the procedure, there is an urgent need for developing strategies for monitoring transplanted islet grafts. In this report we describe for the first time the application of magnetic particle imaging (MPI) for monitoring transplanted islets in the liver and under the kidney capsule in experimental animals.

Methods

Pancreatic islets isolated from Papio hamadryas were labeled with superparamagnetic iron oxides (SPIOs) and used for either islet phantoms or Tx in the liver or under the kidney capsule of NOD scid mice. MPI was used to image and quantify islet phantoms and islet transplanted experimental animals post-mortem at 1 and 14 days after Tx. Magnetic resonance imaging (MRI) was used to confirm the presence of labeled islets in the liver and under the kidney capsule 1 day after Tx.

Results

MPI of labeled islet phantoms confirmed linear correlation between the number of islets and the MPI signal (R²=0.988). Post-mortem MPI performed on day 1 after Tx showed high signal contrast in the liver and under the kidney capsule. Quantitation of the signal supports islet loss over time, which is normally observed 2 weeks after Tx. No MPI signal was observed in control animals. In vivo MRI confirmed the presence of labeled islets/islet clusters in liver parenchyma and under the kidney capsule one day after Tx.

Conclusions

Here we demonstrate that MPI can be used for quantitative detection of labeled pancreatic islets in the liver and under the kidney capsule of experimental animals. We believe that MPI, a modality with no depth attenuation and zero background tissue signal could be a suitable method for imaging transplanted islet grafts.

Synergistic effect of PEGylation and pentoxifylline addition on immunoprotection of pancreatic islets

In this study, a method is proposed to reduce immunological response of immune system against Langerhans islets by PEGylation of islets combined with adjuvant therapy. For this purpose, the best composition for a mixture of succinimidyl valeric acid activated mPEG (mPEG-SVA) with different molecular weights (MWs) and for a mixture of succinimidyl carbonate activated mPEG (mPEG-SC) with different MWs was determined separately. Then, the effect of pentoxifylline (PTX) as an adjuvant drug on immunological response against PEGylated islets at best mPEG composition was studied. The extent of mPEGs reaction, the amount of interlukin-2 (IL-2) and perforin secretion, and the viability of lymphocytes and islets in homo and co-cultures in the presence of PTX at different concentrations were considered for the in vitro evaluation of the proposed method. It was found, that a mixture of mPEG-SVA with MWs of 10 and 5 kDa at a composition of 75 and 25%, respectively, was the best formulation. Also, the addition of PTX drug to co-culture medium increased the protection of PEGylated islets against immune system and a concentration of 75 μg mL^-1 of PTX was suitable for islet protection with no adverse effect on immune cells.

Hypoxic Preconditioning Improves the Therapeutic Potential of Aging Bone Marrow Mesenchymal Stem Cells in Streptozotocin-Induced Type-1 Diabetic Mice

Insulin replacement is the current therapeutic option for type-1 diabetes. However, exogenous insulin cannot precisely represent the normal pattern of insulin secretion. Another therapeutic strategy is transplantation of pancreatic islets, but this is limited by immune rejection, intrinsic complications, and lack of donor availability. Stem cell therapy that results in the regeneration of insulin-producing cells represents an attractive choice. However, with advancing age, stem cells also undergo senescence, which leads to changes in the function of various cellular processes that result in a decrease in the regeneration potential of these aging stem cells. In this study, the effect of young and aging mesenchymal stem cells (MSCs) on the regeneration of pancreatic beta cells in streptozotocin (STZ)-induced type-1 diabetic mice was observed after hypoxic preconditioning. Hypoxia was chemically induced by 2, 4-dinitrophenol (DNP). Plasma insulin and glucose levels were measured at various time intervals, and pancreatic sections were analyzed histochemically. The effect of DNP was also analyzed on apoptosis of MSCs by flow cytometry and on gene expression of certain growth factors by quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). We observed that hypoxic preconditioning caused changes in the gene expression levels of growth factors in both young and aging MSCs. Young MSCs showed significant regeneration potential compared with the aging cells in vivo. However, hypoxic preconditioning was able to improve the regeneration potential of aging MSCs. It is concluded from the present study that the regeneration potential of aging MSCs into pancreatic β-cells can be enhanced by hypoxic preconditioning, which causes changes in the gene expression of certain growth factors.

Islet cell transplant: Update on current clinical trials

In the last 15 years clinical islet transplantation has made the leap from experimental procedure to standard of care for a highly selective group of patients. Due to a risk-benefit calculation involving the required systemic immunosuppression the procedure is only considered in patients with type 1 diabetes, complicated by severe hypoglycemia or end stage renal disease. In this review we summarize current outcomes of the procedure and take a look at ongoing and future improvements and refinements of beta cell therapy.

Noninvasive evaluation of the vascular response to transplantation of alginate encapsulated islets using the dorsal skin-fold model

Alginate encapsulation reduces the risk of transplant rejection by evading immune-mediated cell injury and rejection; however, poor vascular perfusion results in graft failure. Since existing imaging models are incapable of quantifying the vascular response to biomaterial implants after transplantation, in this study, we demonstrate the use of in vivo laser speckle imaging (LSI) and wide-field functional imaging (WiFI) to monitor the microvascular environment surrounding biomaterial implants. The vascular response to two islet-containing biomaterial encapsulation devices, alginate microcapsules and a high-guluronate alginate sheet, was studied and compared after implantation into the mouse dorsal window chamber (N = 4 per implant group). Images obtained over a 14-day period using LSI and WiFI were analyzed using algorithms to quantify blood flow, hemoglobin oxygen saturation and vascular density. Using our method, we were able to monitor the changes in the peri-implant microvasculature noninvasively without the use of fluorescent dyes. Significant changes in blood flow, hemoglobin oxygen saturation and vascular density were noted as early as the first week post-transplant. The dorsal window chamber model enables comparison of host responses to transplanted biomaterials. Future experiments will study the effect of changes in alginate composition on the vascular and immune responses.