Multiscale and multimodal imaging for three-dimensional vascular and histomorphological organ structure analysis of the pancreas.

Exocrine and endocrine pancreas are interconnected anatomically and functionally, with vasculature facilitating bidirectional communication. Our understanding of this network remains limited, largely due to two-dimensional histology and missing combination with three-dimensional imaging. In this study, a multiscale 3D-imaging process was used to analyze a porcine pancreas. Clinical computed tomography, digital volume tomography, micro-computed tomography and Synchrotron-based propagation-based imaging were applied consecutively. Fields of view correlated inversely with attainable resolution from a whole organism level down to capillary structures with a voxel edge length of 2.0 µm. Segmented vascular networks from 3D-imaging data were correlated with tissue sections stained by immunohistochemistry and revealed highly vascularized regions to be intra-islet capillaries of islets of Langerhans. Generated 3D-datasets allowed for three-dimensional qualitative and quantitative organ and vessel structure analysis. Beyond this study, the method shows potential for application across a wide range of patho-morphology analyses and might possibly provide microstructural blueprints for biotissue engineering.

Magnetic resonance imaging of pancreatic islets using tissue-adhesive particles containing iron oxide nanoparticles.

Post-transplantation tracking of pancreatic islets is a prerequisite for advancing cell therapy to treat type 1 diabetes. Magnetic resonance imaging (MRI) has emerged as a safe and non-invasive technique for visualizing cells in clinical applications. In this study, we proposed a novel MRI contrast agent formulation by encapsulating iron oxide nanoparticles (IONPs) in poly(lactic-co-glycolic acid) (PLGA) particles functionalized with a tissue adhesive polydopamine (PD) layer (IONP-PLGA-PD MS). Intriguingly, our particles facilitated efficient and robust labeling through a one-step process, allowing for the incorporation of a substantial amount of IONPs without detrimental impacts on the viability and functionality of pancreatic islets. The MRI signals emanating from islets labeled using our particles were found to be stable over 30 days in vitro and 60 days when transplanted under kidney capsules of diabetic mice. These results suggest that our approach provides a potential platform for monitoring the fate of pancreatic islets after transplantation.

Pancreatic Islet Viability Assessment Using Hyperspectral Imaging of Autofluorescence.

Islets prepared for transplantation into type 1 diabetes patients are exposed to compromising intrinsic and extrinsic factors that contribute to early graft failure, necessitating repeated islet infusions for clinical insulin independence. A lack of reliable pre-transplant measures to determine islet viability severely limits the success of islet transplantation and will limit future beta cell replacement strategies. We applied hyperspectral fluorescent microscopy to determine whether we could non-invasively detect islet damage induced by oxidative stress, hypoxia, cytokine injury, and warm ischaemia, and so predict transplant outcomes in a mouse model. In assessing islet spectral signals for NAD(P)H, flavins, collagen-I, and cytochrome-C in intact islets, we distinguished islets compromised by oxidative stress (ROS) (AUC = 1.00), hypoxia (AUC = 0.69), cytokine exposure (AUC = 0.94), and warm ischaemia (AUC = 0.94) compared to islets harvested from pristine anaesthetised heart-beating mouse donors. Significantly, with unsupervised assessment we defined an autofluorescent score for ischaemic islets that accurately predicted the restoration of glucose control in diabetic recipients following transplantation. Similar results were obtained for islet single cell suspensions, suggesting translational utility in the context of emerging beta cell replacement strategies. These data show that the pre-transplant hyperspectral imaging of islet autofluorescence has promise for predicting islet viability and transplant success.

Acid-Resistant BODIPY Amino Acids for Peptide-Based Fluorescence Imaging of GPR54 Receptors in Pancreatic Islets.

The G protein-coupled kisspeptin receptor (GPR54 or KISS1R) is an important mediator in reproduction, metabolism and cancer biology; however, there are limited fluorescent probes or antibodies for direct imaging of these receptors in cells and intact tissues, which can help to interrogate their multiple biological roles. Herein, we describe the rational design and characterization of a new acid-resistant BODIPY-based amino acid (Trp-BODIPY PLUS), and its implementation for solid-phase synthesis of fluorescent bioactive peptides. Trp-BODIPY PLUS retains the binding capabilities of both short linear and cyclic peptides and displays notable turn-on fluorescence emission upon target binding for wash-free imaging. Finally, we employed Trp-BODIPY PLUS to prepare some of the first fluorogenic kisspeptin-based probes and visualized the expression and localization of GPR54 receptors in human cells and in whole mouse pancreatic islets by fluorescence imaging.

3D Optical Molecular Imaging of the Rodent Pancreas by OPT and LSFM.

The rodent pancreas is the prevalent model system for preclinical diabetes research. However, due to the compound endocrine-exocrine organization of the gland, with the endocrine islets of Langerhans scattered by the thousands throughout the much greater exocrine parenchyma, stereological assessments of endocrine cell mass, commonly insulin-producing ß-cells, are exceedingly challenging. In recent years, optical mesoscopic imaging techniques such as optical projection tomography (OPT) and light sheet fluorescence microscopy (LSFM) have seen dramatic developments, enabling 3D visualization of fluorescently labeled cells in mm- to cm-sized tissues with µm resolution. Here we present a protocol for 3D visualization and "absolute" quantitative assessments of, for example, islet mass throughout the volume of rodent pancreata with maintained spatial context.

In Vivo Imaging of Naked and Microencapsulated Islet Cell Transplantation.

We describe step-by-step methods to label human pancreatic islet cells and murine insulinoma cells and their subsequent transplantation into type I diabetic mouse models with a focus on in vivo imaging using clinically applicable scanners. We also cover islets that are microencapsulated within alginate hydrogels loaded with imaging agents. By following these methods, it is possible to image cell grafts using T1-weighted and T2/T2*-weighted 1H magnetic resonance imaging (MRI), 19F MRI, computed tomography, ultrasound imaging, and bioluminescence imaging in vivo. Considering a myriad of factors that may affect the outcome of proper in vivo detection, we discuss potential issues that may be encountered during and after the process of labeling. The ultimate goal is to use these in vivo imaging approaches to determine and optimize naked and encapsulated islet cell survival, therapeutic function, and engraftment procedures.

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.

Predicting endocrine function after total pancreatectomy and islet cell autotransplantation: A novel approach utilizing computed tomography texture analysis.

BACKGROUND: Islet cell autotransplantation is an effective method to prevent morbidity associated with type IIIc diabetes after total pancreatectomy. However, there is no valid method to predict long-term endocrine function. Our aim was to assess computed tomography texture analysis as a strategy to predict long-term endocrine function after total pancreatectomy and islet cell autotransplantation. METHODS: All patients undergoing total pancreatectomy and islet cell autotransplantation from 2007 to 2020 who had high-quality preoperative computed tomography imaging available for texture analysis were included. The primary outcome was optimal long-term endocrine function, defined as stable glycemic control with <10 units of insulin/day. RESULTS: Sixty-three patients met inclusion criteria. Median yield was 6,111 islet equivalent/kg body weight. At a median follow-up of 64.2 months, 12.7% (n = 8) of patients were insulin independent and 39.7% (n = 25) demonstrated optimal endocrine function. Neither total islet equivalent nor islet equivalent/kg body weight alone were associated with optimal endocrine function. To improve endocrine function prediction, computed tomography texture analysis parameters were analyzed, identifying an association between kurtosis (odds ratio, 2.32; 95% confidence interval, 1.08-4.80; P = .02) and optimal endocrine function. Sensitivity analysis discovered a cutoff for kurtosis = 0.60, with optimal endocrine function seen in 66.7% with kurtosis ≥0.60, compared with only 26.2% with kurtosis <0.60 (P < .01). On multivariate logistic regression including islet equivalent yield, only kurtosis ≥0.60 (odds ratio, 5.61; 95% confidence interval, 1.56-20.19; P = .01) and fewer small islet equivalent (odds ratio, 1.00; 95% confidence interval, 1.00-1.00; P = .02) were associated with optimal endocrine function, with the whole model demonstrating excellent prediction of long-term endocrine function (area under the curve, 0.775). CONCLUSION: Computed tomography texture analysis can provide qualitative data, that when used in combination with quantitative islet equivalent yield, can accurately predict long-term endocrine function after total pancreatectomy and islet cell autotransplantation.

Fluorescence imaging of beta cell primary cilia.

Primary cilia are slender cell-surface organelles that project into the intercellular space. In pancreatic beta cells, primary cilia coordinate a variety of cell responses including GPCR signaling, calcium influx, and insulin secretion, along with likely many underappreciated roles in islet development and differentiation. To study cilia function in islet biology, direct visualization of primary cilia by microscopic methods is often a necessary first step. Ciliary abundance, distribution, and morphology are heterogeneous among islet cells and are best visualized by fluorescence microscopy, the tools for which are readily accessible to most researchers. Here we present a collection of fluorescence imaging methods that we have adopted and optimized for the observation of primary cilia in mouse and human islets. These include conventional confocal microscopy using fixed islets and pancreas sections, live-cell imaging with cilia-targeted biosensors and probes, cilia motion recordings, and quantitative analysis of primary cilia waveform in the ex vivo environment. We discuss practical considerations and limitations of our approaches as well as new tools on the horizon to facilitate the observation of primary cilia in pancreatic islets.

Mouse models and human islet transplantation sites for intravital imaging.

Human islet transplantations into rodent models are an essential tool to aid in the development and testing of islet and cellular-based therapies for diabetes prevention and treatment. Through the ability to evaluate human islets in an in vivo setting, these studies allow for experimental approaches to answer questions surrounding normal and disease pathophysiology that cannot be answered using other in vitro and in vivo techniques alone. Intravital microscopy enables imaging of tissues in living organisms with dynamic temporal resolution and can be employed to measure biological processes in transplanted human islets revealing how experimental variables can influence engraftment, and transplant survival and function. A key consideration in experimental design for transplant imaging is the surgical placement site, which is guided by the presence of vasculature to aid in functional engraftment of the islets and promote their survival. Here, we review transplantation sites and mouse models used to study beta cell biology in vivo using intravital microscopy and we highlight fundamental observations made possible using this methodology.

Critical Considerations in Bioluminescence Imaging of Transplanted Islets: Dynamic Signal Change in Early Posttransplant Phase and Signal Absorption by Tissues.

OBJECTIVES: In pancreatic islet transplantation studies, bioluminescence imaging enables quantitative and noninvasive tracking of graft survival. Amid the recent heightened interest in extrahepatic sites for islet and stem cell-derived beta-like cell transplantations, proper understanding the nature of bioluminescence imaging in these sites is important. METHODS: Islets isolated from Firefly rats ubiquitously expressing luciferase reporter gene in Lewis rats were transplanted into subcutaneous or kidney capsule sites of wild-type Lewis rats or immunodeficient mice. Posttransplant changes of bioluminescence signal curves and absorption of bioluminescence signal in transplantation sites were examined. RESULTS: The bioluminescence signal curve dynamically changed in the early posttransplantation phase; the signal was low within the first 5 days after transplantation. A substantial amount of bioluminescence signal was absorbed by tissues surrounding islet grafts, correlating to the depth of the transplanted site from the skin surface. Grafts in kidney capsules were harder to image than those in the subcutaneous site. Within the kidney capsule, locations that minimized depth from the skin surface improved the graft detectability. CONCLUSIONS: Posttransplant phase and graft location/depth critically impact the bioluminescence images captured in islet transplantation studies. Understanding these parameters is critical for reducing experimental biases and proper interpretation of data.

Poly(4-Styrenesulfonic Acid-co-maleic Anhydride)-Coated NaGdF4:Yb,Tb,Nd Nanoparticles with Luminescence and Magnetic Properties for Imaging of Pancreatic Islets and ß-Cells.

Novel Yb,Tb,Nd-doped GdF3 and NaGdF4 nanoparticles were synthesized by a coprecipitation method in ethylene glycol (EG) in the presence of the poly(4-styrenesulfonic acid-co-maleic anhydride) stabilizer. The particle size and morphology, crystal structure, and phase change were controlled by adjusting the PSSMA concentration and source of fluoride anions in the reaction. Doping of Yb3+, Tb3+, and Nd3+ ions in the NaGdF4 host nanoparticles induced luminescence under ultraviolet and near-infrared excitation and high relaxivity in magnetic resonance (MR) imaging (MRI). In vitro toxicity of the nanoparticles and their cellular uptake efficiency were determined in model rat pancreatic ß-cells (INS-1E). As the NaGdF4:Yb,Tb,Nd@PSSMA-EG nanoparticles were non-toxic and possessed good luminescence and magnetic properties, they were applicable for in vitro optical and MRI of isolated pancreatic islets in phantoms. The superior contrast was achieved for in vivo T2*-weighted MR images of the islets transplanted under the kidney capsule to mice in preclinical trials.

Ultrasound Imaging of Pancreatic Perfusion Dynamics Predicts Therapeutic Prevention of Diabetes in Preclinical Models of Type 1 Diabetes.

In type 1 diabetes (T1D), immune-cell infiltration into islets of Langerhans (insulitis) and ß-cell decline occur years before diabetes presents. There is a lack of validated clinical approaches for detecting insulitis and ß-cell decline, to diagnose eventual diabetes and monitor the efficacy of therapeutic interventions. We previously determined that contrast-enhanced ultrasound measurements of pancreas perfusion dynamics predict disease progression in T1D pre-clinical models. Here, we test whether these measurements predict therapeutic prevention of T1D. We performed destruction-reperfusion measurements with size-isolated microbubbles in non-obese diabetic (NOD)-severe combined immunodeficiency (SCID) mice receiving an adoptive transfer of diabetogenic splenocytes. Mice received vehicle control or the following treatments: (i) anti-CD3 to block T-cell activation; (ii) anti-CD4 to deplete CD4+ T cells; (iii) verapamil to reduce ß-cell apoptosis; or (iv) tauroursodeoxycholic acid (TUDCA) to reduce ß-cell endoplasmic reticulum stress. We compared measurements of pancreas perfusion dynamics with subsequent progression to diabetes. Anti-CD3, anti-CD4, and verapamil delayed diabetes development. Blood flow dynamics was significantly altered in treated mice with delayed/absent diabetes development compared with untreated mice. Conversely, blood flow dynamics in treated mice with unchanged diabetes development was similar to that in untreated mice. Thus, measurement of pancreas perfusion dynamics predicts the successful prevention of diabetes. This strategy may provide a clinically deployable predictive marker for therapeutic prevention in asymptomatic T1D.

Potential of [11C]UCB-J as a PET tracer for islets of Langerhans.

Biomarkers for the measurement of islets of Langerhans could help elucidate the etiology of diabetes. Synaptic vesicle glycoprotein 2 A (SV2A) is a potential marker reported to be localized in the endocrine pancreas. [11C]UCB-J is a novel positron emission tomography (PET) radiotracer that binds to SV2A and was previously evaluated as a synaptic marker in the central nervous system. Here, we evaluated whether [11C]UCB-J could be utilized as a PET tracer for the islets of Langerhans in the pancreas by targeting SV2A. The mRNA transcription of SV2A was evaluated in human isolated islets of Langerhans and exocrine tissue. In vitro autoradiography was performed on pancreas and brain sections from rats and pigs, and consecutive sections were immunostained for insulin. Sprague-Dawley rats were examined with PET-MRI and ex vivo autoradiography at baseline and with administration of levetiracetam (LEV). Similarly, pigs were examined with dynamic PET-CT over the pancreas and brain after administration of [11C]UCB-J at baseline and after pretreatment with LEV. In vivo radioligand binding was assessed using a one-compartment tissue model. The mRNA expression of SV2A was nearly 7 times higher in endocrine tissue than in exocrine tissue (p < 0.01). In vitro autoradiography displayed focal binding of [11C]UCB-J in the pancreas of rats and pigs, but the binding pattern did not overlap with the insulin-positive areas or with ex vivo autoradiography. In rats, pancreas binding was higher than that in negative control tissues but could not be blocked by LEV. In pigs, the pancreas and brain exhibited accumulation of [11C]UCB-J above the negative control tissue spleen. While brain binding could be blocked by pretreatment with LEV, a similar effect was not observed in the pancreas. Transcription data indicate SV2A to be a valid target for imaging islets of Langerhans, but [11C]UCB-J does not appear to have sufficient sensitivity for this application.

Protocol for in vivo and ex vivo assessments of glucose-stimulated insulin secretion in mouse islet ß cells.

Pancreatic islet ß cells secrete insulin in a biphasic manner when sensing high blood glucose level. This protocol describes the evaluation of different phases of insulin secretion, as well as basal, glucose-stimulated and total insulin secretion abilities, thereby enabling precise assessment of ß cell function both in vivo and ex vivo. The in vivo assay consists of intravenous tube imbedding surgery and hyperglycemic clamp. The ex vivo assay consists of islet isolation, dynamic perfusion and static immersion. For complete details on the use and execution of this protocol, please refer to Sun et al. (2021).

Pancreas Optical Clearing and 3-D Microscopy in Health and Diabetes.

Although first described over a hundred years ago, tissue optical clearing is undergoing renewed interest due to numerous advances in optical clearing methods, microscopy systems, and three-dimensional (3-D) image analysis programs. These advances are advantageous for intact mouse tissues or pieces of human tissues because samples sized several millimeters can be studied. Optical clearing methods are particularly useful for studies of the neuroanatomy of the central and peripheral nervous systems and tissue vasculature or lymphatic system. Using examples from solvent- and aqueous-based optical clearing methods, the mouse and human pancreatic structures and networks will be reviewed in 3-D for neuro-insular complexes, parasympathetic ganglia, and adipocyte infiltration as well as lymphatics in diabetes. Optical clearing with multiplex immunofluorescence microscopy provides new opportunities to examine the role of the nervous and circulatory systems in pancreatic and islet functions by defining their neurovascular anatomy in health and diabetes.

In Vivo ZIMIR Imaging of Mouse Pancreatic Islet Cells Shows Oscillatory Insulin Secretion.

Appropriate insulin secretion is essential for maintaining euglycemia, and impairment or loss of insulin release represents a causal event leading to diabetes. There have been extensive efforts of studying insulin secretion and its regulation using a variety of biological preparations, yet it remains challenging to monitor the dynamics of insulin secretion at the cellular level in the intact pancreas of living animals, where islet cells are supplied with physiological blood circulation and oxygenation, nerve innervation, and tissue support of surrounding exocrine cells. Herein we presented our pilot efforts of ZIMIR imaging in pancreatic islet cells in a living mouse. The imaging tracked insulin/Zn2+ release of individual islet ß-cells in the intact pancreas with high spatiotemporal resolution, revealing a rhythmic secretion activity that appeared to be synchronized among islet ß-cells. To facilitate probe delivery to islet cells, we also developed a chemogenetic approach by expressing the HaloTag protein on the cell surface. Finally, we demonstrated the application of a fluorescent granule zinc indicator, ZIGIR, as a selective and efficient islet cell marker in living animals through systemic delivery. We expect future optimization and integration of these approaches would enable longitudinal tracking of beta cell mass and function in vivo by optical imaging.

Pancreatic ß-cell heterogeneity in health and diabetes: classes, sources, and subtypes.

Pancreatic ß-cells perform glucose-stimulated insulin secretion, a process at the center of type 2 diabetes etiology. Efforts to understand how ß-cells behave in healthy and stressful conditions have revealed a wide degree of morphological, functional, and transcriptional heterogeneity. Sources of heterogeneity include ß-cell topography, developmental origin, maturation state, and stress response. Advances in sequencing and imaging technologies have led to the identification of ß-cell subtypes, which play distinct roles in the islet niche. This review examines ß-cell heterogeneity from morphological, functional, and transcriptional perspectives, and considers the relevance of topography, maturation, development, and stress response. It also discusses how these factors have been used to identify ß-cell subtypes, and how heterogeneity is impacted by diabetes. We examine open questions in the field and discuss recent technological innovations that could advance understanding of ß-cell heterogeneity in health and disease.

Bioluminescence Imaging In Vivo Confirms the Viability of Pancreatic Islets Transplanted into the Greater Omentum.

PURPOSE: The liver is the most widely used site for pancreatic islet transplantation. However, several site-specific limitations impair functional success, with instant blood-mediated inflammatory reaction being the most important. The aim of this study was to develop a preclinical model for placement of the islet graft into a highly vascularized omental flap using a fibrin gel. For this purpose, we tested islet viability by bioluminescence imaging (BLI). PROCEDURES: Pancreatic islets were isolated from luciferase-positive and luciferase-negative rats, mixed at a 1:1 ratio, placed into a plasma-thrombin bioscaffold, and transplanted in standard (10 pancreatic islets/g wt; n = 10) and marginal (4 pancreatic islets/g wt; n = 7) numbers into the omentums of syngeneic diabetic animals. For the control, 4 pancreatic islets/g were transplanted into the liver using the standard procedure (n = 7). Graft viability was tested by bioluminescence at days 14, 30, 60, and 90 post transplant. Glucose levels, intravenous glucose tolerance, and serum C-peptide were assessed regularly. RESULTS: Nonfasting glucose levels < 10 mmol/l were restored in all animals. While islet viability in the omentum was clearly detected by stable luminescence signals throughout the whole study period, no signals were detected from islets transplanted into the liver. The bioluminescence signals were highly correlated with stimulated C-peptide levels detected at 80 days post transplant. Glucose tolerance did not differ among the 3 groups. CONCLUSIONS: We successfully tested a preclinical model of islet transplantation into the greater omentum using a biocompatible scaffold made from autologous plasma and human thrombin. Both standard and marginal pancreatic islet numbers in a gel-form bioscaffold placed in the omentum restored glucose homeostasis in recipients with diabetes. Bioluminescence was shown promising as a direct proof of islet viability.

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.