Unbiased image segmentation assessment toolkit for quantitative differentiation of state-of-the-art algorithms and pipelines.

BACKGROUND: Image segmentation pipelines are commonly used in microscopy to identify cellular compartments like nucleus and cytoplasm, but there are few standards for comparing segmentation accuracy across pipelines. The process of selecting a segmentation assessment pipeline can seem daunting to researchers due to the number and variety of metrics available for evaluating segmentation quality. RESULTS: Here we present automated pipelines to obtain a comprehensive set of 69 metrics to evaluate segmented data and propose a selection methodology for models based on quantitative analysis, dimension reduction or unsupervised classification techniques and informed selection criteria. CONCLUSION: We show that the metrics used here can often be reduced to a small number of metrics that give a more complete understanding of segmentation accuracy, with different groups of metrics providing sensitivity to different types of segmentation error. These tools are delivered as easy to use python libraries, command line tools, Common Workflow Language Tools, and as Web Image Processing Pipeline interactive plugins to ensure a wide range of users can access and use them. We also present how our evaluation methods can be used to observe the changes in segmentations across modern machine learning/deep learning workflows and use cases.

Measuring dimensionality of cell-scaffold contacts of primary human bone marrow stromal cells cultured on electrospun fiber scaffolds.

The properties and structure of the cellular microenvironment can influence cell behavior. Sites of cell adhesion to the extracellular matrix (ECM) initiate intracellular signaling that directs cell functions such as proliferation, differentiation, and apoptosis. Electrospun fibers mimic the fibrous nature of native ECM proteins and cell culture in fibers affects cell shape and dimensionality, which can drive specific functions, such as the osteogenic differentiation of primary human bone marrow stromal cells (hBMSCs), by. In order to probe how scaffolds affect cell shape and behavior, cell-fiber contacts were imaged to assess their shape and dimensionality through a novel approach. Fluorescent polymeric fiber scaffolds were made so that they could be imaged by confocal fluorescence microscopy. Fluorescent polymer films were made as a planar control. hBSMCs were cultured on the fluorescent substrates and the cells and substrates were imaged. Two different image analysis approaches, one having geometrical assumptions and the other having statistical assumptions, were used to analyze the 3D structure of cell-scaffold contacts. The cells cultured in scaffolds contacted the fibers in multiple planes over the surface of the cell, while the cells cultured on films had contacts confined to the bottom surface of the cell. Shape metric analysis indicated that cell-fiber contacts had greater dimensionality and greater 3D character than the cell-film contacts. These results suggest that cell adhesion site-initiated signaling could emanate from multiple planes over the cell surface during culture in fibers, as opposed to emanating only from the cell's basal surface during culture on planar surfaces.

Single-cell-resolution map of human retinal pigment epithelium helps discover subpopulations with differential disease sensitivity.

Regional phenotypic and functional differences in the retinal pigment epithelium (RPE) monolayer have been suggested to account for regional susceptibility in ocular diseases such as age-related macular degeneration (AMD), late-onset retinal degeneration (L-ORD), and choroideremia (CHM). However, a comprehensive description of human topographical RPE diversity is not yet available, thus limiting the understanding of regional RPE diversity and degenerative disease sensitivity in the eye. To develop a complete morphometric RPE map of the human eye, artificial intelligence­based software was trained to recognize, segment, and analyze RPE borders. Five statistically different, concentric RPE subpopulations (P1 to P5) were identified using cell area as a parameter, including a subpopulation (P4) with cell area comparable to that of macular cells in the far periphery of the eye. This work provides a complete reference map of human RPE subpopulations and their location in the eye. In addition, the analysis of cadaver non-AMD and AMD eyes and ultra-widefield fundus images of patients revealed differential vulnerability of the five RPE subpopulations to different retinal diseases.

Deep learning predicts function of live retinal pigment epithelium from quantitative microscopy.

Increases in the number of cell therapies in the preclinical and clinical phases have prompted the need for reliable and noninvasive assays to validate transplant function in clinical biomanufacturing. We developed a robust characterization methodology composed of quantitative bright-field absorbance microscopy (QBAM) and deep neural networks (DNNs) to noninvasively predict tissue function and cellular donor identity. The methodology was validated using clinical-grade induced pluripotent stem cell-derived retinal pigment epithelial cells (iPSC-RPE). QBAM images of iPSC-RPE were used to train DNNs that predicted iPSC-RPE monolayer transepithelial resistance, predicted polarized vascular endothelial growth factor (VEGF) secretion, and matched iPSC-RPE monolayers to the stem cell donors. DNN predictions were supplemented with traditional machine-learning algorithms that identified shape and texture features of single cells that were used to predict tissue function and iPSC donor identity. These results demonstrate noninvasive cell therapy characterization can be achieved with QBAM and machine learning.

Modeling, validation and verification of three-dimensional cell-scaffold contacts from terabyte-sized images.

BACKGROUND: Cell-scaffold contact measurements are derived from pairs of co-registered volumetric fluorescent confocal laser scanning microscopy (CLSM) images (z-stacks) of stained cells and three types of scaffolds (i.e., spun coat, large microfiber, and medium microfiber). Our analysis of the acquired terabyte-sized collection is motivated by the need to understand the nature of the shape dimensionality (1D vs 2D vs 3D) of cell-scaffold interactions relevant to tissue engineers that grow cells on biomaterial scaffolds. RESULTS: We designed five statistical and three geometrical contact models, and then down-selected them to one from each category using a validation approach based on physically orthogonal measurements to CLSM. The two selected models were applied to 414 z-stacks with three scaffold types and all contact results were visually verified. A planar geometrical model for the spun coat scaffold type was validated from atomic force microscopy images by computing surface roughness of 52.35 nm ±31.76 nm which was 2 to 8 times smaller than the CLSM resolution. A cylindrical model for fiber scaffolds was validated from multi-view 2D scanning electron microscopy (SEM) images. The fiber scaffold segmentation error was assessed by comparing fiber diameters from SEM and CLSM to be between 0.46% to 3.8% of the SEM reference values. For contact verification, we constructed a web-based visual verification system with 414 pairs of images with cells and their segmentation results, and with 4968 movies with animated cell, scaffold, and contact overlays. Based on visual verification by three experts, we report the accuracy of cell segmentation to be 96.4% with 94.3% precision, and the accuracy of cell-scaffold contact for a statistical model to be 62.6% with 76.7% precision and for a geometrical model to be 93.5% with 87.6% precision. CONCLUSIONS: The novelty of our approach lies in (1) representing cell-scaffold contact sites with statistical intensity and geometrical shape models, (2) designing a methodology for validating 3D geometrical contact models and (3) devising a mechanism for visual verification of hundreds of 3D measurements. The raw and processed data are publicly available from https://isg.nist.gov/deepzoomweb/data/ together with the web -based verification system.

A switchable positive and negative air pressure device for efficient and gentle handling of nanofiber scaffolds.

A scaffold handling device (SHD) has been designed that can switch from gentle suction to positive pressure to lift and place nanofiber scaffolds. In tissue engineering laboratories, delicate fibrous scaffolds, such as electrospun nanofiber scaffolds, are often used as substrates for cell culture. Typical scaffold handling procedures include lifting the scaffolds, moving them from one container to another, sterilization, and loading scaffolds into cell culture plates. Using tweezers to handle the scaffolds can be slow, can damage the scaffolds, and can cause them to wrinkle or fold. Scaffolds may also acquire a static charge which makes them difficult to put down as they cling to tweezers. An SHD has been designed that enables more efficient, gentle lifting, and placement of delicate scaffolds. Most of the parts to make the SHD can be purchased, except for the tip which can be 3D-printed. The SHD enables more reliable handling of nanofiber scaffolds that may improve the consistency of biomanufacturing processes.

Training to Improve Precision and Accuracy in the Measurement of Fiber Morphology.

An estimated $7.1 billion dollars a year is spent due to irreproducibility in pre-clinical data from errors in data analysis and reporting. Therefore, developing tools to improve measurement comparability is paramount. Recently, an open source tool, DiameterJ, has been deployed for the automated analysis of scanning electron micrographs of fibrous scaffolds designed for tissue engineering applications. DiameterJ performs hundreds to thousands of scaffold fiber diameter measurements from a single micrograph within a few seconds, along with a variety of other scaffold morphological features, which enables a more rigorous and thorough assessment of scaffold properties. Herein, an online, publicly available training module is introduced for educating DiameterJ users on how to effectively analyze scanning electron micrographs of fibers and the large volume of data that a DiameterJ analysis yields. The end goal of this training was to improve user data analysis and reporting to enhance reproducibility of analysis of nanofiber scaffolds. User performance was assessed before and after training to evaluate the effectiveness of the training modules. Users were asked to use DiameterJ to analyze reference micrographs of fibers that had known diameters. The results showed that training improved the accuracy and precision of measurements of fiber diameter in scanning electron micrographs. Training also improved the precision of measurements of pore area, porosity, intersection density, and characteristic fiber length between fiber intersections. These results demonstrate that the DiameterJ training module improves precision and accuracy in fiber morphology measurements, which will lead to enhanced data comparability.

Nanofiber Scaffold-Based Tissue-Engineered Retinal Pigment Epithelium to Treat Degenerative Eye Diseases.

Clinical-grade manufacturing of a functional retinal pigment epithelium (RPE) monolayer requires reproducing, as closely as possible, the natural environment in which RPE grows. In vitro, this can be achieved by a tissue engineering approach, in which the RPE is grown on a nanofibrous biological or synthetic scaffold. Recent research has shown that nanofiber scaffolds perform better for cell growth and transplantability compared with their membrane counterparts and that the success of the scaffold in promoting cell growth/function is not heavily material dependent. With these strides, the field has advanced enough to begin to consider implementation of one, or a combination, of the tissue engineering strategies discussed herein. In this study, we review the current state of tissue engineering research for in vitro culture of RPE/scaffolds and the parameters for optimal scaffold design that have been uncovered during this research. Next, we discuss production methods and manufacturers that are capable of producing the nanofiber scaffolds in such a way that would be biologically, regulatory, clinically, and commercially viable. Then, a discussion of how the scaffolds could be characterized, both morphologically and mechanically, to develop a testing process that is viable for regulatory screening is performed. Finally, an example of a tissue-engineered RPE/scaffold construct is given to provide the reader a framework for understanding how these pieces could fit together to develop a tissue-engineered RPE/scaffold construct that could pass regulatory scrutiny and can be commercially successful.

Biomaterial Strategies for Immunomodulation.

Strategies to enhance, suppress, or qualitatively shape the immune response are of importance for diverse biomedical applications, such as the development of new vaccines, treatments for autoimmune diseases and allergies, strategies for regenerative medicine, and immunotherapies for cancer. However, the intricate cellular and molecular signals regulating the immune system are major hurdles to predictably manipulating the immune response and developing safe and effective therapies. To meet this challenge, biomaterials are being developed that control how, where, and when immune cells are stimulated in vivo, and that can finely control their differentiation in vitro. We review recent advances in the field of biomaterials for immunomodulation, focusing particularly on designing biomaterials to provide controlled immunostimulation, targeting drugs and vaccines to lymphoid organs, and serving as scaffolds to organize immune cells and emulate lymphoid tissues. These ongoing efforts highlight the many ways in which biomaterials can be brought to bear to engineer the immune system.

Dataset for the validation and use of DiameterJ an open source nanofiber diameter measurement tool.

DiameterJ is an open source image analysis plugin for ImageJ. DiameterJ produces ten files for every image that it analyzes. These files include the images that were analyzed, the data to create histograms of fiber radius, pore size, fiber orientation, and summary statistics, as well as images to check the output of DiameterJ. DiameterJ was validated with 130 in silico-derived, digital, synthetic images and 24 scanning electron microscope (SEM) images of steel wire samples with a known diameter distribution. Once validated, DiameterJ was used to analyze SEM images of electrospun polymeric nanofibers, including a comparison of different segmentation algorithms. In this article, all digital synthetic images, SEM images, and their segmentations are included. Additionally, DiameterJ's raw output files, and processed data is included for the reader. The data provided herein was used to generate the figures in DiameterJ: A Validated Open Source Nanofiber Diameter Measurement Tool[1], where more discussion can be found.

DiameterJ: A validated open source nanofiber diameter measurement tool.

Despite the growing use of nanofiber scaffolds for tissue engineering applications, there is not a validated, readily available, free solution for rapid, automated analysis of nanofiber diameter from scanning electron microscope (SEM) micrographs. Thus, the goal of this study was to create a user friendly ImageJ/FIJI plugin that would analyze SEM micrographs of nanofibers to determine nanofiber diameter on a desktop computer within 60 s. Additional design goals included 1) compatibility with a variety of existing segmentation algorithms, and 2) an open source code to enable further improvement of the plugin. Using existing algorithms for centerline determination, Euclidean distance transforms and a novel pixel transformation technique, a plugin called "DiameterJ" was created for ImageJ/FIJI. The plugin was validated using 1) digital synthetic images of white lines on a black background and 2) SEM images of nominally monodispersed steel wires of known diameters. DiameterJ analyzed SEM micrographs in 20 s, produced diameters not statistically different from known values, was over 10-times closer to known diameter values than other open source software, provided hundreds of times the sampling of manual measurement, and was hundreds of times faster than manual assessment of nanofiber diameter. DiameterJ enables users to rapidly and thoroughly determine the structural features of nanofiber scaffolds and could potentially allow new insights to be formed into fiber diameter distribution and cell response.

Molecular factors in dendritic cell responses to adsorbed glycoconjugates.

Carbohydrates and glycoconjugates have been shown to exert pro-inflammatory effects on the dendritic cells (DCs), supporting pathogen-induced innate immunity and antigen processing, as well as immunosuppressive effects in the tolerance to self-proteins. Additionally, the innate inflammatory response to implanted biomaterials has been hypothesized to be mediated by inflammatory cells interacting with adsorbed proteins, many of which are glycosylated. However, the molecular factors relevant for surface displayed glycoconjugate modulation of dendritic cell (DC) phenotype are unknown. Thus, in this study, a model system was developed to establish the role of glycan composition, density, and carrier cationization state on DC response. Thiol modified glycans were covalently bound to a model protein carrier, maleimide functionalized bovine serum albumin (BSA), and the number of glycans per BSA modulated. Additionally, the carrier isoelectric point was scaled from a pI of ∼4.0 to ∼10.0 using ethylenediamine (EDA). The DC response to the neoglycoconjugates adsorbed to wells of a 384-well plate was determined via a high throughput assay. The underlying trends in DC phenotype in relation to conjugate properties were elucidated via multivariate general linear models. It was found that glycoconjugates with more than 20 glycans per carrier had the greatest impact on the pro-inflammatory response from DCs, followed by conjugates having an isoelectric point above 9.5. Surfaces displaying terminal α1-2 linked mannose structures were able to increase the inflammatory DC response to a greater extent than did any other terminal glycan structure. The results herein can be applied to inform the design of the next generation of combination products and biomaterials for use in future vaccines and implanted materials.

Microfluidic thrombosis under multiple shear rates and antiplatelet therapy doses.

The mainstay of treatment for thrombosis, the formation of occlusive platelet aggregates that often lead to heart attack and stroke, is antiplatelet therapy. Antiplatelet therapy dosing and resistance are poorly understood, leading to potential incorrect and ineffective dosing. Shear rate is also suspected to play a major role in thrombosis, but instrumentation to measure its influence has been limited by flow conditions, agonist use, and non-systematic and/or non-quantitative studies. In this work we measured occlusion times and thrombus detachment for a range of initial shear rates (500, 1500, 4000, and 10000 s(-1)) and therapy concentrations (0-2.4 µM for eptifibatide, 0-2 mM for acetyl-salicylic acid (ASA), 3.5-40 Units/L for heparin) using a microfluidic device. We also measured complete blood counts (CBC) and platelet activity using whole blood impedance aggregometry. Effects of shear rate and dose were analyzed using general linear models, logistic regressions, and Cox proportional hazards models. Shear rates have significant effects on thrombosis/dose-response curves for all tested therapies. ASA has little effect on high shear occlusion times, even at very high doses (up to 20 times the recommended dose). Under ASA therapy, thrombi formed at high shear rates were 4 times more prone to detachment compared to those formed under control conditions. Eptifibatide reduced occlusion when controlling for shear rate and its efficacy increased with dose concentration. In contrast, the hazard of occlusion from ASA was several orders of magnitude higher than that of eptifibatide. Our results show similar dose efficacy to our low shear measurements using whole blood aggregometry. This quantitative and statistically validated study of the effects of a wide range of shear rate and antiplatelet therapy doses on occlusive thrombosis contributes to more accurate understanding of thrombosis and to models for optimizing patient treatment.