Μm Pixel Size Research Articles

Analytic sparse-view CBCT reconstruction using a novel sinogram restoration method based on higher-order Fourier harmonic peaks

This study presents an analytic sparse-view cone-beam computed tomography (CBCT) reconstruction method using a novel sinogram restoration technique based on higher-order Fourier harmonic peaks to obtain CBCT images of reasonable quality with a reduced radiation dose. The proposed method involves four main steps: (1) acquiring sparse-view (P144) sinogram from a CBCT system, (2) upsampling (P720) the original sparse-view sinogram with equally spaced zero padding, (3) separating higher-order Fourier harmonic peaks of the upsampled sinogram using a band-pass filter, and (4) restoring the sinogram of the higher-order harmonic peaks by taking its magnitude, followed by computationally cost-efficient filtered-backprojection (FBP)-based CBCT reconstruction and denoising processes. The notation P144 indicates that the number of projections is 144. To verify the efficacy of the proposed method, an experiment was performed on a chest phantom using a prototype CBCT system comprising an X-ray tube (90 kV p and 40 mA), a large-area flat-panel detector (388 μm pixel size), and a rotational gantry. The quality of the restored sparse-view CBCT images was quantitatively evaluated in terms of the image intensity profile, universal quality index (UQI), and peak signal-to-noise ratio (PSNR). The results indicate that the proposed sinogram restoration method effectively recovered zero-padded areas in the original upsampled sinogram with image intensities nearly identical to those of the reference dense-view (P720) sinogram, which demonstrates the efficacy of the proposed sinogram restoration method. The quality of the sparse-view CBCT image restored with higher-order harmonic peaks was close to that of the reference dense-view CBCT image, maintaining the image quality. The UQI and PSNR values of the restored sparse-view CBCT image were 0.93 and 34.84, respectively, which are approximately 1.3 and 1.2 times greater than those of the original sparse-view CBCT image, respectively, improving the image quality. Consequently, the proposed method has the potential to resolve the issues caused by sparse-view sampling in FBP-based CBCT.

Establishment of a Digital Laminography facility at the Malaysian Nuclear Agency

Digital Laminography (DL) is a technique that enables the estimation of indication depth from a set of digital projection radiographs. It allows the engineers or researchers to visualize and measure the depth from the object’s surface. The technique applies to welded components and non-metal applications such as composite materials. The technique also allows users to understand engineering problems and further analyze the cause of failures. Malaysian Nuclear Agency is pursuing the building and establishment the DL system at its facility. A gantry is designed to hold a 225kVp X-ray tube that is mechanically moved slowly. A 100 µm pixel size Digital Detector Array (DDA) is used to capture the images. This paper highlights simulation and a preliminary assessment to understand the physics and appropriate steps to build a DL system. It discusses the simulation and experimental study of exposure parameters and setup by digital radiographic testing (RT-D) of known imperfections of a welded steel plate before performing the DL measurement. The radiographic images and their achieved contrast sensitivity and image quality are analyzed according to ISO 17636-2. The results of simulations and experiments demonstrate a good and consistent ability to measure the depth and extension of the reconstructed imperfections within ± 1 mm regarding the actual size and position.

Improvements in Fast Mass Microscopy for Large-Area Samples.

Mass spectrometry imaging (MSI) is a technique that analyzes the chemical information and spatial distribution of surface analytes. Most MSI studies are conducted in microprobe mode, in which a mass spectrum is collected for each pixel to create a mass image. Thus, the spatial resolution, sample imaging area, and imaging speed are linked. In this mode, halving the pixel size quadruples the analytical time, which presents a practical limit on the high spatial resolution MSI throughput. Fast mass microscopy (FMM) is, in contrast, a microscope-mode MSI technique that decouples spatial resolution and imaging speed. FMM circumvents the linear-quadratic relationship of pixel size and analytical time, which enables increased imaging size area and the analytical speed achievable. In this study, we implement instrument modifications to the FMM system, including the addition of linear encoders that enable roughly 8.5× faster imaging than was previously achieved, allowing a 42.5 × 26 mm2 sample area to be imaged at a 1 μm pixel size in <4.5 min. Linear encoders also enable the alignment of multipass images that increase image homogeneity and signal intensity. The applicability of FMM to large area samples has made it important to define the tolerance to height variations of the technique, which was determined to be at least 218 ± 0.03 (n = 3) μm.

Ultra-high brightness Micro-LEDs with wafer-scale uniform GaN-on-silicon epilayers

Owing to high pixel density and brightness, gallium nitride (GaN) based micro-light-emitting diodes (Micro-LEDs) are considered revolutionary display technology and have important application prospects in the fields of micro-display and virtual display. However, Micro-LEDs with pixel sizes smaller than 10 μm still encounter technical challenges such as sidewall damage and limited light extraction efficiency, resulting in reduced luminous efficiency and severe brightness non-uniformity. Here, we reported high-brightness green Micro-displays with a 5 μm pixel utilizing high-quality GaN-on-Si epilayers. Four-inch wafer-scale uniform green GaN epilayer is first grown on silicon substrate, which possesses a low dislocation density of 5.25 × 108 cm−2, small wafer bowing of 16.7 μm, and high wavelength uniformity (standard deviation STDEV < 1 nm), scalable to 6-inch sizes. Based on the high-quality GaN epilayers, green Micro-LEDs with 5 μm pixel sizes are designed with vertical non-alignment bonding technology. An atomic sidewall passivation method combined with wet treatment successfully addressed the Micro-LED sidewall damages and steadily produced nano-scale surface textures on the pixel top, which unlocked the internal quantum efficiency of the high-quality green GaN-on-Si epi-wafer. Ultra-high brightness exceeding 107 cd/m2 (nits) is thus achieved in the green Micro-LEDs, marking the highest reported results. Furthermore, integration of Micro-LEDs with Si-based CMOS circuits enables the realization of green Micro-LED displays with resolution up to 1080 × 780, realizing high-definition playback of movies and images. This work lays the foundation for the mass production of high-brightness Micro-LED displays on large-size GaN-on-Si epi-wafers.

MALDI-2-Enabled Oversampling for the Mass Spectrometry Imaging of Metabolites at Single-Cell Resolution.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can provide valuable insights into the metabolome of complex biological systems such as organ tissues and cells. However, obtaining metabolite data at single-cell spatial resolutions presents a few technological challenges. Generally, spatial resolution is defined by the increment the sample stage moves between laser ablation spots. Stage movements less than the diameter of the focused laser beam (i.e., oversampling) can improve spatial resolution; however, such oversampling conditions result in a reduction in sensitivity. To overcome this, we combine an oversampling approach with laser postionization (MALDI-2), which allows for both higher spatial resolution and improved analyte ionization efficiencies. This approach provides significant enhancements to sensitivity for various metabolite classes (e.g., amino acids, purines, carbohydrates etc.), with mass spectral intensities from 6 to 8 μm pixel sizes (from a laser spot size of ∼13 μm) being commensurate with or higher than those obtained by conventional MALDI at 20 μm pixel sizes for many different metabolites. This technique has been used to map the distribution of metabolites throughout mouse spinal cord tissue to observe how metabolite localizations change throughout specific anatomical regions, such as those distributed to the somatosensory area of the dorsal horn, white matter, gray matter, and ventral horn. Furthermore, this method is utilized for single-cell metabolomics of human iPSC-derived astrocytes at 10 μm pixel sizes whereby many different metabolites, including nucleotides, were detected from individual cells while providing insight into cellular localizations.

Spatially resolved epigenome sequencing via Tn5 transposition and deterministic DNA barcoding in tissue.

Spatial epigenetic mapping of tissues enables the study of gene regulation programs and cellular functions with the dependency on their local tissue environment. Here we outline a complete procedure for two spatial epigenomic profiling methods: spatially resolved genome-wide profiling of histone modifications using in situ cleavage under targets and tagmentation (CUT&Tag) chemistry (spatial-CUT&Tag) and transposase-accessible chromatin sequencing (spatial-ATAC-sequencing) for chromatin accessibility. Both assays utilize in-tissue Tn5 transposition to recognize genomic DNA loci followed by microfluidic deterministic barcoding to incorporate spatial address codes. Furthermore, these two methods do not necessitate prior knowledge of the transcription or epigenetic markers for a given tissue or cell type but permit genome-wide unbiased profiling pixel-by-pixel at the 10 μm pixel size level and single-base resolution. To support the widespread adaptation of these methods, details are provided in five general steps: (1) sample preparation; (2) Tn5 transposition in spatial-ATAC-sequencing or antibody-controlled pA-Tn5 tagmentation in CUT&Tag; (3) library preparation; (4) next-generation sequencing; and (5) data analysis using our customed pipelines available at: https://github.com/dyxmvp/Spatial_ATAC-seq and https://github.com/dyxmvp/spatial-CUT-Tag . The whole procedure can be completed on four samples in 2-3 days. Familiarity with basic molecular biology and bioinformatics skills with access to a high-performance computing environment are required. A rudimentary understanding of pathology and specimen sectioning, as well as deterministic barcoding in tissue-specific skills (e.g., design of a multiparameter barcode panel and creation of microfluidic devices), are also advantageous. In this protocol, we mainly focus on spatial profiling of tissue region-specific epigenetic landscapes in mouse embryos and mouse brains using spatial-ATAC-sequencing and spatial-CUT&Tag, but these methods can be used for other species with no need for species-specific probe design.

3D electronic implants in subretinal space: Long-term follow-up in rodents

Clinical results with photovoltaic subretinal prosthesis (PRIMA) demonstrated restoration of sight via electrical stimulation of the interneurons in degenerated retina, with resolution matching the 100 μm pixel size. Since scaling the pixels below 75 μm in the current bipolar planar geometry will significantly limit the penetration depth of the electric field and increase stimulation threshold, we explore the possibility of using smaller pixels based on a novel 3-dimensional honeycomb-shaped design. We assessed the long-term biocompatibility and stability of these arrays in rats by investigating the anatomical integration of the retina with flat and 3D implants and response to electrical stimulation over lifetime – up to 32–36 weeks post-implantation in aged rats. With both flat and 3D implants, signals elicited in the visual cortex decreased after the day of implantation by more than 3-fold, and gradually recovered over the next 12–16 weeks. With 25 μm high honeycomb walls, the majority of bipolar cells migrate into the wells, while amacrine and ganglion cells remain above the cavities, which is essential for selective network-mediated stimulation of the retina. Retinal thickness and full-field stimulation threshold with 40 μm-wide honeycomb pixels were comparable to those with planar devices – 0.05 mW/mm2 with 10 ms pulses. However, fewer cells from the inner nuclear layer migrated into the 20 μm-wide wells, and stimulation threshold increased over 12–16 weeks, before stabilizing at about 0.08 mW/mm2. Such threshold is still significantly lower than 1.8 mW/mm2 with a previous design of flat bipolar pixels, confirming the promise of the 3D honeycomb-based approach to high resolution subretinal prosthesis.

P‐141: Ultrafine‐pitch AlGaN Ultraviolet‐C microLED Displays for Quantum Dots Color Conversion

Aluminum Gallium Nitride (AlGaN) ultraviolet‐C (UV‐C) micro‐light‐emitting diodes (microLEDs) offer significant advantages in terms of convenience, cost‐effectiveness, and environmental friendliness, positioning them as promising candidates for display applications. However, achieving the desired high efficiency and scalability for large displays with ultra‐fine pixels necessitates substantial progress beyond current experimental outcomes. This study showcases the application of AlGaN UV‐C microLED display panels and micro‐displays incorporating quantum dots (QDs) for color conversion. Sidewall treatment and atomic layer deposited (ALD) passivation effectively address dangling bonds and etching damages, leading to a notable enhancement of TM‐polarized light extraction efficiency (LEE). Moreover, dedicated strain modulation efforts successfully reduce the high Al content (over 50%) wafer bowling effect, facilitating the modularization of ultrafine‐pitch AlGaN UV‐C microLED panels. Consequently, the devices achieve a peak performance of over 5% external quantum efficiency (EQE) as the mesa size scales down to 3 μm. The highlighted 0.18‐inch UV‐C microLED display panels, featuring a 9 μm pixel size, are precisely controlled by a CMOS IC driver to achieve desired patterns. Serving as an efficient pumping source for perovskite quantum dots paper (PQDP), this UV‐C microLED display suggests the potential to revolutionize the full‐color display industry by providing an innovative and unconventional solution.

Two photon imaging probe with highly efficient autofluorescence collection at high scattering and deep imaging conditions

In this paper, we present a 2-photon imaging probe system featuring a novel fluorescence collection method with improved and reliable efficiency. The system aims to miniaturize the potential of 2-photon imaging in the metabolic and morphological characterization of cervical tissue at sub-micron resolution over large imaging depths into a flexible and clinically viable platform towards the early detection of cancers. Clinical implementation of such a probe system is challenging due to inherently low levels of autofluorescence, particularly when imaging deep in highly scattering tissues. For an efficient collection of fluorescence signals, our probe employs 12 0.5 NA collection fibers arranged around a miniaturized excitation objective. By bending and terminating a multitude of collection fibers at a specific angle, we increase collection area and directivity significantly. Positioning of these fibers allows the collection of fluorescence photons scattered away from their ballistic trajectory multiple times, which offers a system collection efficiency of 4%, which is 55% of what our bench-top microscope with 0.75 NA objective achieves. We demonstrate that the collection efficiency is largely maintained even at high scattering conditions and high imaging depths. Radial symmetry of arrangement maintains uniformity of collection efficiency across the whole FOV. Additionally, our probe can image at different tissue depths via axial actuation by a dc servo motor, allowing depth dependent tissue characterization. We designed our probe to perform imaging at 775 nm, targeting 2-photon autofluorescence from NAD(P)H and FAD molecules, which are often used in metabolic tissue characterization. An air core photonic bandgap fiber delivers laser pulses of 100 fs duration to the sample. A miniaturized objective designed with commercially available lenses of 3 mm diameter focuses the laser beam on tissue, attaining lateral and axial imaging resolutions of 0.66 µm and 4.65 µm, respectively. Characterization results verify that our probe achieves collection efficiency comparable to our optimized bench-top 2-photon imaging microscope, minimally affected by imaging depth and radial positioning. We validate autofluorescence imaging capability with excised porcine vocal fold tissue samples. Images with 120 µm FOV and 0.33 µm pixel sizes collected at 2 fps confirm that the 300 µm imaging depth was achieved.

Design and fabrication of a sandwich detector for material discrimination and contrast cancellation in dual-energy based x-ray imaging

Dual-energy imaging represents a versatile and evolving technology with wide-ranging applications in medicine and beyond. Recent technological developments increased the potential for improved diagnostic accuracy and expanded imaging capabilities across various fields. The purpose of this work is to design and develop an energy-integrating multilayer detector, known as a sandwich detector, aimed at single-shot dual-energy imaging tasks such as material discrimination and contrast cancellation. The sandwich detector uses two complementary metal oxide semiconductor advanced pixel sensors of 50 μm pixel size. The top and bottom sensors detect low-energy (LE) and high-energy (HE) photons, with sensors coupled with 250 and 600 μm scintillators, respectively. For better spectral separation between layers without excessively affecting the detected statistic in the bottom layer, the insertion of a 0.25-mm Cu filter between the layers was found to be the optimal choice, from among the tested 0-, 0.25-, and 0.5-mm filter options. The thickness selection for scintillator and intermediate Cu filter was carried out through a dual-energy simulation model. The experiments confirmed the model's reliability in selecting the optimal thicknesses of the intermediate Cu filter, thereby providing reassurance also on the choice of the top scintillator.

Quantifying the spatial heterogeneity of topsoil microstructure in a horticultural cover cropping system from Southwestern Ontario, Canada

Cover crops (CC) are promoted to enhance soil structure and aggregation, but little is known about their impact on the spatial variability of soil microstructure. This study was conducted to assess the effects of medium-term (4-yr) annual CC systems, including oat (Avena sativa L.), winter cereal rye (rye; Secale cereale L.), oilseed radish (OSR; Raphanus sativus L. var. oleoferus Metzg. Stokes), as well as a mixture of OSR and winter cereal rye (OSR + Rye), against a control (no cover crop, no-CC), on topsoil microstructure utilizing 3D semivariance analysis, as influenced by soil depth (0–5 and 5–10 cm) in a tile-drained Orthic Humic Gleysol in Ridgetown, Ontario, Canada. Replicate undisturbed topsoil core samples were collected manually in plexiglass tubes from each plot. All soil cores were dried at 40 °C, then imaged at 20 μm pixel size using GE MS8-130× CT scanner (120kv, 0.5 mm Cu filter). The whole core greyscale imagery (representing radiodensity on the Hounsfield Scale) was subjected to a three-phase segmentation (solids, voids, and remaining soil matrix). For the whole soil and the soil matrix imagery, 16-bit histograms and 3D orthogonal semivariograms were generated. Directional anisotropy and four semivariogram parameters close to the origin, including the ratio between the values of the total variance and the semivariance at first lag (RVF), the ratio between semivariance values at second and first lag (RSF), first derivative near the origin (FDO), and second derivative at the third lag (SDT), were calculated to explain spatial variability in the soil microstructure. The results exhibited lower radiodensities for whole soil samples from the 0–5 cm than 5–10 cm layers. All CCs, other than oats, showed lower radiodensities than the control (no-CC). For both the whole soil and soil matrix, more variability was encountered in the vertical than the horizontal dimensions of all soils. Comparing the whole soil and the soil matrix in different CC systems and layers, more anisotropy was pronounced in the soil matrix than the whole soil imagery. The highest and the lowest anisotropy, calculated for the whole soil and soil matrix of different CC systems, were observed in oat and rye plots, respectively. There were no significant differences among CCs systems in terms of RVF, RSF, and SDT values, suggesting similarity of the structure at the scale slightly above image resolution. The results illustrated that soils under different CC systems showed only significant differences in the whole soil for FDO values (P ≤ 0.08). All four near-origin semivariogram parameters showed significant differences between 0 and 5 and 5–10 cm layers in both the whole soil and the soil matrix, suggesting more complexity in the microstructure of the uppermost soil layers.

Abstract 3800: Next generation of spatial biology: High-throughput multiplexed Imaging Mass Cytometry™ with whole slide modes

Abstract Gaining spatial insights into the cellular composition of tumor tissue has tremendous potential to inform clinical and translational researchers about mechanisms behind spatial predictors of immunotherapy success, disease etiology and progression. Imaging Mass Cytometry™ (IMC™) is a high-plex spatial biology imaging technique that enables deep characterization of the diversity and complexity of the tumor microenvironment (TME). IMC supports detailed assessment of cell phenotype and function using 40-plus metal-tagged antibodies simultaneously on a single slide without issues associated with fluorescence-based spectral overlap, tissue autofluorescence or implementation of multiple washing and acquisition cycles. Currently, IMC enables user-defined regions of interest (ROI) in tissues to evaluate cellular and structural composition. To enhance the IMC user experience, we developed two new whole slide imaging (WSI) modes which enable streamlined workflows using ultrafast preview mode (PM) and high-throughput tissue mode (TM). PM samples the entire tissue at predefined spacing to rapidly capture a low-resolution image of all expressed markers in the antibody panel. PM generates an image in minutes to enable informed ROI placements while leaving the stained tissue intact for higher-resolution imaging. PM and TM are designed so acquisitions can easily occur on the same slide without additional processing steps. TM rapidly acquires images of the whole tissue at lower resolution (7 μm pixel size) at a quality that can be used for quantitative analysis of the tissue spatial biology. Specifically designed for high-throughput applications, TM in combination with a newly available 40-slide loader for the Hyperion XTi™ Imaging System permits automated and continuous imaging of more than 40 large tissue samples (400 mm2 per tissue) per week. We showcase the application of WSI modes using the newly developed Maxpar® Human Immuno-Oncology IMC Panel Kit. The 31-marker panel was combined with catalog antibodies to create a 40-plus-marker panel that expands the ability to conduct comprehensive high-plex tumor and immune cell profiling. Tumor tissue microarrays (TMA) and whole tumor tissue sections were stained with the expanded panel. Single-cell analysis of selected ROIs, on whole tumor sections and TMAs, guided by PM data successfully provided quantitative analyses of spatial biology at single-cell resolution. In parallel, TM on whole tumor sections followed by pixel-based analysis provided a spatially resolved quantitative assessment of specific tumor and immune components of the TME. This work demonstrates the expanded capabilities of IMC and establishes it as a reliable high-plex spatial biology imaging platform with high-throughput imaging capabilities ideally suited for translational and clinical applications. For Research Use Only. Not for use in diagnostic procedures. Citation Format: Qanber Raza, Thomas D. Pfister, Jyh Yun Chwee, Liang Lim, David Howell, Nikesh Parsotam, David King, Christina Loh. Next generation of spatial biology: High-throughput multiplexed Imaging Mass Cytometry™ with whole slide modes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3800.

THE RELATIONSHIP BETWEEN MICROSTRUCTURE AND MECHANICAL RESPONSE IN THE HUMAN MENISCUS

To characterize the microstructural organization of collagen fibers in human medial menisci and the response to mechanical loading in relation to age. We combine high resolution imaging with mechanical compression to visualize the altered response of the tissue at the microscale. Menisci distribute the load in the knee and are predominantly composed of water and specifically hierarchically arranged collagen fibers. Structural and compositional changes are known to occur in the meniscus during aging and development of osteoarthritis. However, how microstructural changes due to degeneration affect mechanical performance is still largely unknown [1].Fresh frozen 4 mm Ø plugs of human medial menisci (n=15, men, 20-85 years) with no macroscopic damage nor known diseases from the MENIX biobank at Skåne University Hospital were imaged by phase contrast synchrotron tomography at the TOMCAT beamline (Paul Scherrer Institute, CH). A rheometer was implemented into the beamline to perform in-situ stress relaxation (2 steps 15% and 30% strain) during imaging (21 keV, 2.75μm pixel size). 40s scans were acquired before and after loading, while 14 fast tomographs (5s acquisitions) were taken during relaxation. The fiber 3D orientations and structural changes during loading were determined using a structure tensor approach (adapting a script from [1]). The 3D collagen fiber orientation in menisci revealed alternating layers of fibers. Two main areas are shown: surfaces and bulk. The surface layers are a mesh of randomly oriented fibers. Within the bulk 2-3 layers of fibers are visible that alternate about 30° to each other. Structural degeneration with age is visible and is currently being quantified. During stress-relaxation all menisci show a similar behavior, with samples from older donors being characterized by larger standard deviation Furthermore, the behavior of the different layers of fibers is tracked during relaxation showing how fibers with different orientation respond to the applied loading.Acknowledgments: We thank PSI for the beamtime at the TOMCAT beamline X02DA, and funding from Swedish Research Council (2019-00953), under the frame of ERA PerMed, and the Novo Nordisk Foundation through MathKOA (NNF21OC0065373).

Enhancing spatial resolution in MÖNCH for electron microscopy via deep learning

Hybrid Pixel Detectors (HPDs) are highly suitable in diffraction-based electron microscopy due to their high frame rates (> 1 kHz), high dynamic range, and good radiation hardness. However, their use in imaging applications has been limited by their relatively large pixel size (≥ 55 μm) and high-energy (>80 keV) electrons scattering over multiple pixels in the sensor layer. To realize the full potential of fast, radiation-hard HPDs across electron microscopy modalities, we developed deep learning techniques to precisely localize the impact point of incident electrons in MÖNCH, a charge integrating HPD with 25 μm pixel size. With neural network models trained using labeled data via simulations and experimental measurements, the best spatial resolution obtained, defined in terms of the root mean squared error, was 0.60 pixels for 200 keV electrons, a three-fold improvement over a simple charge centroid method. This article presents the training sample generation, deep learning model design, training results, and imaging outcomes for a sample containing gold nanoparticles.

CNR performance of semiconductor materials for X-ray imaging of breast calcifications

We present the results of a GAMOS/GEANT4 computer simulation of a standard X-ray mammography system, which consists of a Tungsten 28 kVp polychromatic X-ray source with a 50 μm Rh filter, a mammography phantom with Al2O3 spherical specks of different diameters, and a generic pixel detector (55 μm × 55 μm pixel size) with different types of semiconductor sensors. The number of photons simulated is calibrated to produce similar entrance surface dose (ESD) as the one used by a standard clinical mammography screening. Estimates of Contrast to Noise Ratio (CNR) as a function of ESD, sensor thickness and microcalcification diameter are presented for four different sensor materials: Silicon (Si), Cadmium Telluride (CdTe), Gallium Arsenide (GaAs) and Perovskite (MAPbI3). For the X-ray energy spectrum and pixel size considered, and an ESD dose of 4 mGy, our study shows that, with the exception of Si, these sensors, as thin as 200 μm, are able to resolve (with at least 3 standard deviations above background) Al2O3 spherical specks up to a minimum diameter of 180 μm, having statistically compatible CNR performance. The increase in substrate thickness has a substantial improvement in the CNR values provided by the Si sensor, while for the other cases the enhancement of CNR is marginal and consistent with statistical uncertainties with the thinnest case considered.

Evaluation of planar silicon pixel sensors with the RD53A readout chip for the Phase-2 Upgrade of the CMS Inner Tracker

The Large Hadron Collider at CERN will undergo an upgrade in order to increase its luminosity to 7.5 × 1034 cm-2s-1. The increased luminosity during this High-Luminosity running phase, starting around 2029, means a higher rate of proton-proton interactions, hence a larger ionizing dose and particle fluence for the detectors. The current tracking system of the CMS experiment will be fully replaced in order to cope with the new operating conditions. Prototype planar pixel sensors for the CMS Inner Tracker with square 50 μm × 50 μm and rectangular 100 μm × 25 μm pixels read out by the RD53A chip were characterized in the lab and at the DESY-II testbeam facility in order to identify designs that meet the requirements of CMS during the High-Luminosity running phase. A spatial resolution of approximately 3.4 μm (2 μm) is obtained using the modules with 50 μm × 50 μm (100 μm × 25 μm) pixels at the optimal angle of incidence before irradiation. After irradiation to a 1 MeV neutron equivalent fluence of Φeq = 5.3 × 1015 cm-2, a resolution of 9.4 μm is achieved at a bias voltage of 800 V using a module with 50 μm × 50 μm pixel size. All modules retain a hit efficiency in excess of 99% after irradiation to fluences up to 2.1 × 1016 cm-2. Further studies of the electrical properties of the modules, especially crosstalk, are also presented in this paper.

Mass Spectrometry Imaging of In Vitro Cryptosporidium parvum-Infected Cells and Host Tissue.

Cryptosporidium parvum is a zoonotic-relevant parasite belonging to the phylum Alveolata (subphylum Apicomplexa). One of the most zoonotic-relevant etiologies of cryptosporidiosis is the species C. parvum, infecting humans, cattle and wildlife. C. parvum-infected intestinal mucosa as well as host cells infected in vitro have not yet been the subject of extensive biochemical investigation. Efficient treatment options or vaccines against cryptosporidiosis are currently not available. Human cryptosporidiosis is currently known as a neglected poverty-related disease (PRD), being potentially fatal in young children or immunocompromised patients. In this study, we used a combination of atmospheric pressure scanning microprobe matrix-assisted laser desorption/ionization (AP-SMALDI) mass spectrometry imaging (MSI) and liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) to determine and locate molecular biomarkers in in vitro C. parvum-infected host cells as well as parasitized neonatal calf intestines. Sections of C. parvum-infected and non-infected host cell pellets and infected intestines were examined to determine potential biomarkers. Human ileocecal adenocarcinoma cells (HCT-8) were used as a suitable in vitro host cell system. More than a thousand different molecular signals were found in both positive- and negative-ion mode, which were significantly increased in C. parvum-infected material. A database search in combination with HPLC-MS/MS experiments was employed for the structural verification of markers. Our results demonstrate some overlap between the identified markers and data obtained from earlier studies on other apicomplexan parasites. Statistically relevant biomarkers were imaged in cell layers of C. parvum-infected and non-infected host cells with 5 µm pixel size and in bovine intestinal tissue with 10 µm pixel size. This allowed us to substantiate their relevance once again. Taken together, the present approach delivers novel metabolic insights on neglected cryptosporidiosis affecting mainly children in developing countries.

Lipid Signatures and Inter-Cellular Heterogeneity of Naı̈ve and Lipopolysaccharide-Stimulated Human Microglia-like Cells.

Microglia are non-neuronal cells, which reside in the central nervous system and are known to play an important role in health and disease. We investigated the lipidomic phenotypes of human naı̈ve and stimulated microglia-like cells by atmospheric-pressure scanning microprobe matrix-assisted laser desorption/ionization mass spectrometry imaging (AP-SMALDI MSI). With lateral resolutions between 5 and 1.5 μm pixel size, we were able to chart lipid compositions of individual cells, enabling differentiation of cell lines and stimulation conditions. This allowed us to reveal local lipid heterogeneities in naı̈ve and lipopolysaccharide (LPS)-stimulated cells. We were able to identify individual cells with elevated triglyceride (TG) levels and could show that the number of these TG-enriched cells increased with LPS stimulation as a hallmark for a proinflammatory phenotype. Additionally, the observed local abundance alterations of specific phosphatidylinositols (PIs) indicate a cell specific regulation of the PI metabolism.

Phasor Representation Approach for Rapid Exploratory Analysis of Large Infrared Spectroscopic Imaging Data Sets.

Infrared (IR) spectroscopic imaging is potentially useful for digital histopathology as it provides spatially resolved molecular absorption spectra, which can subsequently yield useful information by powerful artificial intelligence methods. A typical analysis pipeline in using IR imaging data for chemical pathology often involves iterative processes of segmentation, evaluation, and analysis that necessitate rapid data exploration. Here, we present a fast, reliable, and intuitive method based on a phasor representation of spectra and discuss its unique applicability for IR imaging data. We simulate different features extant in IR spectra and discuss their influence on the phasor waveforms; similarly, we undertake IR image analysis in the transform space to understand spectral similarity and variance. We demonstrate the potential of phasor analysis for biomedical tissue imaging using a variety of samples, using fresh frozen surgical prostate resections and formalin-fixed paraffin-embedded breast cancer tissue microarray samples as model systems that span common histopathology practice. To demonstrate further generalizability of this approach, we apply the method to data from different experimental conditions─including standard (5.5 μm × 5.5 μm pixel size) and high-definition (1.1 μm × 1.1 μm pixel size) Fourier transform IR (FTIR) spectroscopic imaging using transmission and transflection modes. Quantitative segmentation results from our approach are compared to previous studies, showing good agreement and quick visualization. The presented method is rapid, easy to use, and highly capable of deciphering compositional differences, presenting a convenient tool for exploratory analysis of IR imaging data.

Microscopy-Directed Imaging Mass Spectrometry for Rapid High Spatial Resolution Molecular Imaging of Glomeruli.

The glomerulus is a multicellular functional tissue unit (FTU) of the nephron that is responsible for blood filtration. Each glomerulus contains multiple substructures and cell types that are crucial for their function. To understand normal aging and disease in kidneys, methods for high spatial resolution molecular imaging within these FTUs across whole slide images is required. Here we demonstrate a workflow using microscopy-driven selected sampling to enable 5 μm pixel size matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) of all glomeruli within whole slide human kidney tissues. Such high spatial resolution imaging entails large numbers of pixels, increasing the data acquisition times. Automating FTU-specific tissue sampling enables high-resolution analysis of critical tissue structures, while concurrently maintaining throughput. Glomeruli were automatically segmented using coregistered autofluorescence microscopy data, and these segmentations were translated into MALDI IMS measurement regions. This allowed high-throughput acquisition of 268 glomeruli from a single whole slide human kidney tissue section. Unsupervised machine learning methods were used to discover molecular profiles of glomerular subregions and differentiate between healthy and diseased glomeruli. Average spectra for each glomerulus were analyzed using Uniform Manifold Approximation and Projection (UMAP) and k-means clustering, yielding 7 distinct groups of differentiated healthy and diseased glomeruli. Pixel-wise k-means clustering was applied to all glomeruli, showing unique molecular profiles localized to subregions within each glomerulus. Automated microscopy-driven, FTU-targeted acquisition for high spatial resolution molecular imaging maintains high-throughput and enables rapid assessment of whole slide images at cellular resolution and identification of tissue features associated with normal aging and disease.