Quantitative assessment of p-glycoprotein expression and function using confocal image analysis.

QIBA guidance: Computed tomography imaging for COVID-19 quantitative imaging applications

Proper membrane localization of ion channels is essential for the function of neuronal cells. Particularly, the computational ability of dendrites depends on the localization of different ion channels in specific subcompartments. However, the molecular mechanisms that control ion channel localization in distinct dendritic subcompartments are largely unknown. Here, we developed a quantitative live cell imaging method to analyze protein sorting and post-Golgi vesicular trafficking. We focused on two dendritic voltage-gated potassium channels that exhibit distinct localizations: Kv2.1 in proximal dendrites and Kv4.2 in distal dendrites. Our results show that Kv2.1 and Kv4.2 channels are sorted into two distinct populations of vesicles at the Golgi apparatus. The targeting of Kv2.1 and Kv4.2 vesicles occurred by distinct mechanisms as evidenced by their requirement for specific peptide motifs, cytoskeletal elements, and motor proteins. By live cell and super-resolution imaging, we identified a novel trafficking machinery important for the localization of Kv2.1 channels. Particularly, we identified non-muscle myosin II as an important factor in Kv2.1 trafficking. These findings reveal that the sorting of ion channels at the Golgi apparatus and their subsequent trafficking by unique molecular mechanisms are crucial for their specific localizations within dendrites.

In this study, we present a novel single-shot polarization-resolved digital holographic microscope (PDHM) that integrates both double field-of-view (DFoV) and polarization imaging for real-time, live-cell imaging. This innovative system overcomes the limitations of conventional techniques by simultaneously capturing two distinct regions of the sample, each with polarization information. Using a carefully configured Sagnac setup, the reference beam is split into orthogonally polarized components, each modulated with a distinct spatial carrier frequency. This allows the independent reconstruction of polarization-resolved complex fields. At the same time, a beam splitter placed in the object path spatially folds two separate regions of the sample onto the same sensor area, thereby achieving angular multiplexing without the need for additional optics. This configuration allows both spatially and polarization-resolved information in a single acquisition. The system is experimentally validated on live MCF-7 breast cancer cells, where it successfully reconstructs phase anisotropy and internal cellular features in real time. Its ability to capture wide-field, label-free, and polarization-sensitive information in a compact format makes it a promising tool for biomedical imaging and dynamic cell analysis.

Various three-dimensional (3D) cell culture methods have been developed to implement tumor models similar to in vivo. However, the conventional 3D cell culture method has limitations such as difficulty in using an extracellular matrix (ECM), low experimental reproducibility, complex 3D cell culture protocol, and difficulty in applying to high array plates such as 96- or 384-plates. Therefore, detailed protocols related to robust 3D-aggregated spheroid model (3D-ASM) production were optimized and proposed. A specially designed wet chamber was used to implement 3D-ASM using the hepatocellular carcinoma (HCC) cell lines, and the conditions were established for the icing step to aggregate the cells in one place and optimized ECM gelation step. Immunofluorescence (IF) staining is mainly used to simultaneously analyze drug efficacy and changes in drug-target biomarkers. By applying the IF staining method to the 3D-ASM model, confocal microscopy imaging and 3D deconvolution image analysis were also successfully performed. Through a comparative study of drug response with conventional 2D-high throughput screening (HTS), the 3D-HTS showed a more comprehensive range of drug efficacy analyses for HCC cell lines and enabled selective drug efficacy analysis for the FDA-approved drug sorafenib. This suggests that increased drug resistance under 3D-HTS conditions does not reduce the analytical discrimination of drug efficacy, also drug efficacy can be analyzed more selectively compared to the conventional 2D-HTS assay. Therefore, the 3D-HTS-based drug efficacy analysis method using an automated 3D-cell spotter/scanner, 384-pillar plate/wet chamber, and the proposed 3D-ASM fabrication protocol is a very suitable platform for analyzing target drug efficacy in HCC cells.

Intense efforts are underway to evaluate neuroimaging measures as biomarkers for neurodegeneration in premanifest Huntington's disease (preHD). We used a completely automated longitudinal analysis method to compare structural scans in preHD individuals and controls. Using a 1-year longitudinal design, we analyzed T(1) -weighted structural scans in 35 preHD individuals and 22 age-matched controls. We used the SIENA (Structural Image Evaluation, using Normalization, of Atrophy) software tool to yield overall percentage brain volume change (PBVC) and voxel-level changes in atrophy. We calculated sample sizes for a hypothetical disease-modifying (neuroprotection) study. We found significantly greater yearly atrophy in preHD individuals versus controls (mean PBVC controls, -0.149%; preHD, -0.388%; P = .031, Cohen's d = .617). For a preHD subgroup closest to disease onset, yearly atrophy was more than 3 times that of controls (mean PBVC close-to-onset preHD, -0.510%; P = .019, Cohen's d = .920). This atrophy was evident at the voxel level in periventricular regions, consistent with well-established preHD basal ganglia atrophy. We estimated that a neuroprotection study using SIENA would only need 74 close-to-onset individuals in each arm (treatment vs placebo) to detect a 50% slowing in yearly atrophy with 80% power. Automated whole-brain analysis of structural MRI can reliably detect preHD disease progression in 1 year. These results were attained with a readily available imaging analysis tool, SIENA, which is observer independent, automated, and robust with respect to image quality, slice thickness, and different pulse sequences. This MRI biomarker approach could be used to evaluate neuroprotection in preHD.

Assessment of adrenal incidentaloma relies on imaging analysis and evaluation of adrenal function. Radiomics as a tool for quantitative image analysis is useful for evaluation of adrenal incidentaloma. In this review, we examined radiomic literature on adrenal incidentaloma including both adrenal functional assessment and structural differentiation of benign versus malignant adrenal tumors. In this review, we summarized the status of radiomic application on adrenal incidentaloma and suggested potential direction for future research.

Clinical Utility of Quantitative Imaging

Cancer stem cells (CSCs) are a heterogeneous and dynamic self-renewing population that stands at the top of tumor cellular hierarchy and contribute to tumor recurrence and therapeutic resistance. As methods of CSC isolation and functional interrogation advance, there is a need for a reliable and accessible quantitative approach to assess heterogeneity and state transition dynamics in CSCs. We developed a high-throughput automated single cell imaging analysis (HASCIA) approach for the quantitative assessment of protein expression with single-cell resolution and applied the method to investigate spatiotemporal factors that influence CSC state transition using glioblastoma (GBM) CSCs (GSCs) as a model system. We were able to validate the quantitative nature of this approach through comparison of the protein expression levels determined by HASCIA to those determined by immunoblotting. A virtue of HASCIA was exemplified by detection of a subpopulation of SOX2-low cells, which expanded in fraction size during state transition. HASCIA also revealed that GSCs were committed to loose stem cell state at an earlier time point than the average SOX2 level decreased. Functional assessment of stem cell frequency in combination with the quantification of SOX2 expression by HASCIA defined a stable cutoff of SOX2 expression level for stem cell state. We also developed an approach to assess local cell density and found that denser monolayer areas possess higher average levels of SOX2, higher cell diversity, and a presence of a sub-population of slowly proliferating SOX2-low GSCs. HASCIA is an open source software that facilitates understanding the dynamics of heterogeneous cell population such as that of GSCs and their progeny. It is a powerful and easy-to-use image analysis and statistical analysis tool available at https://hascia.lerner.ccf.org. © 2019 International Society for Advancement of Cytometry.

DiOlistic labelling is a robust, unbiased ballistic method that utilises lipophilic dyes to morphologically label neurons. While its efficacy on freshly dissected tissue specimens is well-documented, applying DiOlistic labelling to stored, fixed brain tissue and its use in polychromatic multi-marker studies poses significant technical challenges. Here, we present an improved, step-by-step protocol for DiOlistic labelling of dendrites and dendritic spines in fixed mouse tissue. Our protocol encompasses the five key stages: Tissue Preparation, Dye Bullet Preparation, DiOlistic Labelling, Confocal Imaging, and Image Analysis. This method ensures reliable and consistent labelling of dendritic spines in fixed mouse tissue, combined with increased throughput of samples and multi-parameter staining and visualisation of tissue, thereby offering a valuable approach for neuroscientific research.

Effect of collagen matrix on mechanical properties of bone

Influence of tumor necrosis factor-α on the expression and function of P-glycoprotein in an immortalised rat brain capillary endothelial cell line, GPNT

Image analysis tools are currently in use for a variety of applications in the fields of forensics and security printing. Objective, quantitative data allow for characterization and comparison of a variety of image attributes.In forensics, document examiners can use quantitative image analysis systems in authentication, detection and analysis of forgeries, counterfeits and altered documents. Statistical analysis enables population characterization that can help in forgery detection and supports the potential for source identification. In security printing, image analysis tools can be applied to measure the quality of printed output and assess wear for bank notes.Flexible hardware options allow for a broad application of image quality measurements in a variety of image analysis situations. Camera and scanner-based image quality systems can be used for quantitative analysis of image content. A laser-based system can be used for height and depth profiling. Oblique angle illumination and scanning can be used for impression detection. A flatbed scanner can be used in transmission mode for the evaluation of bank note wear and for watermark analysis.In this paper, we will be discussing the use of a variety of hardware configurations for image analysis in forensics and security printing.

BackgroundThe application of artificial intelligence (AI) to whole slide images has the potential to improve research reliability and ultimately diagnostic efficiency and service capacity. Image annotation plays a key role in AI and digital pathology. However, the work‐streams required for tissue‐specific (skin) and immunostain‐specific annotation has not been extensively studied compared with the development of AI algorithms.ObjectivesThe objective of this study is to develop a common workflow for annotating whole slide images of biopsies from inflammatory skin disease immunostained with a variety of epidermal and dermal markers prior to the development of the AI‐assisted analysis pipeline.MethodsA total of 45 slides containing 3–5 sections each were scanned using Aperio AT2 slide scanner (Leica Biosystems). These slides were annotated by hand using a commonly used image analysis tool which resulted in more than 4000 images blocks. We used deep learning (DL) methodology to first sequentially segment (epidermis and upper dermis), with the exclusion of common artefacts and second to quantify the immunostained signal in those two compartments of skin biopsies and the ratio of positive cells.ResultsWe validated two DL models using 10‐fold validation runs and by comparing to ground truth manually annotated data. The models achieved an average (global) accuracy of 95.0% for the segmentation of epidermis and dermis and 86.1% for the segmentation of positive/negative cells.ConclusionsThe application of two DL models in sequence facilitates accurate segmentation of epidermal and dermal structures, exclusion of common artefacts and enables the quantitative analysis of the immunostained signal. However, inaccurate annotation of the slides for training the DL model can decrease the accuracy of the output. Our open source code will facilitate further external validation across different immunostaining platforms and slide scanners.

The goal of a QIBA Profile is to help achieve a useful level of performance for a given biomarker. The Claim (Section 2) describes the biomarker performance and is derived from the body of scientific literature meeting specific requirements, in particular test-retest studies. The Activities (Section 3) contribute to generating the biomarker. Requirements are placed on the Actors that participate in those activities as necessary to achieve the Claim. Assessment Procedures (Section 4) for evaluating specific requirements are defined as needed to ensure acceptable performance. Diffusion-Weighted Imaging (DWI) and the Apparent Diffusion Coefficient (ADC) are being used clinically as qualitative (DWI) and quantitative (ADC) indicators of disease presence, progression or response to treatment. Use of ADC as a robust quantitative biomarker with finite confidence intervals places additional requirements on Sites, Acquisition Devices and Protocols, Field Engineers, Scanner Operators (MR Technologists, Radiologists, Physicists and other Scientists), Image Analysts, Reconstruction Software and Image Analysis Tools. Additionally, due to the intrinsic dependence of measured ADC values on biophysical tissue properties, both the Profile Claims and the associated scan protocols (Section 3.6.2) are organ-specific. All of these are considered Actors involved in Activities of Acquisition Device Pre-delivery and Installation, Subject Handling, Image Data Acquisition, Reconstruction, Registration, ADC map generation, Quality Assurance (QA), Distribution, Analysis, and Interpretation. The requirements addressed in this Profile are focused on achieving ADC values with minimal systematic bias and measurement variability. DISCLAIMER: Technical performance of the MRI system can be assessed using a phantom having known diffusion properties, such as the QIBA DWI phantom. The clinical performance target is to achieve a 95% confidence interval for measurement of ADC with a variable precision depending on the organ being imaged and assuming adequate technical performance requirements are met. While in vivo DWI/ADC measurements have been performed throughout the human body, this Profile focused on four organ systems, namely brain, liver, prostate, and breast as having high clinical utilization of ADC with a sufficient level of statistical evidence to support the Profile Claims derived from the current peer-reviewed literature. In due time, new DWI technologies with proven greater performance levels, as well as more organ systems will be incorporated in future Profiles. This document is intended to help a variety of users: clinicians using this biomarker to aid patient management; imaging staff generating this biomarker; MRI system architects developing related products; purchasers of such products; and investigators designing clinical trials utilizing quantitative diffusion-based imaging endpoints. Note that this document only states requirements specific to DWI to achieve the claim, not requirements that pertain to clinical standard of care. Conforming to this Profile is secondary to proper patient care.

BCL-2 has been implicated in prostate cancer (PCa) progression and development of castration-resistant disease (CRPC); however, it remains unclear how the BCL-2- and AR-expressing PCa cell populations evolve across the PCa continuum, how AR molecularly regulates BCL-2 and whether BCL-2 represents a common therapeutic target in heterogeneous CRPC. Here we first show the selective induction of BCL-2 by AR pathway inhibitors (ARPIs). Vectra-based quantitative multiplex immunofluorescence (qmIF) and image mass cytometry (IMC) analyses with single-cell resolution in patient PCa and xenograft models reveal markedly increased BCL-2+ (AR+ or AR-) PCa cells in CRPC. Mechanistically, AR represses BCL-2 transcription through several AR binding sites and ARPIs relieve this repression. Therapeutic studies in cells, organoids and xenografts support BCL-2 as a shared vulnerability across diverse CRPC subtypes. A Phase Ib clinical trial (NCT03751436) combining enzalutamide and BCL-2 inhibitor venetoclax demonstrated reduced circulating tumor cells in responding patients. In summary, by integrating high-content single-cell level imaging analyses with mechanistic studies, extensive preclinical therapeutic experiments and a Phase Ib clinical trial, our studies herein elucidate the AR+/-BCL-2+/- PCa cell subpopulation dynamics and credentials BCL-2 as a vital therapeutic target in heterogeneous CRPC.