Automated Image Analysis Algorithms Research Articles

Topographical changes in extracellular matrix during skin fibrosis and recovery can be evaluated using automated image analysis algorithms.

Skin fibrosis is characterized by fibroblast activation and intradermal fat loss, resulting in excess deposition and remodeling of dermal extracellular matrix (ECM). The topography of the dominant ECM proteins, such as collagens, can indicate skin stiffness and remains understudied in evaluating fibrotic skin. Here, we adapted two different unbiased image analysis algorithms to define collagen topography and alignment in a genetically inducible and reversible Wnt activation fibrosis model. We demonstrated that Wnt-activated fibrotic skin has altered collagen fiber characteristics and a loss of collagen alignment, which were restored in the reversible model. This study highlights how unbiased algorithms can be used to analyze ECM topography, providing novel avenues to evaluate fibrotic skin onset, recovery, and treatment.

Abstract 3101: Developing a drug repurposing screen for head and neck squamous cell carcinoma using a novel c-Rel bioassay

Abstract Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. Approximately 890,000 new cases are diagnosed each year, while incidence continues to rise and is anticipated to increase by 30% by 2030. HNSCC occurs most often in men in their 50-60s, although the incidence among younger individuals is increasing. Current standard of care practices include surgical resection, followed by adjuvant radiation or chemoradiation. HNSCC tumors exhibit frequent mutation of CDKN2A (22% of tumors) and TP53 (72% of tumors). Additionally, two members of the TP53 gene family, TP63 and TP73, are frequently altered in HNSCC. TP63 encodes two major isoforms, ΔNp63 which lacks the main transcription activation domain and acts as a dominant-negative inhibitor of transactivation (TA), and TAp63 (contains a p53-like TA domain). ΔNp63 is overexpressed in a majority of HNSCC tumors. Our lab has reported ΔNp63α interacts with activated c-Rel (a nuclear factor-KB family member) in HNSCC, thereby promoting uncontrolled proliferation, a key alteration in the pathogenesis of cancers. Consistent with a role in growth regulation, ΔNp63α:c-Rel complexes bind a promoter motif and repress the cyclin-dependent kinase inhibitor p21WAF1 in both human HNSCCs and normal keratinocytes overexpressing ΔNp63α. The direct relationship between ΔNp63α and activated c-Rel is observed by strong nuclear co-localization in the proliferating compartment of primary head and neck SCC. Stimulation of HNSCC cells with TNFα results in the induction of the c-Rel oncoprotein that binds to ΔNp63, displacing and inactivating the tumor suppressor TAp73 from ΔNp63-TAp73 complexes. Using western blot analysis in human HNSCC cell lines, we confirmed that stimulation with TNFα enhances nuclear c-Rel localization. We then set out to design a high throughput screening bioassay for the purpose of evaluating compounds that can inhibit c-Rel accumulation in the nucleus under TNFα stimulation. By preventing activated c-Rel from interacting with ΔNp63α in the nucleus we aim to decrease uncontrolled proliferation and restore the tumor-suppressive functionality of the ΔNp63-TAp73 complex. A 384-well immunocytochemistry assay was developed using a confocal microscopy readout and an automated image analysis algorithm to quantify nuclear translocation. The optimized assay will be used to screen the NCATS collection of approved drugs and investigational oncology agents. Top candidates will undergo further investigation in vitro, ex vivo, and in vivo to explore the possibility of repurposing the small molecules for HNSCC therapeutics. Citation Format: Kristin Ann Altwegg, Kathryn E. King, Dvir Blivis, Ty C. Voss, Natalia J. Martinez, Wendy C. Weinberg, Mark J. Henderson. Developing a drug repurposing screen for head and neck squamous cell carcinoma using a novel c-Rel bioassay [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 3101.

Design and operation of a von Kármán reactor for droplet breakage experiments

The dispersion of an immiscible fluid in a turbulent liquid flow is a frequent occurrence in various natural and technical processes, with particular importance in the chemical, pharmaceutical, mining, petroleum, and food industries. Understanding the dynamics and breakup of liquid droplets is crucial in many scientific and engineering applications, as poor control and optimization of droplet systems results in significant financial losses annually. Although a theoretical background for describing droplet breakup exists, many assumptions still require experimental verification. Numerous mathematical models have been proposed to describe the rate coefficient of droplet breakup and child distribution functions. However, the validation and discrimination between models have been hindered by the lack of experimental data gathered under well-controlled and well characterized conditions. Thus, to validate the current models, novel equipment and methodology for optical droplet breakage research are required. In this work, a von Kármán swirling flow apparatus was designed and constructed to carry out optical based droplet breakage experiments under low-intensity, homogeneous turbulent flow. The methodology presented here describes the procedure for generating and controlling the size of the droplets being injected into the homogeneous turbulent flow field. The experiments involved introducing single droplets into the test section, using peanut oil to be the droplet phase and the continuous phase is water. Automated image analysis algorithms were utilized to determine breakage time, breakage probability, and child droplet size distribution for different turbulence intensities.

In vitro digestion properties and use of automatic image analysis to assess the quality of wheat bread enriched with whole faba bean (Vicia faba L.) flour and its protein-rich fraction

The trend of incorporating faba bean (Vicia faba L.) in breadmaking has been increasing, but its application is still facing technological difficulties. The objective of this study was to understand the influence of substituting the wheat flour (WF) with 10, 20, 30 and 40 % mass of whole bean flour (FBF) or 10 and 20 % mass of faba bean protein-rich fraction (FBPI) on the quality (volume, specific volume, density, colour, and texture), nutritional composition (total starch, free glucose, and protein contents), and kinetics of in vitro starch and protein digestibility (IVSD and IVPD, respectively) of the breads. Automated image analysis algorithm was developed to quantitatively estimate the changes in the crumb (i.e., air pockets) and crust (i.e., thickness) due to the use of FBF or FBPI as part of the partial substitution of wheat flour. Higher levels of both FBF and FBPI substitution were associated with breads having significant (p < 0.05) lower (specific) volume (at least 25 % reduction) and higher density (up to 35 %), increased brownness (up to 49 % and 78 % for crust and crumb respectively), and up to 2.3-fold increase in hardness. Result from the image analysis has provided useful insights on how FBF and FBPI affecting bread characteristics during baking such as loss of crumb expansion, decrease in air pocket expansion and increase in crust thickness. Overall, incorporation of FBF or FBPI in wheat bread were favourable in reducing the starch content and improving the protein content and IVPD of wheat bread. Since bread remains as a staple food due to its convenience, versatility and affordability for individuals and families on a budget, wheat bread enriched with faba bean could be a perfect food matrix to increase daily protein intake.

Quantitative investigation of sooting dynamics in droplet combustion using an automated image analysis algorithm

This paper reports an image analysis approach using a newly-developed open-source program to extract quantitative measurements of soot volume fraction (SVF) from digital video images of burning n-heptane droplets. The automated program developed in this work can analyze images of fixed and untethered droplets to quantify sooting dynamics. The images analyzed in the program were taken from experiments carried out in the Multi-user Droplet Combustion Apparatus (MDCA) onboard the International Space Station (ISS). In these experiments, video imaging of burning droplets was obtained using backlighting by a laser diode with a wavelength of 653 nm. The light was collimated before it passed through the droplet and soot-containing region, after which the light was then attenuated and projected onto the camera’s sensors. This technique facilitates the measurements of SVF based on the principles of the full field light extinction method (FFLEM). The measurements provide quantitative data that reveal the sooting dynamics of liquid fuels during droplet combustion processes.The analyses of a soot-attenuating image (ISS n-heptane, untethered droplet) at an instant during the burning show that the SVF distribution has a peak at the soot shell location. It then decreases due to soot oxidation when the location is further away from the burning droplet. Regarding temporal effects on the maximum SVF (SVFmax), results show that SVFmax first increases after the burning is initiated until a peak value is reached, after which SVFmax decreases. The SVFmax values identified in this study for n-heptane are quantitatively consistent with previously reported values for fiber-supported droplets and are reached relatively early in the burning history. n-Heptane images are also analyzed to show the effects of initial droplet sizes on the maximum soot volume fraction. Results show that SVFmax decreases with increasing initial droplet size, which is consistent with visual observations of less soot formed and dimmer flame brightness as Do increases.

Encapsulation and adhesion of nanoparticles as a potential biomarker for TNBC cells metastatic propensity

Metastasis is the main cause of cancer-related mortality; therefore, the ability to predict its propensity can remarkably affect survival rate. Metastasis development is predicted nowadays by lymph-node status, tumor size, histopathology, and genetic testing. However, all these methods may have inaccuracies, and some require weeks to complete. Identifying novel prognostic markers will open an essential source for risk prediction, possibly guiding to elevated patient treatment by personalized strategies. Cancer cell invasion is a critical step in metastasis. The cytoskeletal mechanisms used by metastatic cells for the invasion process are very similar to the utilization of actin cytoskeleton in the endocytosis process. In the current study, the adhesion and encapsulation efficiency of low-cost carboxylate-modified fluorescent nanoparticles by breast cancer cells with high (HM) and low metastatic potential (LM) have been evaluated; benign cells were used as control. Using high-content fluorescence imaging and analysis, we have revealed (within a short time of 1 h), that efficiency of nanoparticles adherence and encapsulation is sufficiently higher in HM cells compared to LM cells, while benign cells are not encapsulating or adhering the particles during experiment time at all. We have utilized custom-made automatic image analysis algorithms to find quantitative co-localization (Pearson’s coefficients) of the nanoparticles with the imaged cells. The method proposed here is straightforward; it does not require especial equipment or expensive materials nor complicated cell manipulations, it may be potentially applicable for various cells, including patient-derived cells. Effortless and quantitative determination of the metastatic likelihood has the potential to be performed using patient-specific biopsy/surgery sample, which will directly influence the choice of protocols for cancer patient’s treatment and, as a result, increase their life expectancy.

Evaluation of reproducible cryogel preparation based on automated image analysis using deep learning.

Cryogels represent a class of porous sponge-like materials possessing unique properties including high-fidelity reproduction of tissue structure and maximized permeability. Their architecture is mainly based on an interconnected network of macropores that provides sufficient stability while allowing the movement of substances through the material. In most cryogel applications, the pore size is very important, especially when the material is used as a 3D scaffold for tissue culture, applied as a filter, or utilized as a membrane. In this study, poly(dimethylacrylamide-co-2-hydroxyethyl methacrylate) cryogels have been prepared by two preparation methods to investigate the reproducibility of homogeneous pore structures and pore sizes. Automated image analysis algorithms were developed to rapidly evaluate cryogel pore sizes based on scanning electron microscopy (SEM) images. The quantification approach contained a unique combination of classical and deep learning-based algorithms. To validate the accuracy of the two models, we compared the results obtained from automated SEM image analysis with those from manual pore size determinations and mercury intrusion porosimetry (MIP) measurements. Effect sizes were calculated to compare the results from manual and automated pore size measurements for the cryogel reproducibility series. 81% of the values obtained revealed only trivial differences, which strongly suggests that automated image analysis can reliably substitute the manual evaluation of cryogel pore sizes. The use of an adapted reactor setup yielded cryogels with heterogeneous morphologies in the absence of recognizable pore structures. With the conventional cryogel preparation using plastic syringes, the obtained cryogels represented highly reproducible morphologies and pore sizes in the range between 17 and 22 μm. Calculated effect sizes within the cryogel replicate series revealed only trivial differences between the obtained pore sizes in 83.5% or 99.4% of the data (classical approach and deep learning-based approach, respectively).

Age-dependent changes in epidermal architecture explored using an automated image analysis algorithm on in vivo reflectance confocal microscopy images.

Reflectance confocal microscopy (RCM) allows for real-time in vivo visualization of the epidermis at the cellular level noninvasively. Parameters relating to tissue architecture can be extracted from RCM images, however, analysis of such images requires manual identification of cells to derive these parameters, which can be time-consuming and subject to human error, highlighting the need for an automated cell identification method. First, the region-of-interest (ROI) containing cells needs to be identified, followed by the identification of individual cells within the ROI. To perform this task, we use successive applications of Sato and Gabor filters. The final step is post-processing improvement of cell detection and removal of size outliers. The proposed algorithm is evaluated on manually annotated real data. It is then applied to 5345 images to study the evolution of epidermal architecture in children and adults. The images were acquired on the volar forearm of healthy children (3 months to 10 years) and women (25-80 years), and on the volar forearm and cheek of women (40-80 years). Following the identification of cell locations, parameters such as cell area, cell perimeter, and cell density are calculated, as well as the probability distribution of the number of nearest neighbors per cell. The thicknesses of the Stratum Corneum and supra-papillary epidermis are also calculated using a hybrid deep-learning method. Epidermal keratinocytes are significantly larger (area and perimeter) in the granular layer than in the spinous layer and they get progressively larger with a child's age. Skin continues to mature dynamically during adulthood, as keratinocyte size continues to increase with age on both the cheeks and volar forearm, but the topology and cell aspect ratio remain unchanged across different epidermal layers, body sites, and age. Stratum Corneum and supra-papillary epidermis thicknesses increase with age, at a faster rate in children than in adults. The proposed methodology can be applied to large datasets to automate image analysis and the calculation of parameters relevant to skin physiology. These data validate the dynamic nature of skin maturation during childhood and skin aging in adulthood.

Unpaired mesh-to-image translation for 3D fluorescent microscopy images of neurons.

While Generative Adversarial Networks (GANs) can now reliably produce realistic images in a multitude of imaging domains, they are ill-equipped to model thin, stochastic textures present in many large 3D fluorescent microscopy (FM) images acquired in biological research. This is especially problematic in neuroscience where the lack of ground truth data impedes the development of automated image analysis algorithms for neurons and neural populations. We therefore propose an unpaired mesh-to-image translation methodology for generating volumetric FM images of neurons from paired ground truths. We start by learning unique FM styles efficiently through a Gramian-based discriminator. Then, we stylize 3D voxelized meshes of previously reconstructed neurons by successively generating slices. As a result, we effectively create a synthetic microscope and can acquire realistic FM images of neurons with control over the image content and imaging configurations. We demonstrate the feasibility of our architecture and its superior performance compared to state-of-the-art image translation architectures through a variety of texture-based metrics, unsupervised segmentation accuracy, and an expert opinion test. In this study, we use 2 synthetic FM datasets and 2 newly acquired FM datasets of retinal neurons.

Reliability of Retinal Layer Annotation with a Novel, High-Resolution Optical Coherence Tomography Device: A Comparative Study.

Optical coherence tomography (OCT) enables in vivo diagnostics of individual retinal layers in the living human eye. However, improved imaging resolution could aid diagnosis and monitoring of retinal diseases and identify potential new imaging biomarkers. The investigational high-resolution OCT platform (High-Res OCT; 853 nm central wavelength, 3 µm axial-resolution) has an improved axial resolution by shifting the central wavelength and increasing the light source bandwidth compared to a conventional OCT device (880 nm central wavelength, 7 µm axial-resolution). To assess the possible benefit of a higher resolution, we compared the retest reliability of retinal layer annotation from conventional and High-Res OCT, evaluated the use of High-Res OCT in patients with age-related macular degeneration (AMD), and assessed differences of both devices on subjective image quality. Thirty eyes of 30 patients with early/intermediate AMD (iAMD; mean age 75 ± 8 years) and 30 eyes of 30 age-similar subjects without macular changes (62 ± 17 years) underwent identical OCT imaging on both devices. Inter- and intra-reader reliability were analyzed for manual retinal layer annotation using EyeLab. Central OCT B-scans were graded for image quality by two graders and a mean-opinion-score (MOS) was formed and evaluated. Inter- and intra-reader reliability were higher for High-Res OCT (greatest benefit for inter-reader reliability: ganglion cell layer; for intra-reader reliability: retinal nerve fiber layer). High-Res OCT was significantly associated with an improved MOS (MOS 9/8, Z-value = 5.4, p < 0.01) mainly due to improved subjective resolution (9/7, Z-Value 6.2, p < 0.01). The retinal pigment epithelium drusen complex showed a trend towards improved retest reliability in High-Res OCT in iAMD eyes but without statistical significance. Improved axial resolution of the High-Res OCT benefits retest reliability of retinal layer annotation and improves perceived image quality and resolution. Automated image analysis algorithms could also benefit from the increased image resolution.

Image analysis of cutaneous melanoma histology: a systematic review and meta-analysis

The current subjective histopathological assessment of cutaneous melanoma is challenging. The application of image analysis algorithms to histological images may facilitate improvements in workflow and prognostication. To date, several individual algorithms applied to melanoma histological images have been reported with variations in approach and reported accuracies. Histological digital images can be created using a camera mounted on a light microscope, or through whole slide image (WSI) generation using a whole slide scanner. Before any such tool could be integrated into clinical workflow, the accuracy of the technology should be carefully evaluated and summarised. Therefore, the objective of this review was to evaluate the accuracy of existing image analysis algorithms applied to digital histological images of cutaneous melanoma.Database searching of PubMed and Embase from inception to 11th March 2022 was conducted alongside citation checking and examining reports from organisations. All studies reporting accuracy of any image analysis applied to histological images of cutaneous melanoma, were included. The reference standard was any histological assessment of haematoxylin and eosin-stained slides and/or immunohistochemical staining. Citations were independently deduplicated and screened by two review authors and disagreements were resolved through discussion. The data was extracted concerning study demographics; type of image analysis; type of reference standard; conditions included and test statistics to construct 2 × 2 tables. Data was extracted in accordance with our protocol and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Diagnostic Test Accuracy (PRISMA-DTA) Statement. A bivariate random-effects meta-analysis was used to estimate summary sensitivities and specificities with 95% confidence intervals (CI). Assessment of methodological quality was conducted using a tailored version of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. The primary outcome was the pooled sensitivity and specificity of image analysis applied to cutaneous melanoma histological images. Sixteen studies were included in the systematic review, representing 4,888 specimens. Six studies were included in the meta-analysis. The mean sensitivity and specificity of automated image analysis algorithms applied to melanoma histological images was 90% (CI 82%, 95%) and 92% (CI 79%, 97%), respectively. Based on limited and heterogeneous data, image analysis appears to offer high accuracy when applied to histological images of cutaneous melanoma. However, given the early exploratory nature of these studies, further development work is necessary to improve their performance.

33218 Advantages of standardization of dermoscopic imaging by leveraging the DICOM standard

With the rise of digital dermoscopy, databases of dermoscopic images of cutaneous conditions are growing every day. However, the lack of standardization yields numerous problems, such as incompatible databases, and missing information. Even more troublesome is the lack of standardization in color rendering of dermoscopic images, resulting in significant color variability between images captured with different systems. Such color variability may negatively influence confidence and quality of diagnosis and reliability of automated image analysis algorithms.

EP11.02-002 A Comparative Study of PD-L1 Scoring: Humans versus AI

Immunotherapy with PD-1/PD-L1 inhibitors has revolutionized the treatment of non-small cell lung cancer (NSCLC). In clinical practice, PD-L1 expression by immunohistochemistry has been implemented as a companion or complementary diagnostic for anti-PD-1/PD-L1 agents. A widely adopted measure of PD-L1 expression in NSCLC is the tumor proportion score (TPS), defined as the ratio of positive membranous stained tumor cells and the total number of viable tumor cells. Several automatic image analysis algorithms for determining the TPS on the whole slide images (WSI) of NSCLC have been developed recently.

Automated detection and quantification of Enchytraeus crypticus (Oligochaeta: Enchytraeidae) in tropical artificial soil using image analysis.

The effects of toxic substance in soil matrices are evaluated by assessing adult worm survival and reproduction. Throughout the test, hundreds of juvenile potworms can be found. The current method for Enchytraeus crypticus quantification in soil samples is a laborious and time-consuming procedure that involves manual counting. The present work proposes a method for quick and reliable counting of E. crypticus by using an automated image analysis algorithm applied to soil images. Comparisons between automated and manual methods conducted in double-blind trials involving a large, routine batch of tropical artificial soil samples revealed no statistically significant differences for a wide range of worm densities. The proposed method overcomes time-consuming counts in manual methods and is suited to be deployed routinely for soil toxicity studies involving large batches of samples.

Time Since Stroke Onset, Quantitative Collateral Score, and Functional Outcome After Endovascular Treatment for Acute Ischemic Stroke.

Background and ObjectivesIn patients with ischemic stroke undergoing endovascular treatment (EVT), time to treatment and collateral status are important prognostic factors and may be correlated. We aimed to assess the relation between time to CT angiography (CTA) and a quantitatively determined collateral score and to assess whether the collateral score modified the relation between time to recanalization and functional outcome.MethodsWe analyzed data from patients with acute ischemic stroke included in the Multicenter Randomized Controlled Trial of Endovascular Treatment for Acute Ischemic Stroke Registry between 2014 and 2017, who had a carotid terminus or M1 occlusion and were treated with EVT within 6.5 hours of symptom onset. A quantitative collateral score (qCS) was determined from baseline CTA using a validated automated image analysis algorithm. We also determined a 4-point visual collateral score (vCS). Multivariable regression models were used to assess the relations between time to imaging and the qCS and between the time to recanalization and functional outcome (90-day modified Rankin Scale score). An interaction term (time to recanalization × qCS) was entered in the latter model to test whether the qCS modifies this relation. Sensitivity analyses were performed using the vCS.ResultsWe analyzed 1,813 patients. The median time from symptom onset to CTA was 91 minutes (interquartile range [IQR] 65–150 minutes), and the median qCS was 49% (IQR 25%–78%). Longer time to CTA was not associated with the log-transformed qCS (adjusted β per 30 minutes, 0.002, 95% CI −0.006 to 0.011). Both a higher qCS (adjusted common odds ratio [acOR] per 10% increase: 1.06, 95% CI 1.03–1.09) and shorter time to recanalization (acOR per 30 minutes: 1.17, 95% CI 1.13–1.22) were independently associated with a shift toward better functional outcome. The qCS did not modify the relation between time to recanalization and functional outcome (p for interaction: 0.28). Results from sensitivity analyses using the vCS were similar.DiscussionIn the first 6.5 hours of ischemic stroke caused by carotid terminus or M1 occlusion, the collateral status is unaffected by time to imaging, and the benefit of a shorter time to recanalization is independent of baseline collateral status.

P-094 Fundamental understanding of sperm motion in viscoelastic media

Abstract Study question How does viscosity influence the flagellar beating behaviour of free-swimming bull, mouse, and human sperm? Summary answer Sperm flagellar beating behaviour exhibits a transition from an irregular three-dimensional (3D) beating at 5 mPa·s to an organized two-dimensional (2D) waveform at 20 mPa·s. What is known already Sperm migrate in a complex viscoelastic environment through the female reproductive tract. The viscoelastic properties of the oviductal fluid significantly influence the progressive motility of sperm, acting as one of the key guidance mechanisms in vivo. However, the biomechanics of sperm flagellar activity in response to varying viscosity of the oviductal fluid is poorly understood. Understanding sperm flagellar behaviour in physiologically relevant environments is crucial to understanding reproduction and may help to describe unknown causes of infertility. Lack of high-speed high-resolution imaging techniques and automated image-analysis capabilities have been the main barriers to fully describe the flagellar beating behaviour. Study design, size, duration We used a custom-built high-speed high-resolution dark-field microscopy platform to resolve the flagellar dynamics of human, bull, and mouse sperm near surfaces in viscoelastic media ranging in viscosity from 1 to 250 mPa·s. The imaging system includes an automated image analysis algorithm to quantify sperm flagellar waveform and motility characteristics by extracting the flagellar centreline, reconstructing the waveform and calculating tangent-angle profiles. 20 sperm from 3 different bull, mice and humans were analyzed. Participants/materials, setting, methods Bull, mouse, and human sperm were used in this study. In each experiment, a diluted sperm sample in a buffer supplemented with methylcellulose was used and free-swimming sperm were imaged using dark-field microscopy at 200 frames per second. An automated image analysis algorithm was used to extract sperm flagellar centreline and Proper Orthogonal Decomposition (POD) was then used to study sperm flagellar waveform. Statistical analysis was performed using one-way ANOVA. Main results and the role of chance The reconstructed flagellar beating pattern was different for sperm swimming in low and high-viscosity media. Bull sperm exhibited a lower flagellar beating amplitude along the end piece when swimming in a high-viscosity media, a potential energy-efficient strategy to navigate a high viscosity fluid. The first two dominant POD modes (shape modes) describe more than 90% of the beating pattern for all species. Bull sperm exhibited a transition mode with irregular loops in 5 mPa·s buffer, but the flagellar shape cycle created an organised repetitive circular cycle in 1 mPa.s (3D beating) buffer and at viscosities higher than 5 mPa·s (2D beating). Human sperm also indicated a similar behaviour but with the transition happening at higher viscosities. Mouse sperm in high-viscosity media had a lower flagellar beating amplitude across the principal piece and higher beating amplitude across the end piece. The flagellar shape cycle in mouse sperm showed a periodic flagellar beating behaviour at high-viscosities (&amp;gt;20 mPa·s), but a shape cycle with distorted loops at lower viscosities. Our results showed in quantitative detail that increasing viscosity alters sperm flagellar beating pattern, and how sperm migration behaviour in low viscosity media can be distinct from their swimming behaviour in vivo. Limitations, reasons for caution A more comprehensive study of sperm motility parameters such as curvilinear velocity, average path velocity and straight line velocity with a larger sample size is required to fully characterise sperm swimming behaviour as a function of viscosity. Wider implications of the findings The increasing viscosity of the oviductal fluid regulates the sperm flagellar beating behaviour to switch from a 3D swimming behaviour with irregular shape cycles at lower viscosities to a 2D slithering mode with repetitive circular shape cycles at higher viscosities to achieve a more energy-efficient beating pattern for navigation. Trial registration number Not applicable

Automated staining analysis in digital cytopathology and applications.

The progress of digital pathology in recent years has been an opportunity for the development of automated image analysis algorithms for quantitative measurements and computer aided diagnosis. With those new methods comes the need for high staining quality and reproducibility, as image analysis tools are typically more sensible to slight stain variations than trained pathologists. This article presents a method for the automated analysis of cytology slides stains specifically adapted to the challenges encountered in digital cytopathology. In particular, the variety of cell types in cytology slides, the 3D distribution of the cellular material, the presence of superposed cells and the need for independent analysis of sub-cellular compartments are addressed. The proposed method is applied to the quantification of staining variations for quality control, resulting from changes in the staining protocol such as reagent immersion time or a reagent change. Another demonstrated application is the selection of staining protocol parameters that maximize the visible details in nucleus. Finally the analysis pipeline is also used to compare different stain normalization algorithms on digital cytology slides. Code available at: https://gitlab.com/vitadx/articles/automated_staining_analysis.

Automatic and Label-Free Analysis of the Microstructure Feature Differences Between Normal Brain Tissue, Low-Grade, and High-Grade Gliomas Using the Combination of Multiphoton Microscopy and Image Analysis

Accurate intraoperative identification of gliomas is of utmost importance. This task often remains a challenge for the pathologist and neurosurgeon because of the absence of full intraoperative microstructure feature details of the tumor. Here, multiphoton microscopy (MPM), based on second harmonic generation (SHG) and two-photon excited fluorescence (TPEF), is applied for label-free detecting the microstructure feature differences between normal brain tissue, low-grade, and high-grade gliomas. MPM can not only capture the difference of their qualitative microstructure features such as increased cellularity, nuclear atypia, microvascular proliferation, and necrosis that are significant for diagnosing and grading of glioma, but also visualize some additional features such as collagen deposition that cannot be seen by conventional methods. In addition, automated image analysis algorithms are developed to automatically and accurately calculate the quantitative diagnostic features: collagen content, the number and area of nuclei to further quantitatively analyze the microstructure features difference of collagen deposition, cellularity, and nuclear atypia between normal brain tissue, low-grade, and high-grade gliomas. With the development of two-photon fiberscope, combined MPM and image processing techniques may become an imaging tool for assisting intraoperatively diagnosing and grading gliomas.

Single cell phenotyping of PDL1 and HLA1 on circulating tumor cells (CTC) in clear cell renal cell carcinoma (ccRCC) on systemic treatment with immunotherapy (IO) and vascular endothelial growth factor receptor tyrosine kinase inhibitors (TKI).

381 Background: Single agent or combination regimens using different IO and TKI agents have dramatically improved survival of patients (pt) with advanced ccRCC. Nevertheless, selecting optimal combination and sequencing of treatments remains challenging given the current absence of predictive biomarkers. Considering substantial disease heterogeneity and tumor clonal evolution, CTCs could provide a more comprehensive and longitudinal assessment of disease and response to treatment when compared to single site biopsy. In this study we explore changes in CTC characteristics in correlation with pt’s response (Resp) to treatment and progression (PD). Methods: 152 blood sample time points from 44 ccRCC pts (mean=3.5 sample/pt, range= 1-9) were included. An automated microfluidic platform using exclusion-based sample technology was employed for high sensitivity enrichment of RCC CTCs using EpCAM and CAIX antibodies. High-specificity CTC identification was achieved with positive staining for pCK or CAXII, and negative staining for CD45, CD34 and CD66b. Single cell phenotyping of PDL1 and HLA1 expression on each CTC was quantified with automated image analysis algorithms followed by manual visual QA of the putative CTCs. Cellular-level expression of PDL1 and HLA1 were compared within treatment-response groupings, using Wilcoxon rank-sum tests (Table). Results: Pts were 70% male, 93% Caucasian, 51% de novo metastatic, 98% received systemic treatment. CTC samples were collected at baseline (12) or while on treatment with IO (71), TKI (55), or IO/TKI (14). Across treatments, the number of CTCs increased from Resp to PD but this trend was not statistically significant. PDL1 expression was higher at PD compared to Resp on IO and IO/TKI but not significantly different on TKI. HLA1 expression was higher at PD compared to Resp on IO and TKI but not significantly different on IO/TKI. Average CTC PD-L1 expression was higher at Resp to IO compared to baseline. Conclusions: Single cell phenotyping of PDL1 and HLA1 were done at Resp compared to PD time points on IO and/or TKI to identify potential mechanisms of resistance. Further evaluation of these preliminary results in prospective trials is ongoing to advance new predictive biomarkers for ccRCC.[Table: see text]

Abstract WMP92: Time Since Stroke Onset, Quantitative Collateral Score And Functional Outcome After Endovascular Treatment For Acute Ischemic Stroke - Results From The Mr Clean Registry.

Background: In patients with ischemic stroke undergoing endovascular treatment (EVT), time to treatment and collateral status are important prognostic factors. We assessed the relation between time to CT angiography (CTA) and collateral status. Furthermore, we assessed whether collateral status modifies the relationship between onset to recanalization time (ORT) and functional outcome. Methods: From the prospective, multicenter MR CLEAN Registry, we included patients with acute ischemic stroke, who had a carotid terminus or M1 occlusion and were treated with EVT in the Netherlands within 6.5 hours of symptom onset. A quantitative collateral score (qCS) was assessed from baseline CTA using an automated image analysis algorithm (Strokeviewer; Nico.lab). Multivariable regression models were used to assess the relationship between time to imaging and the qCS and between ORT and functional outcome (90-day modified Rankin Scale score). An interaction term (ORT * qCS) was introduced in the latter model to test whether qCS modifies this relation. Results: We analysed 1813 patients. The median time from symptom onset to CTA was 91 minutes [IQR: 56-150] and the median qCS was 49% [IQR: 25-79]. Longer time to CTA was not associated with qCS (β per 30 minutes, 0.001 [-0.008 - 0.010]). Both a higher qCS (acOR per 10% increase, 1.07 [1.03-1.10], p&lt;0.001) and shorter ORT (acOR per 30 minutes, 1.17 [1.13-1.21], p&lt;0.001) were independently associated with a shift towards better functional outcome. The qCS did not modify the relationship between ORT and functional outcome (p for interaction: 0.28; Figure). Conclusions: In patients with ischemic stroke caused by carotid-terminus or M1 occlusion presenting within 6.5 hours of symptom onset, the collateral status is unaffected by time to CTA and the benefit of a shorter ORT is similar across the entire range of collateral scores.