Segmenting overlapping cell nuclei in digital histopathology images

Scaling up cell-counting efforts in neuroscience through semi-automated methods

Quantifying how the cellular composition of brain regions vary across development, aging, sex, and disease, is crucial in experimental neuroscience, and the accuracy of different counting methods is continuously debated. Due to the tedious nature of most counting procedures, studies are often restricted to one or a few brain regions. Recently, there have been considerable methodological advances in combining semi-automated feature extraction with brain atlases for cell quantification. Such methods hold great promise for scaling up cell-counting efforts. However, little focus has been paid to how these methods should be implemented and reported to support reproducibility. Here, we provide an overview of practices for conducting and reporting cell counting in mouse and rat brains, showing that critical details for interpretation are typically lacking. We go on to discuss how novel methods may increase efficiency and reproducibility of cell counting studies. Lastly, we provide practical recommendations for researchers planning cell counting.

Formulated Chinese medicine Shaoyao Gancao Tang reduces NLRP1 and NLRP3 in Alzheimer's disease cell and mouse models for neuroprotection and cognitive improvement

Amyloid β (Aβ) plays a major role in the neurodegeneration of Alzheimer’s disease (AD). The accumulation of misfolded Aβ causes oxidative stress and inflammatory damage leading to apoptotic cell death. Traditional Chinese herbal medicine (CHM) has been widely used in treating neurodegenerative diseases by reducing oxidative stress and neuroinflammation. We examined the neuroprotective effect of formulated CHM Shaoyao Gancao Tang (SG-Tang, made of Paeonia lactiflora and Glycyrrhiza uralensis at 1:1 ratio) in AD cell and mouse models. In Aβ-GFP SH-SY5Y cells, SG-Tang reduced Aβ aggregation and reactive oxygen species (ROS) production, as well as improved neurite outgrowth. When the Aβ-GFP-expressing cells were stimulated with conditioned medium from interferon (IFN)-γ-activated HMC3 microglia, SG-Tang suppressed expressions of inducible nitric oxide synthase (iNOS), NLR family pyrin domain containing 1 (NLRP1) and 3 (NLRP3), tumor necrosis factor (TNF)-α, interleukin (IL)-1β and IL-6, attenuated caspase-1 activity and ROS production, and promoted neurite outgrowth. In streptozocin-induced hyperglycemic APP/PS1/Tau triple transgenic (3×Tg-AD) mice, SG-Tang also reduced expressions of NLRP1, NLRP3, Aβ and Tau in hippocampus and cortex, as well as improved working and spatial memories in Y maze and Morris water maze. Collectively, our results demonstrate the potential of SG-Tang in treating AD by moderating neuroinflammation.

Multiparametric biophysical profiling of red blood cells in malaria infection

Biophysical separation promises label-free, less-invasive methods to manipulate the diverse properties of live cells, such as density, magnetic susceptibility, and morphological characteristics. However, some cellular changes are so minute that they are undetectable by current methods. We developed a multiparametric cell-separation approach to profile cells with simultaneously changing density and magnetic susceptibility. We demonstrated this approach with the natural biophysical phenomenon of Plasmodium falciparum infection, which modifies its host erythrocyte by simultaneously decreasing density and increasing magnetic susceptibility. Current approaches have used these properties separately to isolate later-stage infected cells, but not in combination. We present biophysical separation of infected erythrocytes by balancing gravitational and magnetic forces to differentiate infected cell stages, including early stages for the first time, using magnetic levitation. We quantified height distributions of erythrocyte populations-27 ring-stage synchronized samples and 35 uninfected controls-and quantified their unique biophysical signatures. This platform can thus enable multidimensional biophysical measurements on unique cell types.

System for quantitative evaluation of DAB&H-stained breast cancer biopsy digital images (CHISEL)

This study presents CHISEL (Computer-assisted Histopathological Image Segmentation and EvaLuation), an end-to-end system capable of quantitative evaluation of benign and malignant (breast cancer) digitized tissue samples with immunohistochemical nuclear staining of various intensity and diverse compactness. It stands out with the proposed seamless segmentation based on regions of interest cropping as well as the explicit step of nuclei cluster splitting followed by a boundary refinement. The system utilizes machine learning and recursive local processing to eliminate distorted (inaccurate) outlines. The method was validated using two labeled datasets which proved the relevance of the achieved results. The evaluation was based on the IISPV dataset of tissue from biopsy of breast cancer patients, with markers of T cells, along with Warwick Beta Cell Dataset of DAB&H-stained tissue from postmortem diabetes patients. Based on the comparison of the ground truth with the results of the detected and classified objects, we conclude that the proposed method can achieve better or similar results as the state-of-the-art methods. This system deals with the complex problem of nuclei quantification in digitalized images of immunohistochemically stained tissue sections, achieving best results for DAB&H-stained breast cancer tissue samples. Our method has been prepared with user-friendly graphical interface and was optimized to fully utilize the available computing power, while being accessible to users with fewer resources than needed by deep learning techniques.

Evaluation of digital image analysis as a supportive tool for the stratification of head and neck vascular anomalies

Background

The histological differentiation of individual types of vascular anomalies (VA), such as lymphatic malformations (LM), hemangioma (Hem), paraganglioma (PG), venous malformations (VeM), arteriovenous malformations (AVM), pyogenic granulomas (GP), and (not otherwise classified) vascular malformations (VM n.o.c.) is frequently difficult due to the heterogeneity of these anomalies. The aim of the study was to evaluate digital image analysis as a method for VA stratification

Methods

A total of 40 VA tissues were examined immunohistologically using a selection of five vascular endothelial-associated markers (CD31, CD34, CLDN5, PDPN, VIM). The staining results were documented microscopically followed by digital image analyses based quantification of the candidate-marker-proteins using the open source program ImageJ/Fiji.

Results

Differences in the expression patterns of the candidate proteins could be detected particularly when deploying the quotient of the quantified immunohistochemical signal values. Deploying signal marker quotients, LM could be fully distinguished from all other tested tissue types. GP achieved stratification from LM, Hem, VM, PG and AVM tissues, whereas Hem, PG, VM and AVM exhibited significantly different signal marker quotients compared with LM and GP tissues.

Conclusion

Although stratification of different VA from each other was only achieved in part with the markers used, the results of this study strongly support the usefulness of digital image analysis for the stratification of VA. Against the background of upcoming new diagnostic techniques involving artificial intelligence and deep (machine) learning, our data serve as a paradigm of how digital evaluation methods can be deployed to support diagnostic decision making in the field of VAs.

Tuft Cell Formation Reflects Epithelial Plasticity in Pancreatic Injury: Implications for Modeling Human Pancreatitis

Chronic pancreatitis, a known risk factor for the development of pancreatic ductal adenocarcinoma (PDA), is a serious, widespread medical condition characterized by inflammation, fibrosis, and acinar to ductal metaplasia (ADM). ADM is a cell type transdifferentiation event where pancreatic acinar cells become ductal-like under conditions of injury or oncogenic mutation. Here, we show that chronic pancreatitis and ADM in genetically wild type mice results in the formation of a significant population of chemosensory tuft cells. Transcriptomic analyses of pancreatitis tuft cells identify expression of inflammatory mediators, consistent with a role for tuft cells in injury progression and/or resolution. Though similar to tuft cell populations in other organs and disease systems, we identified a number of key differences that suggest context-specific tuft cell functions. We evaluated seven different mouse strains for tuft cell formation in response to chronic injury and identified significant heterogeneity reflecting varying proclivity for epithelial plasticity between strains. These results have interesting implications in the role of epithelial plasticity and heterogeneity in pancreatitis and highlight the importance of mouse strain selection when modeling human disease.

Active poly-GA vaccination prevents microglia activation and motor deficits in a C9orf72 mouse model

The C9orf72 repeat expansion is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and/or frontotemporal dementia (FTD). Non-canonical translation of the expanded repeat results in abundant poly-GA inclusion pathology throughout the CNS. (GA)149 -CFP expression in mice triggers motor deficits and neuroinflammation. Since poly-GA is transmitted between cells, we investigated the therapeutic potential of anti-GA antibodies by vaccinating (GA)149 -CFP mice. To overcome poor immunogenicity, we compared the antibody response of multivalent ovalbumin-(GA)10 conjugates and pre-aggregated carrier-free (GA)15 . Only ovalbumin-(GA)10 immunization induced a strong anti-GA response. The resulting antisera detected poly-GA aggregates in cell culture and patient tissue. Ovalbumin-(GA)10 immunization largely rescued the motor function in (GA)149 -CFP transgenic mice and reduced poly-GA inclusions. Transcriptome analysis showed less neuroinflammation in ovalbumin-(GA)10 -immunized poly-GA mice, which was corroborated by semiquantitative and morphological analysis of microglia/macrophages. Moreover, cytoplasmic TDP-43 mislocalization and levels of the neurofilament light chain in the CSF were reduced, suggesting neuroaxonal damage is reduced. Our data suggest that immunotherapy may be a viable primary prevention strategy for ALS/FTD in C9orf72 mutation carriers.

Automated Individualization of Size-Varying and Touching Neurons in Macaque Cerebral Microscopic Images

In biomedical research, cell analysis is important to assess physiological and pathophysiological information. Virtual microscopy offers the unique possibility to study the compositions of tissues at a cellular scale. However, images acquired at such high spatial resolution are massive, contain complex information, and are therefore difficult to analyze automatically. In this article, we address the problem of individualization of size-varying and touching neurons in optical microscopy two-dimensional (2-D) images. Our approach is based on a series of processing steps that incorporate increasingly more information. (1) After a step of segmentation of neuron class using a Random Forest classifier, a novel min-max filter is used to enhance neurons' centroids and boundaries, enabling the use of region growing process based on a contour-based model to drive it to neuron boundary and achieve individualization of touching neurons. (2) Taking into account size-varying neurons, an adaptive multiscale procedure aiming at individualizing touching neurons is proposed. This protocol was evaluated in 17 major anatomical regions from three NeuN-stained macaque brain sections presenting diverse and comprehensive neuron densities. Qualitative and quantitative analyses demonstrate that the proposed method provides satisfactory results in most regions (e.g., caudate, cortex, subiculum, and putamen) and outperforms a baseline Watershed algorithm. Neuron counts obtained with our method show high correlation with an adapted stereology technique performed by two experts (respectively, 0.983 and 0.975 for the two experts). Neuron diameters obtained with our method ranged between 2 and 28.6 μm, matching values reported in the literature. Further works will aim to evaluate the impact of staining and interindividual variability on our protocol.

Segmentation of Heavily Clustered Nuclei from Histopathological Images

Automated cell nucleus segmentation is the key to gain further insight into cell features and functionality which support computer-aided pathology in early diagnosis of diseases such as breast cancer and brain tumour. Despite considerable advances in automated segmentation, it still remains a challenging task to split heavily clustered nuclei due to intensity variations caused by noise and uneven absorption of stains. To address this problem, we propose a novel method applicable to variety of histopathological images stained for different proteins, with high speed, accuracy and level of automation. Our algorithm is initiated by applying a new locally adaptive thresholding method on watershed regions. Followed by a new splitting technique based on multilevel thresholding and the watershed algorithm to separate clustered nuclei. Finalized by a model-based merging step to eliminate oversegmentation and a model-based correction step to improve segmentation results and eliminate small objects. We have applied our method to three image datasets: breast cancer stained for hematoxylin and eosin (H&E), Drosophila Kc167 cells stained for DNA to label nuclei, and mature neurons stained for NeuN. Evaluated results show our method outperforms the state-of-the-art methods in terms of accuracy, precision, F1-measure, and computational time.

Comparison of Blue and White Lamp Light with Sunlight for Daylight-Mediated, 5-ALA Photodynamic Therapy, in vivo

Daylight-mediated photodynamic therapy (d-PDT) as a treatment for actinic keratosis (AK) is an increasingly common technique due to a significant reduction in pain, leading to better patient tolerability. While past studies have looked at different light sources and delivery methods, this study strives to provide equivalent PpIX-weighted light doses with the hypothesis that artificial light sources could be equally as effective as natural sunlight if their PpIX-weighted fluences were equalized. Normal mouse skin was used as the model to compare blue LED light, metal halide white light and natural sunlight, with minimal incubation time between topical ALA application and the onset of light delivery. A total PpIX-weighted fluence of 20 J_eff cm^-2 was delivered over 2 h, and the efficacy of response was quantified using three acute bioassays for PDT damage: PpIX photobleaching, Stat3 crosslinking and quantitative histopathology. These bioassays indicated blue light was slightly inferior to both sunlight and white light, but that the latter two were not significantly different. The results suggest that metal halide white light could be a reasonable alternative to daylight PDT, which should allow a more controlled treatment that is independent of weather and yet should have similar response rates with limited pain during treatment.