Toxicologic Pathology最新文献

The Golden Syrian hamster is a well-characterized rodent model for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)-associated pneumonia. We sought to characterize the pulmonary disease course during SARS-CoV-2 infection (strain USA-WA1/2020) in the hamster model using micro-computed tomography (micro-CT) and compare radiologic observations with histopathologic findings. We observed a range of radiologic abnormalities, including ground glass opacities (GGOs), consolidations, air bronchograms, and pneumomediastinum. The appearance, distribution, and progression of these abnormalities in hamsters were similar to those observed in the lungs of coronavirus disease 2019 (COVID-19) patients by clinical CT and chest X-rays, and correlated with clinical signs and weight loss during the course of disease. Histopathological analysis of infected hamsters revealed lung pathology characteristic of COVID-19 pneumonia, and we observed a strong association between CT and histopathologic scorings. We also analyzed accumulation of air in the thoracic cavity by both manual and automated threshold-based segmentation and found that automated analysis significantly decreases the time needed for data analysis. Data presented here demonstrate that micro-CT imaging can be a major tool in preclinical investigative studies using animal models by providing early and detailed assessment of disease severity and outcomes.

Before the COVID-19 pandemic, digital pathology was increasingly used in veterinary education, diagnostics, and research. The pandemic accelerated this adoption as institutions needed to maintain operations amidst lockdowns. It also enabled pharmaceutical companies to conduct peer reviews digitally, circumventing travel restrictions. At the 2023 Society of Toxicologic Pathology Annual Symposium, a Town Hall Meeting highlighted the current use of digital pathology. A majority of the respondents viewed whole slide images (WSI) favorably. Many institutions use digital pathology primarily for non-GLP and GLP conforming primary reads and peer reviews. Takeda has long utilized digital pathology, incorporating scanners and an image management repository, and recently adopted a cloud-based platform tailored for toxicologic pathology, enhancing efficiency and collaboration. Digital pathology not only saves time but also reduces travel needs and environmental impact. Technological advancements and wider adoption are expected to further enhance the field, promising significant benefits for the overall digital pathology infrastructure.

Recent trends in toxicological pathology include implementation of digital platforms that have gained rapid momentum in the field. Are we ready to fully implement this new modality? This opinion piece provides some practical perspectives on digital pathology such as its cost limitations, relative time requirements, and a few technical issues, some of which are encountered for specific lesions, that warrant caution. Although the potential for digital pathology assessment with whole slide images has made great strides, we are of the opinion that it is not yet ready for complete replacement of glass slides in toxicologic pathology safety assessments.

A retrospective study was performed to determine the incidences of spontaneous findings in control laboratory New Zealand White (NZW) and Dutch Belted (DB) rabbits. Terminal body and organ weights data were also collected. A total of 2170 NZW (526 males/1644 females), 100 DB rabbits (50 animals per sex), aged 4- to 7-month-old were obtained from 158 non-clinical studies evaluated between 2013 and 2022. The NZW rabbits had greater mean terminal body weights than DB strain. Mixed cell infiltration in the lung was the most recorded finding in both strains, followed by pulmonary inflammation/mononuclear cell infiltration. Differentiation between pulmonary "infiltration"/"inflammation" remained challenging as interpretation of guidelines for diagnostic terminology may vary amongst pathologists. Other common findings included mineralization and basophilia of the renal tubules; hepatic/renal mononuclear cell infiltration, all more common in females. Cysts were commonly recorded, with high prevalence in the oviduct, thyroid gland, ovary in NZW strain, while uterine, pituitary gland, and thyroid gland cysts were the most identified in DB rabbits. Neoplasms and infectious etiologies were absent. Most of the animals were sexually mature. To our knowledge, this is the most recent comprehensive study of spontaneous lesions and organ weights in both rabbit strains and should facilitate the differentiation of spontaneous and induced lesions in safety studies.

Sharing pathology data is critical for educational and scientific purposes. Since most pharmaceutical or (agro)chemical companies outsource nonclinical safety assessment studies to contract research organizations (CROs), the pathology data of those studies are not owned by the investigator but is the legal property of the respective company sponsoring the work. Although some companies have installed policies that govern sharing of pathology data, many companies generally do not allow the external use of data by either the CRO-based study pathologist or the sponsor pathologist. Policies for governing the external use of data vary significantly. In this article, we present an overview of the different approaches taken across different companies (CROs, pharmaceutical/chemical companies, or other institutes) for sharing pathology material for educational and/or scientific purposes. The results of a survey and interviews with legal departments of different companies will be presented (anonymously) and discussed. In addition, the importance of sharing pathology data is addressed, as well as the challenges and opportunities this presents. Suggestions will be provided regarding what material should be made available and what will be needed to achieve agreement for this to happen.

One of the emerging concepts on the reduction of animal use in non-clinical studies is the use of virtual control group (VCG) to replace concurrent control group (CCG). The VCG involves the generation of a control data from historical control data to match a specific study design. This review focuses on two recently published proof-of-concept (POC) studies conducted in rats. One major issue that was consistently seen across these POC studies was the non-reproducibility of some quantitative endpoints between the CCG and the VCG, with clinical pathology parameters being the most affected. The inconsistencies observed with the clinical pathology parameters when using VCGs may lead to: (1) misconception about the accuracy and sensitivity of traditional clinical pathology biomarkers and its implications on safety monitoring in the clinic; (2) inability to correctly identify and characterize organ dysfunctions; (3) interference with the weight-of-evidence approach used in identifying hazards in toxicologic clinical pathology and toxicology studies at large; and (4) wrong interpretations and data reproducibility issues. Other alternatives to reduce animal use in toxicology studies are also discussed including blood microsampling for toxicokinetics, scientifically justified use of recovery animals, and appropriate use and continuous investments in new alternative methods.

The virtual control group (VCG) concept was originally developed in the IMI2 project eTRANSAFE, using data of control animals which pharmaceutical companies have accrued over decades from animal toxicity studies. This control data could be repurposed to create virtual control animals to reduce or replace concurrent controls in animal studies. Initial work demonstrated the general feasibility of the VCG concept, but implementation requires significant further collaborative efforts. The new Innovative Health Initiative (IHI) project VICT3R aims to address these challenges and to obtain regulatory acceptance for the VCG concept. To achieve these goals, VICT3R will build a database comprising high-quality, standardized, and duly annotated control animal data from past and forthcoming toxicity studies. The VICT3R project will create workflows and computational tools to generate adequate VCGs based on statistical and artificial intelligence (AI) approaches. The validity, reproducibility, and robustness of the resulting VCGs will be assessed by comparing the performance of their use with that of real control groups.

Microscopic observation data collected from approximately 1800 male and female Sprague Dawley (SD) control rats used on 104-week carcinogenicity studies performed at North American Labcorp Early Development, Inc, Madison, WI, were retrospectively evaluated for spontaneous nonneoplastic findings. This study provides incidence of the most common spontaneous nonneoplastic microscopic findings in each organ system of SD rats encountered during 104-week carcinogenicity studies. Some of the most common spontaneous background findings were cardiomyopathy; chronic progressive nephropathy; uterine cystic endometrial hyperplasia; prostate inflammation; pulmonary alveolar macrophage infiltrates; hepatocyte vacuolation, bile duct hyperplasia, and basophilic foci in the liver; pancreatic fibrosis; splenic extramedullary hematopoiesis and pigment; decreased lymphocytes and epithelial hyperplasia in the thymus; ventral brain compression; cystic degeneration and hyperplasia of the adrenal cortex; and mammary gland hyperplasia. The most common nonneoplastic findings in male SD rats were chronic progressive nephropathy (80.9%) and rodent progressive cardiomyopathy (73.2%). The most common nonnenoplastic findings in female SD rats were cystic degeneration of the adrenal cortex (64.7%) and ventral compression of the brain due to pituitary neoplasms (62.7%).

Enhanced histopathology of the immune system uses a precise, compartment-specific, and semi-quantitative evaluation of lymphoid organs in toxicology studies. The assessment of lymphocyte populations in tissues is subject to sampling variability and limited distinctive cytologic features of lymphocyte subpopulations as seen with hematoxylin and eosin (H&E) staining. Although immunohistochemistry is necessary for definitive characterization of T- and B-cell compartments, routine toxicologic assessments are based solely on H&E slides. Here, a deep learning (DL) model was developed using normal rats to quantify relevant compartments of the spleen, including periarteriolar lymphoid sheaths, follicles, germinal centers, and marginal zones from H&E slides. Slides were scanned, destained, dual labeled with CD3 and CD79a chromogenic immunohistochemistry, and rescanned to generate exact co-registered images that served as the ground truth for training and validation. The DL model identified individual splenic compartments with high accuracy (97.8% Dice similarity coefficient) directly from H&E-stained tissue. The DL model was utilized to study the normal range of lymphoid compartment area and cellularity. Future implementation of our DL model and expanding this approach to other lymphoid tissues have the potential to improve accuracy and precision in enhanced histopathology evaluation of the immune system with concurrent gains in time efficiency for the pathologist.