Lymphoblastic lymphoma (LBL) is an aggressive neoplasm characterised by the proliferation of undifferentiated lymphocytes. It primarily spreads to immune organs such as the thymus, spleen, lymph nodes, bone marrow, and liver. Although well-documented in humans, spontaneous LBL cases in laboratory animals are exceedingly rare. This study reports a case of T cell-derived LBL in a young adult ICR mouse, notably without bone marrow metastasis. This case provides valuable insights into the spontaneous occurrence of LBL in laboratory rodents by contributing to comparative oncology and preclinical research.

In recent years, the development of Artificial Intelligence (AI) technology has led to the introduction and use of AI-based histopathological evaluation (AI pathology) by various companies and organizations. The AI Pathology Task Force of the Non-clinical Evaluation Expert Committee within the Drug Evaluation Committee of the Japan Pharmaceutical Manufacturers Association (JPMA) recognizes the importance of understanding the current use and needs surrounding AI pathology in Japan. This includes its role in non-clinical research fields, such as toxicity evaluation, drug efficacy evaluation, and basic research. In addition, assessing needs and challenges related to pathology image databases is essential. Between October and November 2023, with the cooperation of the Japanese Society of Toxicologic Pathology (JSTP), we conducted a questionnaire survey on non-clinical pathology image databases to explore these issues among JPMA-affiliated and JSTP-affiliated organizations. The questionnaire survey consisted of three items: (1) implementation and utilization of whole slide images, (2) use of AI pathology in non-clinical research fields, and (3) needs and feasibility of establishing a precompetitive pathology image database (repository) and AI pathology in the non-clinical pathology field. This report summarizes the survey results and serves as a foundation for guiding future directions in the use of AI pathology in non-clinical studies in Japan.

The use of artificial intelligence (AI) in non-clinical pathology is rapidly expanding. In this study, we conducted a literature survey of articles published after 2017 that used AI to analyze the histopathological images of experimental animals. We identified 44 articles that used AI for various purposes, including the detection of abnormal sites, determination and quantification of normal tissues, and classification of normal/abnormal images. AI systems or applications were either custom-built, commercially available, or a combination of both. Rats and mice were mainly used, and the liver was the most frequently analyzed organ. Our findings suggest that AI can be useful in non-clinical pathology and that collaboration between pharmaceutical companies or cooperation with IT experts can be a potential approach to further advance the utilization of AI in this field.