Evaluation of radiation-induced bone marrow toxicity using artificial intelligence-based image analysis in mice.

IF 1.6 4区 医学 Q4 TOXICOLOGY
Toxicological Research Pub Date : 2025-04-08 eCollection Date: 2025-07-01 DOI:10.1007/s43188-025-00290-3
Yoon Ji Choi, Da Song Back, Kwang Ho Jang, Mijeong Park, Jimin Ha, Youn Kyoung Jeong, Jin Seok Kang
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Abstract

Radiation exposure profoundly affects bone marrow, with even low-dose exposure inducing notable biological changes. Traditional pathology methods often face challenges in detecting subtle alterations. However, artificial intelligence (AI) offers enhanced sensitivity and precision, enabling a more detailed analysis. This study aimed to evaluate the effect of whole-body irradiation (WBI) on blood parameters, bone marrow density, and apoptosis in mice, employing AI-based image analysis for accurate and efficient quantification of cell density and apoptosis. Female C57BL/6 mice (n = 120) were divided into four groups: a control group (Group 1) and three irradiated groups (Groups 2, 3, and 4), exposed to 0.5 Gy, 1 Gy, and 2 Gy of WBI, respectively. Mice were sacrificed at 1, 3, and 7 days post-irradiation for analysis. Blood samples were assessed for hematological changes, and the sternum was histopathologically evaluated. Despite stable body weights, WBI significantly altered blood parameters, reducing white blood cell and red blood cell counts while increasing platelet counts. Histopathological examination revealed a marked reduction in bone marrow cellularity in Groups 3 and 4 on day 1 post-irradiation; however, cellularity appeared to recover in these groups by days 3 and 7. AI-based image analysis of the sternum provided precise quantification, confirming a significant decrease in bone marrow cellularity in Groups 3 and 4 compared to Group 1 on day 1 (p < 0.01). Apoptosis analysis also demonstrated a significant increase in the apoptotic index in Group 4 sternum samples on days 1, 3 (p < 0.01), and day 7 (p < 0.05) relative to Group 1. In summary, WBI induced hematological and histopathological alterations in mice, characterized by changes in blood cell parameters, bone marrow cellularity, and apoptosis. The integration of AI-based image analysis provides a robust and efficient tool for quantifying these changes, offering considerable potential for advancing radiation biology and pathology research.

基于人工智能图像分析的小鼠辐射诱导骨髓毒性评价。
辐射照射对骨髓有深远影响,即使低剂量照射也会引起显著的生物学变化。传统的病理学方法在检测细微变化时常常面临挑战。然而,人工智能(AI)提供了更高的灵敏度和精度,可以进行更详细的分析。本研究旨在评估全身照射(WBI)对小鼠血液参数、骨髓密度和细胞凋亡的影响,采用基于人工智能的图像分析技术准确、高效地定量细胞密度和细胞凋亡。雌性C57BL/6小鼠(n = 120)分为4组:对照组(1组)和3个辐照组(2、3、4组),分别暴露于0.5 Gy、1 Gy、2 Gy的WBI。分别于照射后1、3、7天处死小鼠进行分析。评估血液样本的血液学变化,胸骨进行组织病理学评估。尽管体重稳定,但WBI显著改变了血液参数,减少了白细胞和红细胞计数,同时增加了血小板计数。组织病理学检查显示,第3组和第4组在照射后第1天骨髓细胞数量明显减少;然而,在第3天和第7天,这些组的细胞结构似乎恢复了。基于人工智能的胸骨图像分析提供了精确的定量,证实第1天,与第1组相比,第3组和第4组的骨髓细胞数量显著减少(p p p
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来源期刊
CiteScore
4.20
自引率
4.30%
发文量
39
期刊介绍: Toxicological Research is the official journal of the Korean Society of Toxicology. The journal covers all areas of Toxicological Research of chemicals, drugs and environmental agents affecting human and animals, which in turn impact public health. The journal’s mission is to disseminate scientific and technical information on diverse areas of toxicological research. Contributions by toxicologists, molecular biologists, geneticists, biochemists, pharmacologists, clinical researchers and epidemiologists with a global view on public health through toxicological research are welcome. Emphasis will be given to articles providing an understanding of the toxicological mechanisms affecting animal, human and public health. In the case of research articles using natural extracts, detailed information with respect to the origin, extraction method, chemical profiles, and characterization of standard compounds to ensure the reproducible pharmacological activity should be provided.
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