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

Area of Science:

• Radiation biology
• Hematology
• Pathology

Background:

• Radiation exposure causes significant bone marrow changes, often subtle and difficult to detect with traditional methods.
• Artificial intelligence (AI) offers enhanced sensitivity for analyzing biological alterations.
• Accurate quantification of radiation effects is crucial for understanding radiation biology and pathology.

Purpose of the Study:

• To evaluate the effects of whole-body irradiation (WBI) on blood parameters, bone marrow density, and apoptosis in mice.
• To assess the utility of AI-based image analysis for quantifying radiation-induced changes in bone marrow.
• To investigate dose-dependent and time-dependent responses to WBI.

Main Methods:

• Female C57BL/6 mice were exposed to 0, 0.5, 1, or 2 Gy of WBI.
• Blood parameters (WBC, RBC, platelets) were analyzed post-irradiation.
• Sternum samples underwent histopathological evaluation and AI-based image analysis for cell density and apoptosis.
• Mice were analyzed at 1, 3, and 7 days post-irradiation.

Main Results:

• WBI significantly altered blood parameters, decreasing white blood cell and red blood cell counts while increasing platelet counts.
• AI analysis confirmed a significant decrease in bone marrow cellularity at 2 Gy WBI on day 1 (p < 0.01).
• Apoptosis significantly increased in the 2 Gy WBI group on days 1, 3 (p < 0.01), and 7 (p < 0.05).

Conclusions:

• WBI induces significant hematological and histopathological alterations in mouse bone marrow.
• AI-based image analysis provides a precise and efficient tool for quantifying radiation-induced bone marrow changes.
• This AI approach holds potential for advancing radiation biology and pathology research.