Morphometric visualization, analysis, and assessment of atherosclerotic lesions in an apolipoprotein E–deficient mouse model (ApoE−/−)

Introduction: The improvement of diagnostic methods in atherosclerosis is aimed at accurately determining the stage of the pathological process and eliminating subjective interpretation of data. Implementation of this approach increases the reliability of comparative assessment of the effectiveness of therapeutic and interventional strategies and reduces statistical variability within experimental studies. Materials and Methods: The study was performed on 20 male ApoE−/− mice (40 weeks old) divided into groups receiving a standard diet or a Western diet. After anesthesia, PBS perfusion was performed; the heart with the aorta was excised and fixed in 10% formalin; the aorta was cleaned and stained with Oil Red O. The aorta was longitudinally opened, photographed (GelDoc), and quantitatively analyzed using a Python script. Data are presented as mean ± SD; statistical significance was assessed using Student’s t-test at p < 0.05. Results and Discussion: Thus, the use of the Oil Red O staining method in combination with automated image analysis in Python enables a transition from subjective assessment to precise quantitative measurement of the area of atherosclerotic lesions. This approach increases the reliability of screening therapeutic interventions in experimental models and enhances the statistical power of the study. Conclusion: In this study, an original approach to morphometric visualization, analysis, and quantitative assessment of atherosclerotic lesions of the vascular wall in an apolipoprotein E–deficient mouse model (ApoE−/−) is proposed and validated for the first time.