Computational image analysis of kidney tissue samples of beagle dogs irradiated with ⁶⁰Co gamma-rays

The advancements in the computational capabilities, over the past two decades, led to the intensification of research and practical application in the fields of computational image analysis and data classification. In particular, this approach is of interest in medicine, as it promises enhanced diagnostic accuracy and detection of subtle features. Alterations and patterns in medical images can be detected and quantified with precision. Additionally, the approach is markedly time saving and enabling of handling big amounts of data, giving new insights into the disease mechanisms and progression through data patterns and correlations. Given relatively large quantities of data collected from radiobiology megastudies conducted in the past, we decided to subject some of these archival tissue specimens to computational image analysis in order to study in more detail structural changes in particular organs due to exposures to ionizing radiation. Here, we analyzed solid tissue samples of kidneys in beagle dogs irradiated with ⁶⁰Co gamma-rays. We performed multifractal analysis, of the arrangements and shapes of cell nuclei, as well as tissue architecture in sections stained with hematoxylin and eosin. Although the dosing patterns differed, as well as the resulting days of survival and causes of death (not directly linked to the kidneys), we were able to quantify some of the structural changes present in the analyzed specimens. With the further analyses and more systematic study, we hope to form a base of knowledge on tissue structural modifications and typical values of tissue descriptors in various cases.