Comparative Analysis of Different Methods in the Quantification of Bone Matrix in Irradiated Rats

Histomorphometric analysis is crucial for evaluating tissue, aiding in disease diagnosis and prognosis. While automated image processing has advanced, its application in histomorphometry remains limited. This experimental study aimed to compare conventional and computational methods for analyzing histological images using double-threshold segmentation. To do this, researchers evaluated the effects of radiotherapy on bone repair in rats. Twenty-eight male Wistar rats had bone defects induced in the tibia and lower molars extracted, then were divided into four groups based on radiation dose: control (non-irradiated), 15 Gy, 20 Gy, and 30 Gy. Fourteen days post-surgery, the animals were euthanized, and tissue samples from the mandible and tibia were processed and stained. A total of 651 histological sections were analyzed using three methods: (a) manual grid-based quantification, (b) semi-automatic segmentation using ImageJ, and (c) a newly developed automatic ImageJ plugin. The methods were compared using Bland-Altman statistical analysis. Results showed strong agreement among the methods with no statistical differences (p > 0.05). However, the automated method significantly reduced analysis time (p < 0.01). The study concludes that while all methods are effective for assessing bone neoformation, the automated approach offers greater efficiency, standardization, and reduced bias.