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

Camila Rodrigues Borges Linhares1, Isabella Santos Paula1, Eduardo Fraga Maciel1

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Journal of Imaging Informatics in Medicine
|January 7, 2026
PubMed
Summary

This study compared manual, semi-automatic, and automatic methods for histomorphometric analysis of bone repair. The automated ImageJ plugin proved efficient, accurate, and less biased than traditional techniques.

Keywords:
Automated computer-assisted image analysisBone repairHistomorphometryRadiotherapy

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Area of Science:

  • Biomedical Engineering
  • Histology
  • Radiotherapy Research

Background:

  • Histomorphometric analysis is vital for diagnosing and predicting disease outcomes.
  • Automated image processing offers potential for histomorphometry but requires validation.
  • Radiotherapy's impact on bone repair necessitates reliable quantitative analysis methods.

Purpose of the Study:

  • To compare conventional and computational methods for histological image analysis in bone repair.
  • To evaluate the effectiveness of double-threshold segmentation in histomorphometry.
  • To assess the impact of radiotherapy on bone repair using different analysis techniques.

Main Methods:

  • Experimental study involving Wistar rats exposed to varying radiation doses (0-30 Gy).
  • Bone defects induced in tibia and molars, followed by histological processing and staining.
  • Analysis of 651 sections using manual grid-based, semi-automatic ImageJ, and a novel automatic ImageJ plugin.

Main Results:

  • All three methods (manual, semi-automatic, automatic) showed strong agreement in assessing bone neoformation.
  • No statistically significant differences were found between the analysis methods (p > 0.05).
  • The automated ImageJ plugin significantly reduced analysis time compared to other methods (p < 0.01).

Conclusions:

  • Conventional and computational methods are effective for histomorphometric analysis of bone repair.
  • The automated ImageJ plugin provides a more efficient, standardized, and less biased approach.
  • This automated method enhances the evaluation of radiotherapy effects on bone healing.