Αρχειοθήκη ιστολογίου

Αλέξανδρος Γ. Σφακιανάκης
ΩτοΡινοΛαρυγγολόγος
Αναπαύσεως 5
Άγιος Νικόλαος Κρήτη 72100
2841026182
6032607174

Τετάρτη 26 Σεπτεμβρίου 2018

Quantification of the mandibular defect healing by micro CT morphometric analysis in rats

Publication date: Available online 25 September 2018

Source: Journal of Cranio-Maxillofacial Surgery

Author(s): T. Kustro, T. Kiss, D. Chernohorskyi, Y. Chepurnyi, Z. Helyes, A. Kopchak

Summary
Purpose

The goal of this study was the evaluation of the bone tissue structural characteristics over the time course of mandibular defect healing using micro-CT technique, as well as determination of the inter-relationships between different micro-CT parameters used for assessment of the bone regeneration process and the patterns of their dynamic changes.

Materials and Methods

The body and ramus of the mandible was exposed in 24 Wistar rats. A 2-mm full thickness bony defect was created. Animals were randomized into four groups, which were ended 3, 6, 12 and 24 weeks after operation. The mandible was excised and underwent micro-CT analysis. For statistical evaluation, the Mann–Whitney U test, polynomial or exponential regression and Spearman analysis were applied.

Results

The absolute volume of the bone regenerate increased from 1.69+0.53 mm3 (3 weeks) to 3.36 mm3+0.56 (6 months), as well as percentage of bone volume, increased significantly from 12.5+2.3% at the 3-week term to 26.4+8.7% at the 3-month term or 23.1+8.7% at the 6-month term. Structural (trabecular) thickness gradually increased from 0.13+0.007 mm at the 3-week term to 0.3+0.11 mm at the 6-month term. The structural model index was 0.79+0.46 in the early phase after trauma and then decreased to negative values.

Conclusion

The bone regeneration process was characterised by a significant increase (p<0.05) in bone volume, percentage of bone volume, structural thickness and bone mineral density, and a decrease in bone surface-to-volume ratio and volume of pore space from the 3-week term to the 6-month term. These changes can be mathematically described by nonlinear exponential regression models.



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