Abstract

Despite the current advances in micro-CT analysis, the influence of some image acquisition parameters on the morphometric assessment outcome have not been fully elucidated. The aim of this study was to determine whether data binning and frame averaging affect the morphometric outcome of bone repair assessment using micro-CT. Four Wistar rats’ tibiae with a surgically created bone defect were imaged with micro-CT six times each, frame averaging set to 1 and 2, and data binning set to 1, 2 and 4, for each of the averaging values. Two-way ANOVA followed by Bonferroni tests assessed the significance of frame averaging and data binning on a set of morphometric parameters assessed in the image volumes (p < 0.01). The effect of frame averaging was not significant for any of the assessed parameters. Increased data binning led to larger trabecular thickness. In contrast, smaller bone volume fraction and bone volume were found as data binning increased. Trabeculae number and trabecular separation were not influenced by any of the parameters. In conclusion, the morphometric outcome of bone repair assessment in micro-CT demonstrated dependency upon data binning, but not frame averaging. Therefore, image acquisition of small anatomical structures (e.g., rat trabeculae) should be performed without data binning.

Details

Title
Effect of data binning and frame averaging for micro-CT image acquisition on the morphometric outcome of bone repair assessment
Author
Irie, Milena Suemi 1 ; Spin-Neto Rubens 2 ; Borges, Juliana Simeão 1 ; Wenzel, Ann 2 ; Soares Priscilla Barbosa Ferreira 1 

 Federal University of Uberlândia, Department of Periodontology and Implantology, School of Dentistry, Uberlândia, Brazil (GRID:grid.411284.a) (ISNI:0000 0004 4647 6936) 
 Aarhus University, Department of Dentistry and Oral Health, Section for Oral Radiology, Aarhus C, Denmark (GRID:grid.7048.b) (ISNI:0000 0001 1956 2722) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2622861301
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.