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Impact of Micro-computed Tomography Reconstruction Protocols on Bone Microarchitecture Analysis

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Publisher Elsevier
Date 2019 Jun 15
PMID 31196704
Citations 1
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Abstract

Objective: The aim of this study was to assess the influence of reconstruction protocols of micro-computed tomography (micro-CT) images on analyses of bone microarchitecture.

Study Design: Micro-CT images of the maxillae of 5 Wistar rats were reconstructed with different protocols by varying the levels of the following tools: smoothing filter (SF; 2-6); ring artifact correction (RAC; 5-15); and beam hardening correction (BHC; 15%-60%). A control protocol (P0; without any correction tool) and a standard protocol (SP; according to the manufacturer's recommendation: SF = 2; RAC = 5; BHC = 45%) were also obtained. For each protocol, 8 bone microarchitecture parameters were calculated (bone volume/total volume [BV/TV], bone surface/total volume [BS/TV], trabecular number [Tb.N], trabecular thickness [Tb.Th], trabecular separation [Tb.Sp], degree of anisotropy [DA], connectivity density [Conn.D], and total porosity [Po-tot]) by using CTAn software. Test protocols were compared with the SP by using 1-way analysis of variance and the Dunnet post hoc test (α = 0.05).

Results: An inverse relationship was observed between BHC tool levels and all microarchitecture parameters except BV/TV and Tb.Th. The combination of BHC and SF significantly influenced all microarchitecture parameters except for DA, for which all protocols were similar to the SP (P > .05).

Conclusions: Calculation of bone microarchitecture parameters is influenced by the applied levels of artifact correction tools, mainly BHC and SF. It is necessary to standardize such tool levels for correct data interpretation.

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Micro-Computed Tomography Analysis of Peri-Implant Bone Defects Exposed to a Peri-Implantitis Microcosm, with and without Bone Substitute, in a Rabbit Model: A Pilot Study.

Panes C, Valdivia-Gandur I, Veuthey C, Sousa V, Del Sol M, Beltran V Bioengineering (Basel). 2024; 11(4).

PMID: 38671818 PMC: 11048142. DOI: 10.3390/bioengineering11040397.