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Agreement between histomorphometry and microcomputed tomography to assess bone microarchitecture of dental implant sites
Malmö högskola, Faculty of Odontology (OD).
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2015 (English)In: Clinical Implant Dentistry and Related Research, ISSN 1523-0899, E-ISSN 1708-8208, Vol. 17, no 4, p. 732-741Article in journal (Refereed)
Abstract [en]

Background:Histomorphometry and microcomputed tomography (microCT) have been used in implant studies but need better understanding before being used as equivalent methods. PurposeThe purpose of this study was to investigate the agreement between 2D (histomorphometry) and 3D (microCT) reference methods for assessing jawbone microarchitecture in vivo. Material and MethodsForty-four bone specimens from 32 patients were obtained during implant placement and examined by microCT, followed by hematoxylin-eosin staining and histomorphometric analysis. The morphometric parameters included bone volume density (BV/TV), bone surface fraction (BS/TV), bone surface density, trabecular thickness, trabecular number, and trabecular separation (Tb.Sp). Bland-Altman plots were used for pairwise agreement analysis between the equivalent 3D and 2D parameters, and complemented with Mountain plots. The association between the two methods was tested using Pearson's correlation followed by Passing-Bablok regression. ResultsSystematic bias was observed in all Bland-Altman and Mountain plots, including constant bias for BV/TV and Tb.Sp, and proportional bias for all other parameters. Significant correlation was found for BV/TV (r=0.80; p<.001) and BS/TV (r=0.44; p=.003), and the Passing-Bablok regression showed constant bias for BV/TV and proportional bias for BS/TV. ConclusionBecause of the poor agreement between measures obtained by histomorphometry and microCT, these methods should not be used interchangeably for jawbones.

Place, publisher, year, edition, pages
John Wiley & Sons, 2015. Vol. 17, no 4, p. 732-741
Keywords [en]
bone, computerized tomography, histological analysis, implant
National Category
Dentistry
Identifiers
URN: urn:nbn:se:mau:diva-15804DOI: 10.1111/cid.12176ISI: 000358536700013PubMedID: 24238279Scopus ID: 2-s2.0-84887590750Local ID: 20035OAI: oai:DiVA.org:mau-15804DiVA, id: diva2:1419326
Available from: 2020-03-30 Created: 2020-03-30 Last updated: 2024-02-05Bibliographically approved

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Lindh, Christina

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