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Human Bone Typing Using Quantitative Cone-Beam Computed Tomography

INTRODUCTION: Bone typing is crucial to enable the choice of a suitable implant, the surgical technique, and the evaluation of the clinical outcome. Currently, bone typing is assessed subjectively by the surgeon. OBJECTIVE: The aim of this study is to establish an automatic quantification method to...

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Autores principales: Huang, Hairong, Chen, Dong, Lippuner, Kurt, Hunziker, Ernst B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10023581/
https://www.ncbi.nlm.nih.gov/pubmed/36182605
http://dx.doi.org/10.1016/j.identj.2022.08.011
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author Huang, Hairong
Chen, Dong
Lippuner, Kurt
Hunziker, Ernst B.
author_facet Huang, Hairong
Chen, Dong
Lippuner, Kurt
Hunziker, Ernst B.
author_sort Huang, Hairong
collection PubMed
description INTRODUCTION: Bone typing is crucial to enable the choice of a suitable implant, the surgical technique, and the evaluation of the clinical outcome. Currently, bone typing is assessed subjectively by the surgeon. OBJECTIVE: The aim of this study is to establish an automatic quantification method to determine local bone types by the use of cone-beam computed tomography (CBCT) for an observer-independent approach. METHODS: Six adult human cadaver skulls were used. The 4 generally used bone types in dental implantology and orthodontics were identified, and specific Hounsfield unit (HU) ranges (grey-scale values) were assigned to each bone type for identification by quantitative CBCT (qCBCT). The selected scanned planes were labelled by nonradiolucent markers for reidentification in the backup/cross-check evaluation methods. The selected planes were then physically removed as thick bone tissue sections for in vitro correlation measurements by qCBCT, quantitative micro–computed tomography (micro-CT), and quantitative histomorphometry. RESULTS: Correlation analyses between the different bone tissue quantification methods to identify bone types based on numerical ranges of HU values revealed that the Pearson correlation coefficient of qCBCT with micro-CT and quantitative histomorphometry was R = 0.9 (P = .001) for all 4 bone types . CONCLUSIONS: We found that  qCBCT can reproducibly and objectively assess human bone types at implant sites.
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spelling pubmed-100235812023-03-19 Human Bone Typing Using Quantitative Cone-Beam Computed Tomography Huang, Hairong Chen, Dong Lippuner, Kurt Hunziker, Ernst B. Int Dent J Scientific Research Report INTRODUCTION: Bone typing is crucial to enable the choice of a suitable implant, the surgical technique, and the evaluation of the clinical outcome. Currently, bone typing is assessed subjectively by the surgeon. OBJECTIVE: The aim of this study is to establish an automatic quantification method to determine local bone types by the use of cone-beam computed tomography (CBCT) for an observer-independent approach. METHODS: Six adult human cadaver skulls were used. The 4 generally used bone types in dental implantology and orthodontics were identified, and specific Hounsfield unit (HU) ranges (grey-scale values) were assigned to each bone type for identification by quantitative CBCT (qCBCT). The selected scanned planes were labelled by nonradiolucent markers for reidentification in the backup/cross-check evaluation methods. The selected planes were then physically removed as thick bone tissue sections for in vitro correlation measurements by qCBCT, quantitative micro–computed tomography (micro-CT), and quantitative histomorphometry. RESULTS: Correlation analyses between the different bone tissue quantification methods to identify bone types based on numerical ranges of HU values revealed that the Pearson correlation coefficient of qCBCT with micro-CT and quantitative histomorphometry was R = 0.9 (P = .001) for all 4 bone types . CONCLUSIONS: We found that  qCBCT can reproducibly and objectively assess human bone types at implant sites. Elsevier 2022-09-29 /pmc/articles/PMC10023581/ /pubmed/36182605 http://dx.doi.org/10.1016/j.identj.2022.08.011 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Scientific Research Report
Huang, Hairong
Chen, Dong
Lippuner, Kurt
Hunziker, Ernst B.
Human Bone Typing Using Quantitative Cone-Beam Computed Tomography
title Human Bone Typing Using Quantitative Cone-Beam Computed Tomography
title_full Human Bone Typing Using Quantitative Cone-Beam Computed Tomography
title_fullStr Human Bone Typing Using Quantitative Cone-Beam Computed Tomography
title_full_unstemmed Human Bone Typing Using Quantitative Cone-Beam Computed Tomography
title_short Human Bone Typing Using Quantitative Cone-Beam Computed Tomography
title_sort human bone typing using quantitative cone-beam computed tomography
topic Scientific Research Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10023581/
https://www.ncbi.nlm.nih.gov/pubmed/36182605
http://dx.doi.org/10.1016/j.identj.2022.08.011
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