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Regressive changes of crown‐root morphology and their volumetric segmentation for adult dental age estimation

Cone‐beam computed tomography (CBCT) enables the assessment of regressive morphological changes in teeth, which can be used to predict chronological age (CA) in adults. As each tooth region is known to have different correlations with CA, this study aimed to segment and quantify the sectional volume...

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Autores principales: Merdietio Boedi, Rizky, Shepherd, Simon, Oscandar, Fahmi, Mânica, Scheila, Franco, Ademir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9540017/
https://www.ncbi.nlm.nih.gov/pubmed/35819122
http://dx.doi.org/10.1111/1556-4029.15094
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author Merdietio Boedi, Rizky
Shepherd, Simon
Oscandar, Fahmi
Mânica, Scheila
Franco, Ademir
author_facet Merdietio Boedi, Rizky
Shepherd, Simon
Oscandar, Fahmi
Mânica, Scheila
Franco, Ademir
author_sort Merdietio Boedi, Rizky
collection PubMed
description Cone‐beam computed tomography (CBCT) enables the assessment of regressive morphological changes in teeth, which can be used to predict chronological age (CA) in adults. As each tooth region is known to have different correlations with CA, this study aimed to segment and quantify the sectional volumes of the tooth crown and root from CBCT scans to test their correlations with the chronological age (CA). Seventy‐five CBCT scans from individuals with age between 20 and 60 years were collected retrospectively from an existing database. A total of 192 intact maxillary anterior teeth fulfilled the eligibility criteria. The upper tooth volume ratio (UTVR), lower tooth volume ratio (LTVR), and sex were used as predictor variables. The UTVR and LTVR parameters were both found to be differently correlated to CA and independent from each other. Regression models were derived from each tooth, with the highest R (2) being the maxillary lateral incisor (R (2) = 0.67). Additional single predictor models using each ratio were capable of reliably predicting the CA. The segmentation approach in volumetric adult dental age estimation proved to be beneficial in enhancing the reliability of the regression model.
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spelling pubmed-95400172022-10-14 Regressive changes of crown‐root morphology and their volumetric segmentation for adult dental age estimation Merdietio Boedi, Rizky Shepherd, Simon Oscandar, Fahmi Mânica, Scheila Franco, Ademir J Forensic Sci Original Papers Cone‐beam computed tomography (CBCT) enables the assessment of regressive morphological changes in teeth, which can be used to predict chronological age (CA) in adults. As each tooth region is known to have different correlations with CA, this study aimed to segment and quantify the sectional volumes of the tooth crown and root from CBCT scans to test their correlations with the chronological age (CA). Seventy‐five CBCT scans from individuals with age between 20 and 60 years were collected retrospectively from an existing database. A total of 192 intact maxillary anterior teeth fulfilled the eligibility criteria. The upper tooth volume ratio (UTVR), lower tooth volume ratio (LTVR), and sex were used as predictor variables. The UTVR and LTVR parameters were both found to be differently correlated to CA and independent from each other. Regression models were derived from each tooth, with the highest R (2) being the maxillary lateral incisor (R (2) = 0.67). Additional single predictor models using each ratio were capable of reliably predicting the CA. The segmentation approach in volumetric adult dental age estimation proved to be beneficial in enhancing the reliability of the regression model. John Wiley and Sons Inc. 2022-07-12 2022-09 /pmc/articles/PMC9540017/ /pubmed/35819122 http://dx.doi.org/10.1111/1556-4029.15094 Text en © 2022 The Authors. Journal of Forensic Sciences published by Wiley Periodicals LLC on behalf of American Academy of Forensic Sciences. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Original Papers
Merdietio Boedi, Rizky
Shepherd, Simon
Oscandar, Fahmi
Mânica, Scheila
Franco, Ademir
Regressive changes of crown‐root morphology and their volumetric segmentation for adult dental age estimation
title Regressive changes of crown‐root morphology and their volumetric segmentation for adult dental age estimation
title_full Regressive changes of crown‐root morphology and their volumetric segmentation for adult dental age estimation
title_fullStr Regressive changes of crown‐root morphology and their volumetric segmentation for adult dental age estimation
title_full_unstemmed Regressive changes of crown‐root morphology and their volumetric segmentation for adult dental age estimation
title_short Regressive changes of crown‐root morphology and their volumetric segmentation for adult dental age estimation
title_sort regressive changes of crown‐root morphology and their volumetric segmentation for adult dental age estimation
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9540017/
https://www.ncbi.nlm.nih.gov/pubmed/35819122
http://dx.doi.org/10.1111/1556-4029.15094
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