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Cross Sectional Analysis of Eurasian Skull Anatomy for 3D Cephalometry—Normative Data Reveal Four Different Skull Types

The unsolved problem in three-dimensional surgical planning for patients with facial deformity, dysgnathia, or asymmetry is the lack of a normative database of “norm skulls” that can be used as treatment objectives. A study was conducted on 90 Eurasian persons (46 male and 44 female adults) for whom...

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Autores principales: Ludwigs, Leon, Pape, Christian, Visse, Helena Sophie, Runte, Christoph, Meyer, Ulrich, Dirksen, Dieter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10300808/
https://www.ncbi.nlm.nih.gov/pubmed/37374007
http://dx.doi.org/10.3390/jpm13061018
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author Ludwigs, Leon
Pape, Christian
Visse, Helena Sophie
Runte, Christoph
Meyer, Ulrich
Dirksen, Dieter
author_facet Ludwigs, Leon
Pape, Christian
Visse, Helena Sophie
Runte, Christoph
Meyer, Ulrich
Dirksen, Dieter
author_sort Ludwigs, Leon
collection PubMed
description The unsolved problem in three-dimensional surgical planning for patients with facial deformity, dysgnathia, or asymmetry is the lack of a normative database of “norm skulls” that can be used as treatment objectives. A study was conducted on 90 Eurasian persons (46 male and 44 female adults) for whom cone beam-computed tomography images were available. Inclusion criteria were adult patients with a skeletal Class I pattern, proper interincisal relationship with normal occlusion, the absence of an open bite both in the anterior and posterior region, and a normal and balanced facial appearance; patients with dysgnathia and malformations were excluded. A total of 18 landmarks were digitized and 3D cephalometric measurements were performed and analyzed by means of proportions calculated from the landmarks. Male and female skulls were analyzed, as well as subdivisions revealed by cluster analysis. The data showed that four subtypes of skulls were distinguishable with statistical significance (p < 0.05). A male and a female type subdivided in a brachiocephalic and dolichocephalic phenotype could be identified. For each type, a mean shape was calculated by a Procrustes transformation, which, in turn, was used to create four template skulls from a male and a female skull. This was accomplished by fitting the polygon models of the two skulls to each of the two subtypes based on the landmarks marked on them using a thin plate spline transformation. The normative data of the subtypes can individually serve as a guide for orthodontic surgery in the Eurasian population, which is especially helpful in 3D planning and the execution of craniofacial operations.
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spelling pubmed-103008082023-06-29 Cross Sectional Analysis of Eurasian Skull Anatomy for 3D Cephalometry—Normative Data Reveal Four Different Skull Types Ludwigs, Leon Pape, Christian Visse, Helena Sophie Runte, Christoph Meyer, Ulrich Dirksen, Dieter J Pers Med Article The unsolved problem in three-dimensional surgical planning for patients with facial deformity, dysgnathia, or asymmetry is the lack of a normative database of “norm skulls” that can be used as treatment objectives. A study was conducted on 90 Eurasian persons (46 male and 44 female adults) for whom cone beam-computed tomography images were available. Inclusion criteria were adult patients with a skeletal Class I pattern, proper interincisal relationship with normal occlusion, the absence of an open bite both in the anterior and posterior region, and a normal and balanced facial appearance; patients with dysgnathia and malformations were excluded. A total of 18 landmarks were digitized and 3D cephalometric measurements were performed and analyzed by means of proportions calculated from the landmarks. Male and female skulls were analyzed, as well as subdivisions revealed by cluster analysis. The data showed that four subtypes of skulls were distinguishable with statistical significance (p < 0.05). A male and a female type subdivided in a brachiocephalic and dolichocephalic phenotype could be identified. For each type, a mean shape was calculated by a Procrustes transformation, which, in turn, was used to create four template skulls from a male and a female skull. This was accomplished by fitting the polygon models of the two skulls to each of the two subtypes based on the landmarks marked on them using a thin plate spline transformation. The normative data of the subtypes can individually serve as a guide for orthodontic surgery in the Eurasian population, which is especially helpful in 3D planning and the execution of craniofacial operations. MDPI 2023-06-19 /pmc/articles/PMC10300808/ /pubmed/37374007 http://dx.doi.org/10.3390/jpm13061018 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ludwigs, Leon
Pape, Christian
Visse, Helena Sophie
Runte, Christoph
Meyer, Ulrich
Dirksen, Dieter
Cross Sectional Analysis of Eurasian Skull Anatomy for 3D Cephalometry—Normative Data Reveal Four Different Skull Types
title Cross Sectional Analysis of Eurasian Skull Anatomy for 3D Cephalometry—Normative Data Reveal Four Different Skull Types
title_full Cross Sectional Analysis of Eurasian Skull Anatomy for 3D Cephalometry—Normative Data Reveal Four Different Skull Types
title_fullStr Cross Sectional Analysis of Eurasian Skull Anatomy for 3D Cephalometry—Normative Data Reveal Four Different Skull Types
title_full_unstemmed Cross Sectional Analysis of Eurasian Skull Anatomy for 3D Cephalometry—Normative Data Reveal Four Different Skull Types
title_short Cross Sectional Analysis of Eurasian Skull Anatomy for 3D Cephalometry—Normative Data Reveal Four Different Skull Types
title_sort cross sectional analysis of eurasian skull anatomy for 3d cephalometry—normative data reveal four different skull types
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10300808/
https://www.ncbi.nlm.nih.gov/pubmed/37374007
http://dx.doi.org/10.3390/jpm13061018
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