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Application of the Homologous Modeling Technique for Precision Medicine in the Field of Oral and Maxillofacial Surgery
In the field of oral and maxillofacial surgery, establishment of a new method for predicting morphology is desirable. Therefore, the purpose of the present study was to establish a new method for predicting the original shape of a mandibular defect site using the homologous modeling technique. This...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9698512/ https://www.ncbi.nlm.nih.gov/pubmed/36579552 http://dx.doi.org/10.3390/jpm12111831 |
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author | Nakano, Hiroyuki Suzuki, Kei Inoue, Kazuya Nakajima, Yoichiro Mishima, Katsuaki Ueno, Takaaki Demura, Noboru |
author_facet | Nakano, Hiroyuki Suzuki, Kei Inoue, Kazuya Nakajima, Yoichiro Mishima, Katsuaki Ueno, Takaaki Demura, Noboru |
author_sort | Nakano, Hiroyuki |
collection | PubMed |
description | In the field of oral and maxillofacial surgery, establishment of a new method for predicting morphology is desirable. Therefore, the purpose of the present study was to establish a new method for predicting the original shape of a mandibular defect site using the homologous modeling technique. This study used data from 44 patients who underwent computed tomography in the Department of Oral Surgery at Osaka Medical College. Two types of homologous models were constructed: total mandible (TM) and half mandible (HM). Principal component analysis (PCA) was performed using point cloud data of the homologous model M and homologous model HM, and a multiple regression equation was created using the PC value of TM as the object variable and PC value of HM as the explanatory variable. The predicted PC (M) was created from PC (HM) using a regression formula, back-calculated from point cloud data from PC (M), to create the predicted mandible model. Finally, the original image (TC-M) and estimated mandible were superposed and examined. The mean absolute error between the predicted mandible and actual mandible was 1.04 ± 1.35 mm. We believe that this method will be applicable in actual clinical practice. |
format | Online Article Text |
id | pubmed-9698512 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96985122022-11-26 Application of the Homologous Modeling Technique for Precision Medicine in the Field of Oral and Maxillofacial Surgery Nakano, Hiroyuki Suzuki, Kei Inoue, Kazuya Nakajima, Yoichiro Mishima, Katsuaki Ueno, Takaaki Demura, Noboru J Pers Med Article In the field of oral and maxillofacial surgery, establishment of a new method for predicting morphology is desirable. Therefore, the purpose of the present study was to establish a new method for predicting the original shape of a mandibular defect site using the homologous modeling technique. This study used data from 44 patients who underwent computed tomography in the Department of Oral Surgery at Osaka Medical College. Two types of homologous models were constructed: total mandible (TM) and half mandible (HM). Principal component analysis (PCA) was performed using point cloud data of the homologous model M and homologous model HM, and a multiple regression equation was created using the PC value of TM as the object variable and PC value of HM as the explanatory variable. The predicted PC (M) was created from PC (HM) using a regression formula, back-calculated from point cloud data from PC (M), to create the predicted mandible model. Finally, the original image (TC-M) and estimated mandible were superposed and examined. The mean absolute error between the predicted mandible and actual mandible was 1.04 ± 1.35 mm. We believe that this method will be applicable in actual clinical practice. MDPI 2022-11-03 /pmc/articles/PMC9698512/ /pubmed/36579552 http://dx.doi.org/10.3390/jpm12111831 Text en © 2022 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 Nakano, Hiroyuki Suzuki, Kei Inoue, Kazuya Nakajima, Yoichiro Mishima, Katsuaki Ueno, Takaaki Demura, Noboru Application of the Homologous Modeling Technique for Precision Medicine in the Field of Oral and Maxillofacial Surgery |
title | Application of the Homologous Modeling Technique for Precision Medicine in the Field of Oral and Maxillofacial Surgery |
title_full | Application of the Homologous Modeling Technique for Precision Medicine in the Field of Oral and Maxillofacial Surgery |
title_fullStr | Application of the Homologous Modeling Technique for Precision Medicine in the Field of Oral and Maxillofacial Surgery |
title_full_unstemmed | Application of the Homologous Modeling Technique for Precision Medicine in the Field of Oral and Maxillofacial Surgery |
title_short | Application of the Homologous Modeling Technique for Precision Medicine in the Field of Oral and Maxillofacial Surgery |
title_sort | application of the homologous modeling technique for precision medicine in the field of oral and maxillofacial surgery |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9698512/ https://www.ncbi.nlm.nih.gov/pubmed/36579552 http://dx.doi.org/10.3390/jpm12111831 |
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