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Automated and data-driven plate computation for presurgical cleft lip and palate treatment
PURPOSE: Presurgical orthopedic plates are widely used for the treatment of cleft lip and palate, which is the most common craniofacial birth defect. For the traditional plate fabrication, an impression is taken under airway-endangering conditions, which recent digital alternatives overcome via intr...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284965/ https://www.ncbi.nlm.nih.gov/pubmed/37009952 http://dx.doi.org/10.1007/s11548-023-02858-6 |
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author | Schnabel, Till N. Gözcü, Baran Gotardo, Paulo Lingens, Lasse Dorda, Daniel Vetterli, Frawa Emhemmed, Ashraf Nalabothu, Prasad Lill, Yoriko Benitez, Benito K. Mueller, Andreas A. Gross, Markus Solenthaler, Barbara |
author_facet | Schnabel, Till N. Gözcü, Baran Gotardo, Paulo Lingens, Lasse Dorda, Daniel Vetterli, Frawa Emhemmed, Ashraf Nalabothu, Prasad Lill, Yoriko Benitez, Benito K. Mueller, Andreas A. Gross, Markus Solenthaler, Barbara |
author_sort | Schnabel, Till N. |
collection | PubMed |
description | PURPOSE: Presurgical orthopedic plates are widely used for the treatment of cleft lip and palate, which is the most common craniofacial birth defect. For the traditional plate fabrication, an impression is taken under airway-endangering conditions, which recent digital alternatives overcome via intraoral scanners. However, these alternatives demand proficiency in 3D modeling software in addition to the generally required clinical knowledge of plate design. METHODS: We address these limitations with a data-driven and fully automated digital pipeline, endowed with a graphical user interface. The pipeline adopts a deep learning model to landmark raw intraoral scans of arbitrary mesh topology and orientation, which guides the nonrigid surface registration subsequently employed to segment the scans. The plates that are individually fit to these segmented scans are 3D-printable and offer optional customization. RESULTS: With the distance to the alveolar ridges closely centered around the targeted 0.1 mm, our pipeline computes tightly fitting plates in less than 3 min. The plates were approved in 12 out of 12 cases by two cleft care professionals in a printed-model-based evaluation. Moreover, since the pipeline was implemented in clinical routine in two hospitals, 19 patients have been undergoing treatment utilizing our automated designs. CONCLUSION: The results demonstrate that our automated pipeline meets the high precision requirements of the medical setting employed in cleft lip and palate care while substantially reducing the design time and required clinical expertise, which could facilitate access to this presurgical treatment, especially in low-income countries. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11548-023-02858-6. |
format | Online Article Text |
id | pubmed-10284965 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-102849652023-06-23 Automated and data-driven plate computation for presurgical cleft lip and palate treatment Schnabel, Till N. Gözcü, Baran Gotardo, Paulo Lingens, Lasse Dorda, Daniel Vetterli, Frawa Emhemmed, Ashraf Nalabothu, Prasad Lill, Yoriko Benitez, Benito K. Mueller, Andreas A. Gross, Markus Solenthaler, Barbara Int J Comput Assist Radiol Surg Original Article PURPOSE: Presurgical orthopedic plates are widely used for the treatment of cleft lip and palate, which is the most common craniofacial birth defect. For the traditional plate fabrication, an impression is taken under airway-endangering conditions, which recent digital alternatives overcome via intraoral scanners. However, these alternatives demand proficiency in 3D modeling software in addition to the generally required clinical knowledge of plate design. METHODS: We address these limitations with a data-driven and fully automated digital pipeline, endowed with a graphical user interface. The pipeline adopts a deep learning model to landmark raw intraoral scans of arbitrary mesh topology and orientation, which guides the nonrigid surface registration subsequently employed to segment the scans. The plates that are individually fit to these segmented scans are 3D-printable and offer optional customization. RESULTS: With the distance to the alveolar ridges closely centered around the targeted 0.1 mm, our pipeline computes tightly fitting plates in less than 3 min. The plates were approved in 12 out of 12 cases by two cleft care professionals in a printed-model-based evaluation. Moreover, since the pipeline was implemented in clinical routine in two hospitals, 19 patients have been undergoing treatment utilizing our automated designs. CONCLUSION: The results demonstrate that our automated pipeline meets the high precision requirements of the medical setting employed in cleft lip and palate care while substantially reducing the design time and required clinical expertise, which could facilitate access to this presurgical treatment, especially in low-income countries. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11548-023-02858-6. Springer International Publishing 2023-04-02 2023 /pmc/articles/PMC10284965/ /pubmed/37009952 http://dx.doi.org/10.1007/s11548-023-02858-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Schnabel, Till N. Gözcü, Baran Gotardo, Paulo Lingens, Lasse Dorda, Daniel Vetterli, Frawa Emhemmed, Ashraf Nalabothu, Prasad Lill, Yoriko Benitez, Benito K. Mueller, Andreas A. Gross, Markus Solenthaler, Barbara Automated and data-driven plate computation for presurgical cleft lip and palate treatment |
title | Automated and data-driven plate computation for presurgical cleft lip and palate treatment |
title_full | Automated and data-driven plate computation for presurgical cleft lip and palate treatment |
title_fullStr | Automated and data-driven plate computation for presurgical cleft lip and palate treatment |
title_full_unstemmed | Automated and data-driven plate computation for presurgical cleft lip and palate treatment |
title_short | Automated and data-driven plate computation for presurgical cleft lip and palate treatment |
title_sort | automated and data-driven plate computation for presurgical cleft lip and palate treatment |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284965/ https://www.ncbi.nlm.nih.gov/pubmed/37009952 http://dx.doi.org/10.1007/s11548-023-02858-6 |
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