A Novel Method for Digital Reconstruction of the Mucogingival Borderline in Optical Scans of Dental Plaster Casts
Adequate soft-tissue dimensions have been shown to be crucial for the long-term success of dental implants. To date, there is evidence that placement of dental implants should only be conducted in an area covered with attached gingiva. Modern implant planning software does not visualize soft-tissue...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | Journal of Clinical Medicine |
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| Online Access: | https://www.mdpi.com/2077-0383/11/9/2383 |
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| author | Leonard Simon Brandenburg Stefan Schlager Lara Sophie Harzig David Steybe René Marcel Rothweiler Felix Burkhardt Benedikt Christopher Spies Joachim Georgii Marc Christian Metzger |
| author_facet | Leonard Simon Brandenburg Stefan Schlager Lara Sophie Harzig David Steybe René Marcel Rothweiler Felix Burkhardt Benedikt Christopher Spies Joachim Georgii Marc Christian Metzger |
| author_sort | Leonard Simon Brandenburg |
| collection | DOAJ |
| description | Adequate soft-tissue dimensions have been shown to be crucial for the long-term success of dental implants. To date, there is evidence that placement of dental implants should only be conducted in an area covered with attached gingiva. Modern implant planning software does not visualize soft-tissue dimensions. This study aims to calculate the course of the mucogingival borderline (MG-BL) using statistical shape models (SSM). Visualization of the MG-BL allows the practitioner to consider the soft tissue supply during implant planning. To deploy an SSM of the MG-BL, healthy individuals were examined and the intra-oral anatomy was captured using an intra-oral scanner (IOS). The empirical anatomical data was superimposed and analyzed by principal component analysis. Using a Leave-One-Out Cross Validation (LOOCV), the prediction of the SSM was compared with the original anatomy extracted from IOS. The median error for MG-BL reconstruction was 1.06 mm (0.49–2.15 mm) and 0.81 mm (0.38–1.54 mm) for the maxilla and mandible, respectively. While this method forgoes any technical work or additional patient examination, it represents an effective and digital method for the depiction of soft-tissue dimensions. To achieve clinical applicability, a higher number of datasets has to be implemented in the SSM. |
| first_indexed | 2024-03-10T04:02:39Z |
| format | Article |
| id | doaj.art-a6413c67061440538ded1e5ce8bd9a21 |
| institution | Directory Open Access Journal |
| issn | 2077-0383 |
| language | English |
| last_indexed | 2024-03-10T04:02:39Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Clinical Medicine |
| spelling | doaj.art-a6413c67061440538ded1e5ce8bd9a212023-11-23T08:31:32ZengMDPI AGJournal of Clinical Medicine2077-03832022-04-01119238310.3390/jcm11092383A Novel Method for Digital Reconstruction of the Mucogingival Borderline in Optical Scans of Dental Plaster CastsLeonard Simon Brandenburg0Stefan Schlager1Lara Sophie Harzig2David Steybe3René Marcel Rothweiler4Felix Burkhardt5Benedikt Christopher Spies6Joachim Georgii7Marc Christian Metzger8Medical Center—University of Freiburg, Center for Dental Medicine, Department of Oral and Maxillofacial Surgery, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, GermanyMedical Center—University of Freiburg, Center for Dental Medicine, Department of Oral and Maxillofacial Surgery, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, GermanyMedical Center—University of Freiburg, Center for Dental Medicine, Department of Oral and Maxillofacial Surgery, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, GermanyMedical Center—University of Freiburg, Center for Dental Medicine, Department of Oral and Maxillofacial Surgery, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, GermanyMedical Center—University of Freiburg, Center for Dental Medicine, Department of Oral and Maxillofacial Surgery, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, GermanyMedical Center—University of Freiburg, Center for Dental Medicine, Department of Prosthetic Dentistry, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, GermanyMedical Center—University of Freiburg, Center for Dental Medicine, Department of Prosthetic Dentistry, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, GermanyFraunhofer Institute for Digital Medicine MEVIS, Bremen, Max-von-Laue-Str. 2, 28359 Bremen, GermanyMedical Center—University of Freiburg, Center for Dental Medicine, Department of Oral and Maxillofacial Surgery, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, GermanyAdequate soft-tissue dimensions have been shown to be crucial for the long-term success of dental implants. To date, there is evidence that placement of dental implants should only be conducted in an area covered with attached gingiva. Modern implant planning software does not visualize soft-tissue dimensions. This study aims to calculate the course of the mucogingival borderline (MG-BL) using statistical shape models (SSM). Visualization of the MG-BL allows the practitioner to consider the soft tissue supply during implant planning. To deploy an SSM of the MG-BL, healthy individuals were examined and the intra-oral anatomy was captured using an intra-oral scanner (IOS). The empirical anatomical data was superimposed and analyzed by principal component analysis. Using a Leave-One-Out Cross Validation (LOOCV), the prediction of the SSM was compared with the original anatomy extracted from IOS. The median error for MG-BL reconstruction was 1.06 mm (0.49–2.15 mm) and 0.81 mm (0.38–1.54 mm) for the maxilla and mandible, respectively. While this method forgoes any technical work or additional patient examination, it represents an effective and digital method for the depiction of soft-tissue dimensions. To achieve clinical applicability, a higher number of datasets has to be implemented in the SSM.https://www.mdpi.com/2077-0383/11/9/2383statistical shape modelmucogingival borderlineimplant planningsoft tissue dimensionsvirtual planning |
| spellingShingle | Leonard Simon Brandenburg Stefan Schlager Lara Sophie Harzig David Steybe René Marcel Rothweiler Felix Burkhardt Benedikt Christopher Spies Joachim Georgii Marc Christian Metzger A Novel Method for Digital Reconstruction of the Mucogingival Borderline in Optical Scans of Dental Plaster Casts Journal of Clinical Medicine statistical shape model mucogingival borderline implant planning soft tissue dimensions virtual planning |
| title | A Novel Method for Digital Reconstruction of the Mucogingival Borderline in Optical Scans of Dental Plaster Casts |
| title_full | A Novel Method for Digital Reconstruction of the Mucogingival Borderline in Optical Scans of Dental Plaster Casts |
| title_fullStr | A Novel Method for Digital Reconstruction of the Mucogingival Borderline in Optical Scans of Dental Plaster Casts |
| title_full_unstemmed | A Novel Method for Digital Reconstruction of the Mucogingival Borderline in Optical Scans of Dental Plaster Casts |
| title_short | A Novel Method for Digital Reconstruction of the Mucogingival Borderline in Optical Scans of Dental Plaster Casts |
| title_sort | novel method for digital reconstruction of the mucogingival borderline in optical scans of dental plaster casts |
| topic | statistical shape model mucogingival borderline implant planning soft tissue dimensions virtual planning |
| url | https://www.mdpi.com/2077-0383/11/9/2383 |
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