Automated Support Generation for Fixed Partial Dentures and Impact of Bone Loss, Bone Quality and Support Types: Parametric Cad and Finite Element Analysis

<b>Background:</b> This study aimed to develop an algorithm for modelling tooth-tooth or implant-implant support configurations for a given 4-unit fixed partial denture (FPD). <b>Methods</b>: The algorithm was implemented in Rhinoceros/Grasshopper to automatically generate geometries with varying bone loss (0 mm to 3 mm), support type (tooth-tooth and implant-implant support) and bone quality (D1 to D4) for a 4-unit FPD. Afterward, a finite element analysis was carried out with a load applied to the central connector of the FPD. Stresses in the FPD and the bone around the support were analysed. <b>Results</b>: The results indicated that stresses in the bone were influenced by both the depth of bone loss and bone quality across both support types. The maximum stress in the tested FPD models for tooth-tooth support was not significantly influenced by bone quality; instead, the stress peaks were primarily influenced by the depth of bone loss. For D1 bone, the stresses in FPD and bone increased by 4.79% and 8.86%, respectively, for tooth-tooth support and about 32.67% and 100.96%, respectively, for implant-implant support. <b>Conclusions</b>: The proposed algorithm allows for the automatic, parametrised generation of support for 4-unit fixed partial dentures, which can be used to predict the effect of bone loss and bone quality on stresses for patient-specific geometries. The optimal treatment for support type should be adapted to the patient's specific needs to ensure long-term stability. A decision support involving automatic modelling, e.g., of support, and simulation might improve clinical treatment planning from a long-term perspective.

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Publication Details

Journal
Dentistry Journal
Published
2024-12-04
DOI
https://doi.org/10.3390/dj12120394
Citations
1
Primary Topic
Dental materials and restorations
Type
article
Field-Weighted Citation Impact
0.40

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article

Automated Support Generation for Fixed Partial Dentures and Impact of Bone Loss, Bone Quality and Support Types: Parametric Cad and Finite Element Analysis

Andreas Greuling, Hassen Jemaa, Michael Eisenburger
1 citations
Dentistry Journal
Dental materials and restorations
0.40
article

Automated Support Generation for Fixed Partial Dentures and Impact of Bone Loss, Bone Quality and Support Types: Parametric Cad and Finite Element Analysis

Andreas Greuling, Hassen Jemaa, Michael Eisenburger
article en
1 citations

Abstract

<b>Background:</b> This study aimed to develop an algorithm for modelling tooth-tooth or implant-implant support configurations for a given 4-unit fixed partial denture (FPD). <b>Methods</b>: The algorithm was implemented in Rhinoceros/Grasshopper to automatically generate geometries with varying bone loss (0 mm to 3 mm), support type (tooth-tooth and implant-implant support) and bone quality (D1 to D4) for a 4-unit FPD. Afterward, a finite element analysis was carried out with a load applied to the central connector of the FPD. Stresses in the FPD and the bone around the support were analysed. <b>Results</b>: The results indicated that stresses in the bone were influenced by both the depth of bone loss and bone quality across both support types. The maximum stress in the tested FPD models for tooth-tooth support was not significantly influenced by bone quality; instead, the stress peaks were primarily influenced by the depth of bone loss. For D1 bone, the stresses in FPD and bone increased by 4.79% and 8.86%, respectively, for tooth-tooth support and about 32.67% and 100.96%, respectively, for implant-implant support. <b>Conclusions</b>: The proposed algorithm allows for the automatic, parametrised generation of support for 4-unit fixed partial dentures, which can be used to predict the effect of bone loss and bone quality on stresses for patient-specific geometries. The optimal treatment for support type should be adapted to the patient's specific needs to ensure long-term stability. A decision support involving automatic modelling, e.g., of support, and simulation might improve clinical treatment planning from a long-term perspective.

Dentistry JournalVol. 12(12)
Medizinische Hochschule Hannover (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 39%
Dental materials and restorations
0.40
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