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Record W4365483258 · doi:10.1111/cid.13205

Evaluation of surgical placement accuracy of customized <scp>CAD</scp>/<scp>CAM</scp> titanium mesh using screws‐position‐guided template: A retrospective comparative study

2023· article· en· W4365483258 on OpenAlexvenueno aff
D. Chen, Lingling Zheng, Chao Wang, Yuanding Huang, Haitao Huang, Antonio Apicella, Guiping Hu, Lizhen Wang, Yubo Fan

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2023
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesHigher Education Discipline Innovation ProjectNatural Science Foundation of Beijing MunicipalityNational Natural Science Foundation of China
KeywordsPolygon meshRetainerVolume (thermodynamics)Computer scienceDental alveolusCone beam computed tomographyCADPeriosteumPosition (finance)MedicineOrthodonticsBiomedical engineeringEngineering drawingSurgeryComputed tomographyMaterials scienceComputer graphics (images)Engineering

Abstract

fetched live from OpenAlex

BACKGROUND: Customized computer-aided-design/computer-aided-manufacturing (CAD/CAM) titanium meshes have been adopted for alveolar bone augmentation. But the inaccuracies between planned and created bone volume/contour are quite common, and the surgical placement of the customized mesh was considered as the first critical factor. However, the evaluation of surgical placement accuracy of customized mesh is currently lacking. PURPOSE: The aim of this study was to evaluate the accuracy of the surgical placement of customized meshes. METHODS: A total of 30 cases, 20 without the screws-position-guided template and 10 with the screws-position-guided template, were included in this study. The cone beam CT (CBCT) data sets of pre- and postoperative were converted into 3D models and digitally aligned. Then the actual placement of customized mesh and retainer titanium screws was compared to the virtual one to assess the surgical placement accuracy of customized mesh. At least 6 months after surgery, a new CBCT was taken and converted into 3D models. Planned bone volume, created bone volume, vertical bone augmentation, healing complications rate, pseudo-periosteum rate, exposure rate, and infection rate were all evaluated. RESULTS: The 3D digital reconstruction/registration analysis showed that the average difference between actual placement and planned one of customized mesh in positive and negative directions was 2.69 ± 0.70 mm and -1.41 ± 0.90 mm, respectively, without the screws-position-guided template. And the mean difference values between the actual and planned placement of the screws on the X and Y axes were 0.74 ± 0.85 mm and 0.89 ± 0.84 mm. In contrast, with the screws-position-guided template, the results were 2.38 ± 0.69 mm and -1.30 ± 1.13 mm. Accordingly, the mean difference values of screws were 0.76 ± 0.84 mm and 0.94 ± 0.72 mm. There was no statistical difference between the two groups, and the noninferiority of the control group compared to the test group was also confirmed by the comparative analysis. CONCLUSION: It can be concluded that there is a certain deviation between the planned surgical placement and actual one of customized mesh, and using screws-position-guided template is of limited help for its accurate placement. Further research is needed to achieve precise surgical placement of the customized mesh to achieve precise alveolar bone augmentation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.310
GPT teacher head0.537
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2023
Admission routes1
Has abstractyes

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