The effects of implant angulation on the resonance frequency of a dental implant
Bibliographic record
Abstract
Dental implants are ideally placed in an orientation that allows vertical transfer of occlusal forces along their long axis. Nevertheless, optimal situations for implant placement are seldom encountered resulting in implants placement in angulated positions, which may affect their long-term success. The resonance frequency (RF) is an objective tool used to monitor stability of the implant tissue integration; however, little is known of the effect of the implant orientation in bone on the RF and its potential significance. The purpose of this research was to determine the relation between the dental implant orientation and the corresponding RF of implant. Three-dimensional (3D) modelling software was used to construct a 3D model of a pig mandible from computed tomography (CT) images. The RF of the implant was analysed using finite element (FE) modal analysis in software ANSYS (v.12). In addition, a cubical model was also developed in MIMICS to investigate the parameters affecting the relationship between RF and implant orientation in a simplified environment. The orientation angle was increased from 0 to 10 degrees in 1 degree increments and the resulting RF was analysed using correlation analysis and one-way ANOVA. Our analysis illustrated that the RF fluctuation following altering implant orientation was strongly correlated (r=0.97) with the contacting cortical to cancellous bone ratio (CCBR) at the implant interface. The most extreme RF change (from 9.81kHz to 10.07kHz) occurred when the implant was moved 0.5mm in positive z-direction, which resulted in the maximum change of CCBR from 52.9 to 54.8.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".