Accuracy of dental implant placement using augmented reality-based navigation, static computer assisted implant surgery, and the free-hand method: An in vitro study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: This in vitro study aimed to compare the accuracy of implant placement in model surgeries carried out by implementation of three different methods. METHODS: An in vitro study was conducted on 3D printed study models randomly assigned to three study groups. In Group 1, model surgeries were assisted by augmented reality (AR)based dynamic navigation (Innooral System, Innoimplant Ltd, Budapest, Hungary). In Group 2, implants were placed with a free-hand method, and in Group 3, static Computer Assisted Implant Surgery (CAIS) was used (coDiagnostiX software, version 10.4 Dental Wings, Montreal, CA, USA). A total of 48 dental implants (Callus Pro, Callus Implant Solutions GmbH, Hamburg, Germany) were placed (16 implants in four models per study group). The primary outcome variables were angular deviation, coronal, and apical global deviation. These were calculated for all implants based on preoperative registration of the surgical plan and postoperative cone beam computed tomography (CBCT) reconstruction. RESULTS: The accuracy of implant placement using AR-based dynamic navigation showed no significant difference compared to static CAIS (angular deviation, 4.09 ± 2.79° and 3.21 ± 1.52°; coronal deviation, 1.27 ± 0.40 mm and 1.31 ± 0.42 mm; and apical global deviation 1.34 ± 0.41 mm and 1.38 ± 0.41 mm). Global deviation results were significantly lower with AR-based dynamic navigation than with the free-hand approach (coronal and apical global deviation of 1.93 ± 0.79 mm and 2.28 ± 0.74 mm, respectively). CONCLUSIONS: Implant positioning accuracy of AR-based dynamic navigation was comparable to that of static CAIS and superior to that obtained by the free-hand approach. CLINICAL SIGNIFICANCE: Implementing Augmented Reality based dynamic Computer Assisted Implant Surgery (CAIS) in model surgeries may allow to obtain an implant positioning accuracy comparable to that provided by static CAIS, and superior to that obtained through the free-hand approach. Further clinical studies are necessary to determine the feasibility of AR-based dynamic navigation.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it