Comparison of the accuracy of two different dynamic navigation system registration methods for dental implant placement: A retrospective study
Bibliographic record
Abstract
BACKGROUND: Dynamic navigation approaches are widely employed in the context of implant placement surgery, with registration being integral to the accuracy of such navigation. Relatively few studies to date, however, have compared different registration approaches, and such a comparison has the potential to guide the development of more accurate and reliable clinical registration methodology. PURPOSE: This study was developed to compare the accuracy of dynamic navigation-based dental implant placement conducted using either U-tube or cusp registration methods. MATERIALS AND METHODS: Medical records from all patients that had undergone implant surgery between August 2019 and October 2020 in the First Clinical Division of the Peking University Hospital of Stomatology were retrospectively reviewed, with 64 patients and 99 implants ultimately meeting with study inclusion criteria. Implant placement accuracy was gauged via the superimposition of the planned implant position in preoperative cone-beam computed tomography (CBCT) images with the true postoperative implant position in postoperative CBCT images. Accuracy was measured based upon the angular deviation, entry deviation (3-dimensional [3D] deviation in the coronal aspect of the alveolar ridge), and apex deviation (3D deviation in the apical area of the implant) when comparing these two positions. RESULTS: The angular deviation, entry deviation, and apex deviation of all analyzed implants were 3.29 ± 0.17°, 1.29 ± 0.07 mm, and 1.43 ± 0.08 mm, respectively, while in the cusp registration group these respective values were 3.25 ± 1.58°, 1.28 ± 0.60 mm, and 1.34 ± 0.63 mm as compared to 3.35 ± 1.78°, 1.30 ± 0.78 mm, 1.55 ± 0.9 mm in the U-tube group, respectively. No significant differences in accuracy were observed when comparing these two registration techniques. CONCLUSION: Dynamic computer-assisted surgical systems can facilitate accurate implantation, and both the U-tube and cusp registration methods exhibit similar levels of accuracy. As the cusp registration technique can overcome some of the limitations of the U-tube strategy without the need for an additional registration device, it may be more convenient for clinical use and warrants further research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".