An Accuracy Study of Computer‐Planned Implant Placement in the Augmented Maxilla Using Mucosa‐Supported Surgical Templates
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to determine the clinically relevant accuracy of implant placement in the augmented maxilla using computer planning and a mucosa-supported surgical template. MATERIALS AND METHODS: Twenty-five consecutive edentulous patients with an extreme maxillar alveolar ridge resorption were treated with a bone augmentation procedure. In a second stage, six Brånemark MkIII Groovy (Nobel Biocare®, Zürich, Switzerland) implants were installed. Preoperatively, a cone beam computer tomography (CBCT) scan was acquired, followed by virtual implant planning and flapless implant placement using a surgical template. A postoperative CBCT scan was acquired and registered to the preoperative scan. The Implant Position Orthogonal Projection validation method was applied to measure implant deviations in both the buccolingual and mesio-distal plane. The influence of fixation pins and the position on the dental arch were investigated with regard to implant deviations, and rotations and translations of the surgical template. RESULTS: One hundred fifty implants were installed. In mesio-distal direction, a mean implant deviation of 1.50 mm was scored at the implant tip, 1.27 mm at the shoulder, -0.60 mm in depth, as well as a mean deviation of angulation of 2.50°. In buccolingual direction, a mean implant deviation of 0.99 mm was found at the implant tip, 0.76 mm at the implant shoulder, -0.57 mm in depth, and a deviation of angulation of 2.48°. Of all implants, 53% was placed too superficial compared with the planning. The use of fixation pins and implant deviations in both buccal and mesial directions as also for rotations and translation of the surgical template showed statistically significant differences. CONCLUSIONS: Computer-aided implant planning showed to be a clinically relevant tool. However, this study emphasizes that the surgeon should take into account that deviations are larger compared with implant placement without augmentation procedure. Deviations are mainly caused by angulations and translations of the surgical template.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".