Computer‐guided calvarial mono‐cortical bone blocks harvest: A novel approach for three‐dimensional alveolar reconstruction of atrophic maxilla
Bibliographic record
Abstract
BACKGROUND: Calvarial bone grafts have been one of the grafting options that provides predictable results for three-dimensional reconstruction of severely atrophied ridges owing to their low resorption and rapid revascularization, thus providing adequate volume for implant insertion. The aim of this study was to introduce a computer-guided technique for calvarial graft harvest to minimize the complications known with grafting from this donor site. MATERIALS AND METHODS: Eight patients, suffering from severely atrophied, completely edentulous maxillary ridges, with an age range (21-30 years) were operated on (six males and two females). A custom-made guide for each patient based on preoperative computed tomography (CT) was fabricated for harvesting the outer table cortical bone blocks from the parietal bone, then particulate bone was collected with an auto-chip maker. Bilateral sinus lifting was indicated in all cases. The bone blocks were fixed intraorally and the bone particulates filled the gaps and the volume created by sinus lifting, then the whole complex was covered with collagen membranes fixed with titanium tacks. Immediate and 6 months CT were requested for evaluation of the guide accuracy and the graft integration, respectively. RESULTS: In all cases, the guide was found to accurately fit into its preplanned position and to correctly locate the anticipated harvest site with the needed dimensions of the bone blocks. No intraoperative complications were encountered such as breakage through the inner table or cerebrospinal fluid leakage. Postoperatively, all the cases showed uneventual healing except one case that had an anterior dehiscence. CONCLUSION: The computer-guided calvarial bone blocks harvest from the parietal bone is safe and predictable technique for three-dimensional reconstruction of severely atrophic edentulous maxilla.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".