Computer‐Aided Design Evaluation of Harvestable Mandibular Bone Volume: A Clinical and Tomographic Human Study
Bibliographic record
Abstract
PURPOSE: To evaluate and compare the volume of bone graft material that can be safely harvested from the mandibular symphysis and rami using a computer-aided design (CAD) software program. MATERIALS AND METHODS: Preoperative computerized tomography scans from 40 patients undergoing bone augmentation procedures were analyzed. Symphysis and rami cross sections were mapped using a CAD software program (AutoCAD(®), Autodesk, Inc., San Rafael, CA, USA) to evaluate the bone volume that can be safely harvested. CAD calculations were contrasted to intrasurgical measurements in a subgroup of 20 individuals. RESULTS: CAD calculations yielded a safe harvestable osseous volume of 1.44 cm(3) ± 0.49 for the symphysis and 0.82 cm(3) ± 0.21 for each ramus (p < .0001, confidence interval [CI] 95%: 0.47-0.78). These measurements were significantly lower (p < .0001) than the bone volumes harvested intrasurgically for both symphysis and ramus, respectively (2.40 cm(3) ± 0.50 vs. 2.65 cm(3) ± 0.45). CAD calculations of harvestable symphysis and ramus bone translated into an average of 2.40 cm(3) ± 0.50 (range: 1.80-3.10 cm(3)) and 2.65 cm(3) ± 0.45 (range: 1.90-3.50) of particulate bone graft intrasurgically, respectively. Ramus cortical was significantly thicker than the symphysis cortical, 2.9 ± 0.4 mm versus 2.19 mm ± 0.4 mm (p < .0001, CI 95%: 0.45-1.03). CONCLUSION: The symphysis and rami are good harvesting sources to obtain dense corticocancellous bone. The significant volumetric CAD differences between the symphysis and ramus seem to balance out intrasurgically and may be due to the greater cortical bone volume at the ramus area. It is plausible to harvest an average of 7.70 cm(3) from the symphysis and rami alone. The use of a CAD software program can enhance surgical treatment planning prior to bone transplantation.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".