Assessment of Bone Density in the Posterior Maxilla Based on Hounsfield Units to Enhance the Initial Stability of Implants
Bibliographic record
Abstract
PURPOSE: The poor bone quality that exists in the posterior maxilla is associated with lower initial stability and higher failure rates in implants. This study examined the bone densities of edentulous posterior maxillae by computed tomography (CT). MATERIALS AND METHODS: Based on CT images, the voxel values representing implant replacement in the posterior maxillary regions of 30 patients were calculated in the range from 150 to 2,000 Hounsfield units (HU). The bone densities of these regions were categorized according to Misch's classification and compared among individuals and between sexes. RESULTS: The average of the median individual CT values was 495 HU (95% confidence interval: 442-547 HU) and was significantly higher in males than in females. Most of the bone in the posterior maxillae was classified as D3 (350-850 HU) or D4 (150-350 HU) according to Misch's classification, comprising 50% and 32% of the entire regions, respectively. CONCLUSIONS: More than 80% of the edentulous posterior maxillae consisted of porous cortical crest or no cortical bone according to CT, although the bone densities varied markedly among individuals. More detailed assessments of bone density may be useful to enhance initial stability of implants in the posterior 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.002 | 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".