Peri‐Implant Bone Density in Senile Osteoporosis‐Changes from Implant Placement to Osseointegration
Bibliographic record
Abstract
PURPOSE: The aim of this study was to examine healing over time after implant body placement in a senile osteoporosis model and a control group. MATERIALS AND METHODS: In this study, 16-week-old male mice were used. The senile osteoporosis model consisted of senescence-accelerated prone 6 mice and the control group consisted of senescence-accelerated resistant 1 mice. Titanium-coated plastic implants were used as experimental implants whose dimensions were 3.0 mm in length, 1.1 mm in apical diameter, and 1.2 mm in coronal diameter. Bone samples were collected at 5, 7, 14, 21, and 28 days after implant placement. A micro-quantitative computed tomography (QCT) system was used to scan these samples and a phantom in order to quantitate bone mineral measurements. Bone mineral density (BMD) of each sample was measured. Each sample was also examined by light microscopy after QCT imaging. At 14 and 28 days after implant placement, the bone-implant contact (BIC) ratios were calculated from light microscopy images and were divided into cortical bone and bone marrow regions. RESULTS: When BMD was compared between the osteoporosis and control groups using micro-QCT, the osteoporosis group had a significantly lower BMD in the region 0-20 µm from the implant surface in the bone marrow region at 14 days onward after implant placement. Compared with the control group, the osteoporosis model also had significantly lower BMD in all regions 0-100 µm from the implant surface in the bone marrow region at 14 days after placement. However, in the cortical bone region, no statistically significant difference was observed in the regions at the bone-implant interface. Light microscopy revealed osseointegration for all implants 28 days after implant placement. The osteoporosis model tended to have lower BICs compared with that of the control group, although this did not reach statistical significance. DISCUSSION: Our results showed that osseointegration was achieved in the osteoporosis model. However, the BMD was 30-40% lower than that of the control group in the region closest to the implant surface in bone marrow region. Peri-implant BMD was lower in a relatively large area in the osteoporosis model during an important time for osseointegration. Therefore, this result suggests that osteoporosis might be considered as a risk factor in implant therapy. CONCLUSION: The osteoporosis model had a lower BMD than the control group in the region closest to the implant during an important time for osseointegration. This result suggests that senile osteoporosis might be a risk factor in implant therapy. However, the osteoporosis model and the control group had no difference in peri-implant BMD in the cortical bone region. This suggests that risk might be avoided by implant placement that effectively uses the cortical bone.
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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".