Development and evaluation of a noninvasive vibration modeling technique for primary stability measurement in artificial cortical bone blocks
Bibliographic record
Abstract
Statement of problem Noninvasive methods of quantifying stability are important for monitoring implant health. Current techniques are unable to provide a universal measurement of stability. The Advanced System for Implant Stability Testing (ASIST) is a device that noninvasively measures implant stability by analyzing the vibration response of the implant system to estimate the interfacial stiffness, reported as the ASIST Stability Coefficient (ASC). Purpose The aim of this in vitro study was to determine whether implant stability can be measured as the interfacial stiffness with a refined analytical model that accounts for cortical and cancellous layers. Material and methods Bone-level tapered implants were placed in polyurethane foam comprised of 2 layers mimicking cortical and cancellous bone. Cancellous bone was simulated with 320 kg/m 3 foam, while cortical bone was simulated with 3 densities (480, 640, 800 kg/m 3 ) and 3 thicknesses (1, 2, 3 mm) for a total of 9 experimental groups. Each group contained 10 specimens. The stability of each implant was measured with the ASC, Implant Stability Quotient (ISQ), insertion torque (IT), and pullout test. Two-way ANOVA was used to compare stability values across groups of the same cortical density and thickness (α=.05). The Dunnett test was also used to compare experimental groups with a control group (n=10) of purely cancellous foam (320 kg/m 3 ). Correlations between outcome measurements were described with the Pearson correlation coefficient. Results ASC values followed similar trends with IT and pullout force (PF) measurements where varying the cortical density had the largest effect on stability values at the highest cortical thickness and vice versa. The control group showed values similar to those of the groups with a 1-mm cortical thickness. However, ISQ values significantly increased with cortical thickness ( P <.001) but did not change significantly with cortical density ( P =.265). Strong correlations were observed between the IT and pullout force ( r =0.946), ASC and IT ( r =0.872), and ASC and pullout force ( r =0.917). Weaker correlations were observed between the ISQ and IT ( r =0.495), and ISQ and pullout force ( r =0.552). Conclusions With the refined analytical model, ASC values were comparable with trends in IT and PF, with stronger correlations compared with the ISQ. Within the confines of this controlled in vitro study, the results suggest that the ASIST may provide an improved estimate of an implant's mechanical stability. However, further work with real bone, other implant systems, and human participants is warranted before its clinical feasibility can be assessed.
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".