A Novel Methodology to Estimate Bone Mechanical Properties Using Dual-Energy Imaging to Improve Pedicle Screw Fixation.
Bibliographic record
Abstract
OBJECTIVE: To develop a methodology to improve the representation of the mechanical properties of a vertebral finite element model (FEM) based on a new dual-energy (DE) imaging technology to improve pedicle screw fixation. METHODS: Bone-calibrated radiographs were generated with dual-energy imaging technology in order to estimate the mechanical properties of the trabecular bone. Properties were included in regions of interest in four vertebral FEMs representing heterogeneity and homogeneity, as a realistic and reference model, respectively. Biomechanical parameters were measured during screw pull-out testing to evaluate pedicle screw fixation. RESULTS: Simulations with property distributions deduced from dual-energy imaging characterization (heterogeneous models) induced an increase in biomechanical indicators versus with a homogeneous representation, implying different behaviors for the subject-specific models. CONCLUSION: The presented methodology allows a patient-specific representation of bone quality in a FEM using new DE imaging technology. Consideration of individualized bone distribution in a spinal FEM improves the perspective of orthopedic surgical planning over otherwise underestimated results using a homogeneous representation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".