Design of a lightweight universal talus implant using topology optimization
Bibliographic record
Abstract
Total talus replacement is a promising alternative treatment for talus fractures complicated by avascular necrosis and collapse. This surgical option replaces the human talus bone with a customized talus implant and can maintain ankle joint functionality compared to traditional treatment (e.g., ankle fusion). However, the customized implant is costly and time-consuming due to its customized nature. To circumvent these drawbacks, universal talus implants were proposed. While they showed clinically satisfactory results, existing talus implants are heavier than biological talus bones as they are solid inside. This can lead to unequal weight between the implant and biological talus bone, and therefore leading to other complications. The reduction of the implants’ weight without compromising its performance and congruency with surrounding bones is a potential solution. Therefore, this study aims to design a lightweight universal talus implant using topology optimization. This is done through establishing the loading and boundary conditions for three common foot postures: neutral, dorsi- and plantar-flexion. The optimized implant performance in terms of mass, contact characteristics with surrounding joint cartilage and stress distributions is studied using a 3D Finite Element (FE) model of the ankle joint. The mass of the optimized implant is reduced by approximately 66.6% and its maximum stresses do not exceed 70 MPa, resulting in a safety factor of 15.7. Moreover, the optimized and solid implants show similar contact characteristics. Both implants produced peak contact pressures that were approximately 19.0%–196% higher than those produced by the biological talus. While further mechanical testing under in-vivo loading conditions is required to determine clinical feasibility, preliminarily, the use of a lightweight universal implant is expected to provide the patient with a more natural feel, and a reduced waiting period until surgery.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".