Evaluation of a universal talus implant during gait: a combined musculoskeletal and finite element modelling approach
Bibliographic record
Abstract
Universal talus implant has emerged as an innovative solution for talus bone collapse, aiming to retain the clinical benefits of custom total talus replacement while addressing its logistical drawbacks. A subject-specific combined musculoskeletal–finite element (MSK–FE) modeling framework was developed to evaluate two universal talus implant designs during dynamic gait: a purely cobalt chromium (CoCr) implant, and an implant coated with polycarbonate-urethane (PCU), both compared to the native talus. To do so, a MSK simulation of the stance phase of gait was conducted to estimate joint kinematics and joint reaction forces in the ankle complex, with a subsequent dynamic FE simulation performed to assess contact characteristics in terms of contact area and pressure, in cartilages surrounding the talus/implant. The FE model was built directly from the bone geometries of the MSK model to ensure consistency across the study. Results showed that the PCU-coated implant more closely replicated native biomechanics, while the CoCr implant produced consistently higher pressures and smaller contact regions. Normalized RMSE across gait confirmed lower deviation from the native case for the PCU-implant in most joints. These findings highlight the potential of PCU coated implants in improving contact mechanics in articular cartilage as well as the potential of the universal implant topology. This is the first study to dynamically evaluate intra-articular behaviour in all joints surrounding the talus bone during gait, and particularly by analysing the performance of universal talus implants, demonstrating the utility of a MSK-FE approach and offering valuable insights into implant performance under physiological conditions, informing future implant design. • Analysis of contact characteristics in the ankle complex during gait • A combined, subject-specific, musculoskeletal and finite element modelling approach • Evaluation of two universal talus implant designs: metallic and PCU-coated • The metallic implant resulted in highest contact pressures and smallest contact areas • PCU-coated implant performs similarly to the biological talus
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".