TKR WEAR MEASUREMENT IN 72 PATIENTS USING RADIOSTEREOMETRIC ANALYSIS
Bibliographic record
Abstract
Articulation of the polyethylene (PE) insert between the metal femoral and tibial components in total knee replacements (TKR) results in wear of the insert which can necessitate revision surgery. Continuous PE advancements have improved wear resistance and durability increasing implant longevity. Keeping up with these material advancements, this study utilises model-based radiostereometric analysis (mbRSA) as a tool to measure in vivo short-term linear PE wear to thus predict long-term wear of the insert. Radiographic data was collected from the QEII Health Sciences Centre in Halifax, NS. Data consisted of follow-up RSA examinations at post-operative, six-, 12-, and 24-month time periods for 72 patients who received a TKR. Implanted in all patients were Stryker Triathlon TKRs with a fixed, conventional PE bearing of either a cruciate retaining or posterior stabilised design. Computer-aided design (CAD) implant models were either provided by the manufacturer or obtained from 3D scanned retrieved implants. Tibial and femoral CAD models were used in mbRSA to capture pose data in the form of Cartesian coordinates at all follow-ups for each patient. Coordinate data was manually entered into a 3D modeling software (Geomagic Studio) to position the implant components in virtual space as presented in the RSA examinations. PE wear was measured over successive follow-ups as the linear change in joint space, defined as the shortest distance between the tibial baseplate and femoral component, independently for medial and lateral sides. A linear best-fit was applied to each patient9s wear data; the slope of this line determined the annual wear rate per individual patient. Wear rates were averaged to provide a mean rate of in vivo wear for the Triathlon PE bearing. Mean linear wear per annum across all 72 patients was 0.088mm/yr (SD: 0.271 mm/yr) for the medial condyle and 0.032 mm/yr (SD: 0.230 mm/yr) for the lateral condyle. Cumulative linear wear at the 2-year follow-up interval was 0.207mm (SD: 0.565mm) and 0.068mm (SD: 0.484mm) for the medial and lateral condyles, respectively. Linear PE wear measurements using mbRSA and Geomagic Studio resulted in 0.056mm/yr additional wear on the medial condyle than the lateral condyle. Large standard deviations for yearly wear rates and cumulative measurements demonstrate this method does not yet exhibit the accuracy needed to provide short-term in vivo wear measurement. Inter-patient variability from RSA examinations is likely a source of error when dealing with such small units of measure. Further analysis on patient age and body mass index may eliminate some variability in the data to improve accuracy. Despite high standard deviations, the results from this research are in proximity to previously reported linear wear measurements 0.052mm/yr and 0.054mm/yr. Linear wear analysis will continue upon completion of >100 patients, in addition to volumetric PE wear over the entire articulating surface.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 0.001 |
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".