A NOVEL METHOD FOR MEASURING CIRCUMFERENTIAL 3D MOTION OF CEMENTLESS TIBIAL TRAYS DURING SIMULATION OF FUNCTIONAL LOADING
Bibliographic record
Abstract
INTRODUCTION Stable fixation of cementless tibial trays remains a challenge due bone density variability within the proximal tibia and the spectrum of loads imposed by different activities. This study presents a novel approach to measuring the interface motion of cementless tibial components during functional loading and tests whether interface motion of cementless tibial trays varies around the implant periphery. METHODS We developed a method to measure relative displacement of a tibial tray relative to the underlying bone using 3D digital image correlation (DIC) and multi-camera stereo photogrammetry. A clinically successful design of cementless total knee prosthesis (Zimmer Inc, Warsaw, IN) was implanted in 6 fresh cadaveric knees. A black-on-white stochastic pattern was applied to the outer surface of the tibia and the cementless prosthesis. High resolution digital images were prepared of the interface region and divided into 25 × 25 pixel regions of interest (ROI). Stereo images of the same ROI were generated using two cameras angled at 60 degrees using image correlation techniques. All specimens were mounted in a custom-built functional activity simulator and loaded with the forces and moments recorded during three common functional activities (standing from a seated position, walking, and stair descent), as reported in the Orthoload database, scaled by 50% for application to cadaveric bone. Prior to functional testing, each implant-tibia construct was preconditioned with 500 cycles of flexion from 5–100 degrees under a vertical tibial load of 1050 N at a frequency of 0.2 Hz. During loading, image data was acquired simultaneously (±20 μs) from the entire circumference of the tibial interface forming 4 stereo images using 8 cameras spaced at 90 degree intervals (Allied Vision Technologies, Exton, PA) using custom image acquisition software (Mathworks, Natick, MA) (Figure 1). The multiple stereo images were registered using the surface topography of each specimen as measured by laser scanning (FARO Inc., Montreal) (Figure 2). During post-processing, the circumferential tray/tibia interface was divided into 10 zones for subsequent analysis (Figure 3). Interface displacements were measured on a point-to-point basis at approximately 700 sites on each specimen using commercial DIC software (Dantec Dynamics, Skovlunde, Denmark) (Figure 4). RESULTS The average 3D displacement over 10 circumferential zones of the tray was 83.6±41.5 μm (range: 30.8 to 214.9 μm). The anatomic components of tray migration were 0.4±40.8 μm medially (range: 172 μm lateral to 112 μm medial) and 3.1± 40.6 μm posteriorly (range: 86 μm posteriorly to 61 μm anteriorly). The largest tray displacement was observed in the inferior direction with an average inferior displacement of 37.6±63.8 μm (range: 206 μm inferiorly to 81μm superiorly). The largest displacements were observed posteriorly, with the posteromedial aspect subsiding more the posterolateral aspect. DISCUSSION The stability of tibial trays cannot be accurately assessed by measuring interface motion at a few fixed peripheral sites. If discrete displacement transducers are used for pre-clinical testing, a set of 4–6 transducers should be placed at sites that vary with the pattern of interface motion of each design and the combination of loads and moments applied during testing.
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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 | 0.001 |
| 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) | 0.002 | 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".