Repeatability of a novel technique for in vivo measurement of three‐dimensional patellar tracking using magnetic resonance imaging
Bibliographic record
Abstract
PURPOSE: To determine the repeatability of a novel noninvasive MRI-based technique for measuring patellofemoral kinematics in vivo. MATERIALS AND METHODS: The patellar kinematics measurement method relies on registering bone models (with associated coordinate systems) developed from a high resolution MRI scan to loaded bone positions derived from fast, low resolution MRI scans. The intrasubject variability, high resolution to low resolution registration error, and interexperimenter repeatability were quantified in experiments on three healthy subjects. RESULTS: The intrasubject variability and registration error were within range of the accuracy of our procedure; specifically, less than or equal to 1.40 degrees for orientation and 0.81 mm for translation. The interexperimenter repeatability was less than or equal to 1.28 degrees for orientation, with the exception of patellar spin, and 0.68 mm for translation. CONCLUSION: Our novel measurement technique can measure three-dimensional patellar tracking noninvasively during loaded flexion in a repeatable manner. Our results compare well to another noninvasive tracking protocol, fast phase-contrast MRI, which has a reported subject interexam variability of 2.4 degrees or less for patellar orientation. A particular strength of our method is that axes and high-resolution bone models need only be determined once for intrasubject comparisons. The method is sufficiently accurate and repeatable to detect clinically significant changes in patellofemoral kinematics.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".