Dynamic deformation of the femoral head occurs on weightbearing in Legg-Calves-Perthes disease
Bibliographic record
Abstract
Aims Though the pathogenesis of Legg-Calve-Perthes disease (LCPD) is unknown, repetitive microtrauma resulting in deformity has been postulated. The purpose of this study is to trial a novel upright MRI scanner, to determine whether any deformation occurs in femoral heads affected by LCPD with weightbearing. Methods Children affected by LCPD were recruited for analysis. Children received both standing weightbearing and supine scans in the MROpen upright MRI scanner, for coronal T1 GFE sequences, both hips in field of view. Parameters of femoral head height, width, and lateral extrusion of affected and unaffected hips were assessed by two independent raters, repeated at a one month interval. Inter- and intraclass correlation coefficients were determined. Standing and supine measurements were compared for each femoral head. Results Following rigorous protocol development in healthy age-matched volunteers, successful scanning was performed in 11 LCPD-affected hips in nine children, with seven unaffected hips therefore available for comparison. Five hips were in early stage (1 and 2) and six were in late stage (3 and 4). The mean age was 5.3 years. All hips in early-stage LCPD demonstrated dynamic deformity on weightbearing. Femoral head height decreased (mean 1.2 mm, 12.4% decrease), width increased (mean 2.5 mm, 7.2% increase), and lateral extrusion increased (median 2.5 mm, 23% increase) on standing weightbearing MRI compared to supine scans. Negligible deformation was observed in contra-lateral unaffected hips, with less deformation observed in late-stage hips. Inter- and intraclass reliability for all measured parameters was good to excellent. Conclusion This pilot study has described an effective novel research investigation for children with LCPD. Femoral heads in early-stage LCPD demonstrated dynamic deformity on weightbearing not previously seen, while unaffected hips did not. Expansion of this protocol will allow further translational study into the effects of loading hips with LCPD. Cite this article: Bone Joint Open 2020;1-7:364–369.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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".