T1ρ MRI detects cartilage damage in asymptomatic individuals with a cam deformity
Bibliographic record
Abstract
Hips with a cam deformity are at risk for early cartilage degeneration, mainly in the anterolateral region of the joint. T1ρ MRI is a described technique for assessment of proteoglycan content in hyaline cartilage and subsequently early cartilage damage. In this study, 1.5 Tesla T1ρ MRI was performed on 20 asymptomatic hips with a cam deformity and compared to 16 healthy control hips. Cam deformity was defined as an alpha angle at 1:30 o'clock position over 60° and/or at 3:00 o'clock position over 50.5°. Hip cartilage was segmented and divided into four regions of interest (ROIs): anterolateral, anteromedial, posterolateral, and posteromedial quadrants. Mean T1ρ value of the entire weight bearing cartilage in hips with a cam deformity (34.0 ± 4.6 ms) was significantly higher compared to control hips (31.3 ± 3.2 ms, p = 0.050). This difference reached significance in the anterolateral (p = 0.042) and posteromedial quadrants (p = 0.041). No significant correlation between the alpha angle and T1ρ values was detected. The results indicate cartilage damage occurs in hips with a cam deformity before symptoms occur. A significant difference in T1ρ values was found in the anterolateral quadrant, the area of direct engagement of the deformity, and in the posteromedial quadrant. To conclude, T1ρ MRI can detect early chondral damage in asymptomatic hips with a cam deformity. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 34:1004-1009, 2016.
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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 | 0.000 |
| 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) | 0.001 | 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".