Can T<sub>1</sub>-rho MRI detect acetabular cartilage degeneration in femoroacetabular impingement?
Bibliographic record
Abstract
Advanced MRI cartilage imaging such as T(1)-rho (T1ρ) for the diagnosis of early cartilage degradation prior to morpholgic radiological changes may provide prognostic information in the management of joint disease. This study aimed first to determine the normal T1ρ profile of cartilage within the hip, and secondly to identify any differences in T1ρ profile between the normal and symptomatic femoroacetabular impingement (FAI) hip. Ten patients with cam-type FAI (seven male and three female, mean age 35.9 years (28 to 48)) and ten control patients (four male and six female, mean age 30.6 years (22 to 35)) underwent 1.5T T1ρ MRI of a single hip. Mean T1ρ relaxation times for full thickness and each of the three equal cartilage thickness layers were calculated and compared between the groups. The mean T1ρ relaxation times for full cartilage thickness of control and FAI hips were similar (37.17 ms (SD 9.95) and 36.71 ms (SD 6.72), respectively). The control group demonstrated a T1ρ value trend, increasing from deep to superficial cartilage layers, with the middle third having significantly greater T1ρ relaxation values than the deepest third (p = 0.008). The FAI group demonstrated loss of this trend. The deepest third in the FAI group demonstrated greater T1ρ relaxation values than controls (p = 0.028). These results suggest that 1.5T T1ρ MRI can detect acetabular hyaline cartilage changes in patients with FAI.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".