T1rho Magnetic Resonance Imaging at 3T Detects Knee Cartilage Changes After Viscosupplementation
Bibliographic record
Abstract
Viscosupplementation may affect cartilage. Changes in T1rho magnetic resonance imaging (MRI) relaxation times correlate with proteoglycan changes in cartilage. The authors hypothesized that T1rho MRI will show an improvement in proteoglycan content at 6 weeks and 3 months after viscosupplementation and that this improvement will correlate with functional outcome scores. Ten patients (mean age, 56 years; Kellgren-Lawrence grade 1 or 2) underwent T1rho MRI at baseline, 6 weeks, and 3 months after viscosupplementation. Volumetric T1rho means were calculated by depth and region. Visual analog scale (VAS), International Knee Documentation Committee (IKDC), and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores were obtained. Mean T1rho values decreased in the superficial patella at 6 weeks (10.3%, P=.002) and 3 months (7.9%, P=.018) and in the middle patella at 6 weeks (7.0%, P=.014) compared with baseline values. Deep patella T1rho values increased at 3 months compared with 6 weeks (9.9%, P=.033), returning to values similar to baseline. Mean T1rho values increased in the deep tibia at 6 weeks (4.7%, P=.048) and in the middle tibia (5.2%, P=.004) and deep tibia (11.2%, P=.002) at 3 months compared with baseline. At 6 weeks, improvement was seen in VAS (5.9 to 3.9, P<.01), IKDC-9 (55.3 to 63.7, P=.03), and WOMAC (43.9 to 32.8, P=.03) scores. Functional VAS (4.0, P=.02), IKDC-9 (67.8, P=.04), and WOMAC (30.0, P=.04) scores remained better at 3 months. T1rho MRI is a feasible noninvasive method of studying molecular changes in cartilage. Some segments improved after viscosupplementation, and others worsened, possibly reflecting natural history or symptom relief and subsequent increase in activity-related wear.
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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) | 0.001 | 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 | 0.001 | 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".