T2 mapping of articular cartilage in knee osteoarthritis using a magnetic resonance staging.
Bibliographic record
Abstract
OBJECTIVE: To evaluate T2 mapping of articular cartilage in knee osteoarthritis (OA). METHODS: Totally 38 healthy subjects (group H) and 53 OA patients received scoring with the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC)and underwent T2 mapping of tibiofemoral articular cartilages. The T2 values in 10 subregions of the cartilages were measured. Patients in the OA group were further divided into OA1 group and OA2 group using the modified Magnetic Resonance Recht Grading System. In OA group, the fat-suppressed three-dimensional fast spoiled gradient echo MRI was performed to obtain the modified Whole-Organ Magnetic Resonance Imaging Score (WORMS). The differences of T2 values among group H, group OA1, and group OA2 were compared. The correlation between T2 value and WORMS/WOMAC scores was analyzed. The intra- and inter-observer reproducibility of measurement was calculated. RESULTS: The T2 values in all the subregions ranged 43.9-53.6ms in group H, 41.1-55.0 ms in group OA1, and 45.6-56.1ms in group OA2. T2 values in group OA2 were significantly higher in central medial femoral subregion, central medial, and lateral tibial subregions compared with group H, also significantly higher in central medial femoral subregion, anterior and central medial tibial subregions compared with group OA1 (P<0.05). T2 values were significantly correlated with WORMS scores (R=0.307-0.811, P<0.01) except in posterior lateral femoral subregion, but not with WOMAC scores. The correlation coefficients for intra- and inter-observer measurement showed good reproducibility (R>0.740, P<0.05) except in anterior lateral tibial subregion for inter-observer of measurement. CONCLUSION: T2 mapping can differentiate the OA severity of knee cartilage using a magnetic resonance staging, and therefore can be a sensitive technique for monitoring the severity of OA.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".