Cartilage T2 Assessment at 3-T MR Imaging: In Vivo Differentiation of Normal Hyaline Cartilage from Reparative Tissue after Two Cartilage Repair Procedures—Initial Experience
Bibliographic record
Abstract
PURPOSE: To prospectively compare cartilage T2 values after microfracture therapy (MFX) and matrix-associated autologous chondrocyte transplantation (MACT) repair procedures. MATERIALS AND METHODS: The study had institutional review board approval by the ethics committee of the Medical University of Vienna; informed consent was obtained. Twenty patients who underwent MFX or MACT (10 in each group) were enrolled. For comparability, patients of each group were matched by mean age (MFX, 40.0 years +/- 15.4 [standard deviation]; MACT, 41.0 years +/- 8.9) and postoperative interval (MFX, 28.6 months +/- 5.2; MACT, 27.4 months +/- 13.1). Magnetic resonance (MR) imaging was performed with a 3-T MR imager, and T2 maps were calculated from a multiecho spin-echo measurement. Global, as well as zonal, quantitative T2 values were calculated within the cartilage repair area and within cartilage sites determined to be morphologically normal articular cartilage. Additionally, with consideration of the zonal organization, global regions of interest were subdivided into deep and superficial areas. Differences between cartilage sites and groups were calculated by using a three-way analysis of variance. RESULTS: Quantitative T2 assessment of normal native hyaline cartilage showed similar results for all patients and a significant trend of increasing T2 values from deep to superficial zones (P < .05). In cartilage repair areas after MFX, global mean T2 was significantly reduced (P < .05), whereas after MACT, mean T2 was not reduced (P > or = .05). For zonal variation, repair tissue after MFX showed no significant trend between different depths (P > or = .05), in contrast to repair tissue after MACT, in which a significant increase from deep to superficial zones (P < .05) could be observed. CONCLUSION: Quantitative T2 mapping seems to reflect differences in repair tissues formed after two surgical cartilage repair procedures. (c) RSNA, 2008.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".