Fast presurgical magnetic resonance imaging of meniscal tears and concurrent subchondral bone marrow lesions
Bibliographic record
Abstract
Meniscal tears and subchondral bone marrow lesions have both been described in dogs with cranial cruciate ligament rupture, but their possible concurrence has not been evaluated. In a population of 14 dogs exhibiting signs of stifle pain with surgically confirmed cranial cruciate ligament rupture, a short presurgical 1.5T magnetic resonance (MR) imaging protocol including dorsal proton density, dorsal T1-weighted gradient recalled echo, and sagittal fat-saturated dual echo sequences was tested to further investigate these features and illustrate meniscal tears. Interobserver agreement for detection of medial meniscal tears (k=0.83) and bone marrow lesions (k=0.87) was excellent. Consensus MR reading allowed detection of nine out of 12 surgically confirmed medial meniscal tears and there was no false positive. All dogs had cruciate ligament enthesis-related bone marrow lesions in the tibia, femur or both bones. Additionally, among the 12 dogs with confirmed medial meniscal tears, subchondral bone marrow lesions were present in the caudomedial (9 dogs) and caudoaxial (11 dogs) regions of the tibial plateau, resulting in odds ratios (13.6, p=0.12, and 38.3, p=0.04, respectively) that had large confidence intervals due to the small group size of this study. The other two dogs had neither tibial bone marrow lesions in these locations nor medial meniscal tears. These encouraging preliminary results warrant further investigation using this clinically realistic preoperative MR protocol. As direct diagnosis of meniscal tears remained challenging in dogs even with high-field MR, identification of associated signs such as subchondral bone marrow lesions might indirectly allow suspicion of an otherwise unrecognized meniscal tear.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".