Comparison of inversion recovery gradient echo with inversion recovery fast spin echo techniques for magnetic resonance imaging detection of navicular bone marrow lesions in horses
Bibliographic record
Abstract
OBJECTIVE: To compare navicular bone marrow lesion (BML) conspicuity in the feet of horses as determined via 2 fat-suppressed MRI techniques, including standard short tau inversion recovery (STIR) and inversion recovery gradient echo (IRGE). SAMPLE: Feet (n = 150) of horses with lameness referable to the distal portion of the digit. PROCEDURES: STIR and IRGE sequences were obtained prospectively in all feet with a standing low-field equine MRI system. Presence of a BML was ascertained by identification of a characteristic combination of marrow alterations in T1-weighted, T2*-weighted, T2-weighted, and STIR images. Signal-to-noise and contrast-to-noise ratios were calculated on STIR and IRGE sequences in 56 feet with a navicular BML. RESULTS: Signal-to-noise and contrast-to-noise ratios of both sequences correlated linearly (r = 0.87 and r = 0.92, respectively) but were significantly higher for STIR images (mean ± SD, 22.6 ± 12.7 and 12.4 ± 11.4, respectively), compared with IRGE images (13.7 ± 8.0 and 5.9 ± 7.2, respectively). CONCLUSIONS AND CLINICAL RELEVANCE: Results suggested that the IRGE sequence revealed BMLs significantly less conspicuously, compared with the standard STIR sequence. The 2 techniques cannot be used interchangeably, and IRGE is therefore not recommended as the sole fat-suppressed sequence for routine equine standing MRI protocols.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".