<scp>Micro‐computed tomography</scp> reveals high‐density mineralised protrusions and microstructural lesions in equine stifle joint articular cartilage
Bibliographic record
Abstract
BACKGROUND: Stifle osteoarthritis (OA) lesions are most common in the medial femorotibial (MFT) compartment. Their characterisation and mapping will inform equine veterinarians towards an accurate diagnosis of OA. OBJECTIVES: Investigate and map micro-CT (μCT) changes in the hyaline articular cartilage (HAC) in the medial femoral condyle (MFC) and medial tibial plateau (MTP). STUDY DESIGN: Ex vivo cadaveric. METHODS: Stifles (n = 7 OA and 17 control [CO]) were retrieved from a tissue bank. The MFC and MFT were imaged with μCT. Regions of interest (ROIs) were cranial (MFCcr; MTPcr) and caudal (MFCca; MTPca) sites. In each ROI, μCT images were scored for HAC fibrillation, surface mineralisation and for the presence of high-density mineralised protrusions (HDMP). The lesions were mapped, and site-matched histology was performed. RESULTS: The microstructure of healthy and abnormal HAC was discernible on μCT images and confirmed with histology. HAC fibrillation was more prevalent (p = 0.019) in the MFCcr of the OA group (n = 7/7, 100%) when compared with the CO group (n = 7/17, 41%). Score 1 HAC surface mineralisation was more prevalent (p = 0.038) in the OA MFCca (n = 4/7, 57%) when compared with the CO group (n = 2/17, 12%). HDMP were heterogenous and hyperdense mineralised material protruding into the HAC and were more frequent (p = 0.033) in MFCs (n = 12/24, 50%) compared with MTPs (n = 5/24, 20%). Score 3 HDMPs were also more prevalent (p = 0.003) in the MFCcr (n = 7/24, 29%) compared with MFCca (n = 0/24, 0%) and in MFCs (n = 7/24, 29%) compared with MTPs (n = 3/24, 12.5%) (p = 0.046). MAIN LIMITATIONS: Clinical history was not available for all specimens. CONCLUSIONS: Equine HDMP and HAC surface mineralisation are imaged for the first time in the MFT joint. HAC fibrillation and erosion and HDMP are more frequent in the cranial aspect of the MFC. μCT images of OA in equine stifle joints provide a novel perspective of lesions and improve understanding 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".