Magnetic Resonance Imaging with Gadolinium Arthrography to Assess Acetabular Cartilage Delamination
Bibliographic record
Abstract
Recent reports have demonstrated magnetic resonance imaging (MRI) as a promising technique in detecting articular cartilage lesions of the hip joint. The purpose of our study was to evaluate the diagnostic performance of MRI with gadolinium arthrography in detecting acetabular cartilage delamination in patients with pre-arthritic hip pain. 46 patients (48 hips) underwent surgical dislocation of the hip. Mean age was 38.8 (range 17-56). There were 26 males and 20 females. All patients had Magnetic Resonance Imaging with gadolinium arthrography (MRA) before undergoing open hip surgery where the acetabular cartilage was inspected. Acetabular cartilage delamination on MRA was seen on sagittal images as a linear intra-articular filling defect of low signal intensity >1mm in thickness on T1 weighted images and surrounded by contrast. On MRA all hips had a labral tear confirmed at surgery. At surgery 30 hips had evidence of acetabular cartilage delamination, 4 hips had ulceration and 14 had no articular cartilage damage. The majority of labral tears and cartilage damage were located in the antero-superior quadrant. The sensitivity and specificity of MRA detection of cartilage delamination confirmed at surgery were 97% and 84%, respectively. The positive and negative predictive values of the MRA finding were 90% and 94%, respectively. The presence of the acetabular cartilage delamination represents an early stage of articular cartilage degeneration. When evaluating a young adult with hip pain, labral tears in association with cartilage delamination should be considered. MRA represents an effective diagnostic tool.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.000 | 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".