Ultrasound‐guided gadolinium joint injections for magnetic resonance arthrography
Bibliographic record
Abstract
PURPOSE: To determine the feasibility and accuracy of ultrasound (US) -guided gadolinium injection for MR arthrography of shoulders, wrists, hips, and knee joints as an alternate technique to fluoroscopy. METHODS: One hundred patients referred to our center for an MR arthrogram of shoulders, wrists, hips, and knees were included in the study. There were 53 males and 47 females and ages ranged from 17 to 63 years (mean age, 37). US was used to guide the needle tip into the joint. The intra-articular location of the needle tip was confirmed by fluoroscopic visualization of injected iodinated contrast medium, prior to gadolinium injection. The patients then proceeded for the MRI examination. RESULTS: Ninety-nine of the 100 patients were successfully injected with gadolinium under US guidance. One patient had a vasovagal reaction after local anesthetic injection and the procedure was aborted. CONCLUSION: US is an effective alternate guidance technique for the injection of gadolinium into shoulder, hip, knee, and wrist joints for MR arthrography. Its advantages are cost effectiveness, ease of performance, and lack of radiation.
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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 | 0.008 |
| 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) | 0.002 | 0.001 |
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".