Assessing injectate spread in ultrasound-guided capsular hydro dilatation for adhesive capsulitis: A comparative MRI study of anterior rotator interval vs. posterior glenohumeral joint approaches
Bibliographic record
Abstract
Adhesive capsulitis is a self-limiting condition of the shoulder, characterized by pain and limited range of motion (ROM). Intra-articular steroid injection and hydrodistension of the joint capsule are effective strategies for pain relief and improvement of ROM. Several randomized studies indicate that anterior rotator cuff interval (RCI) injections yield better outcomes than posterior glenohumeral (GH) joint injections. No study has examined the differences in injectate spread patterns between anterior RCI and posterior GH joint approaches. This study involved three patients with adhesive capsulitis who received ultrasound-guided shoulder joint injections with capsular hydrodilatation, utilizing 10 cc, via either the anterior RCI approach or the posterior GH joint approach. The injectate comprised 1 mL (80 mg) methylprednisolone acetate, 4 mL of 2 % lidocaine, and 5 mL of saline mixed with gadolinium contrast. Immediately following the injection, an MRI of the shoulder was performed to evaluate the distribution of the injectate. Injections via the anterior RCI approach exhibited significant intra-capsular spread and vital pathological intra-capsular and pericapsular structures. In contrast, posterior GH joint injections revealed restricted spread, mainly enlarging the joint recess without involvement of the pericapsular ligaments. This study highlights the distribution of injectate following an ultrasound-guided anterior shoulder joint injection, demonstrating that the anterior RCI approach effectively disperses a 10 mL injectate to the intra-capsular synovial lining and key pericapsular structures. The findings suggest that technique selection significantly impacts injectate distribution in adhesive capsulitis, with a 10 mL volume achieving optimal capsular distension without rupture.
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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 | 0.002 | 0.001 |
| 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 | 0.000 |
| 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".