Glenohumeral joint capsular tissue tension loading correlates moderately with shear wave elastography: a cadaveric investigation
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to investigate changes in the mechanical properties of capsular tissue using shear wave elastography (SWE) and a durometer under various tensile loads, and to explore the reliability and correlation of SWE and durometer measurements to evaluate whether SWE technology could be used to assess tissue changes during capsule tensile loading. METHODS: The inferior glenohumeral joint capsule was harvested from 10 fresh human cadaveric specimens. Tensile loading was applied to the capsular tissue using 1-, 3-, 5-, and 8-kg weights. Blinded investigators measured tissue stiffness and hardness during loading using SWE and a durometer, respectively. Intraobserver reliability was established for SWE and durometer measurements using intraclass correlation coefficients (ICCs). The Pearson product-moment correlation was used to assess the associations between SWE and durometer measurements. RESULTS: The ICC3,5 for durometer measurements was 0.90 (95% confidence interval [CI], 0.79 to 0.96; P<0.001) and 0.95 (95% CI, 0.88 to 0.98; P<0.001) for SWE measurements. The Pearson correlation coefficient values for 1-, 3-, and 5-kg weights were 0.56 (P=0.095), 0.36 (P=0.313), and -0.56 (P=0.089), respectively. When the 1- and 3-kg weights were combined, the ICC3,5 was 0.72 (P<0.001), and it was 0.62 (P<0.001) when the 1-, 3-, and 5-kg weights were combined. The 8-kg measurements were severely limited due to SWE measurement saturation of the tissue samples. CONCLUSION: This study suggests that SWE is reliable for measuring capsular tissue stiffness changes in vitro at lower loads (1 and 3 kg) and provides a baseline for the non-invasive evaluation of effects of joint loading and mobilization on capsular tissues in vivo.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".