Open‐MRI measures of cam intrusion for hips in an anterior impingement position relate to acetabular contact force
Bibliographic record
Abstract
Open MRI in functional positions has potential to directly and non-invasively assess cam femoroacetabular impingement (FAI). Our objective was to investigate whether open MRI can depict intrusion of the cam deformity into the intra-articular joint space, and whether intrusion is associated with elevated acetabular contact force. Cadaver hips (9 cam; 3 controls) were positioned in an anterior impingement posture and imaged using open MRI with multi-planar reformatting. The β-angle (describing clearance between the femoral neck and acetabulum) was measured around the entire circumference of the femoral neck. We defined a binary "MRI cam-intrusion sign" (positive if β < 0°). We then instrumented each hip with a piezoresistive sensor and conducted six repeated positioning trials, measuring acetabular contact force (F). We defined a binary "contact-force sign" (positive if F > 20N). Cam hips were more likely than controls to have both a positive MRI cam-intrusion sign (p = 0.0182, Fisher's exact test) and positive contact-force sign (p = 0.0083), which represents direct experimental evidence for cam intrusion. There was also a relationship between the MRI cam-intrusion sign and contact-force sign (p = 0.033), representing a link between imaging and mechanics. Our findings indicate that open MRI has significant potential for in vivo investigation of the cam FAI mechanism.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".