EP79 Multi-Material 3D-Printed Hip Joint Model With Labral Seal for Surgical Planning
Bibliographic record
Abstract
Abstract Introduction Cam-type femoroacetabular impingement (FAI) is a condition in which excess bone at the femoral head–neck junction can damage the labrum and cartilage tissue. FAI is common, occurring in 22–55% of patients with hip pain [1]. Femoral osteochondroplasty is a common treatment, but low patient satisfaction has been reported [2]. We propose 3D-printed models for surgical planning to ensure a healthy post-operative labral seal. Methods MRI and CT images from a healthy hip joint were segmented, including all soft tissues but the ligamentum teres. The Ottawa Hospital Research Institute ethics board approved secondary use of deidentified images. Material jetting 3D printing was used to create a multi-material hip joint model. Distraction testing was performed following established methods [3] to quantify labral seal efficacy. The model was mounted to a tensile testing machine in a neutral pose and the joint was lubricated with vacuum grease. The model was compressed to form the labral seal and then pulled until the seal was broken; force and displacement were measured. The maximum distraction force and displacement at seal break were averaged over five trials and compared to existing cadaveric studies [4–11]. Results The maximum distraction force was 116 ± 11 N (mean ± standard deviation) and the displacement at labral seal break was 3.31 ± 0.235 mm. Discussion Our 3D-printed model demonstrated similar maximum distraction force and displacement as cadaveric tests, and shows promise as a new tool for surgical planning. Future work includes submerging the joint during testing to better simulate physiological conditions. References 1 Best & Martin, Principles of Orthopedic Practice for Primary Care Providers, 2nd ed, 159–72, 2021. 2. Farjo et al, Arthroscopy, 15:132–7, 1999. 3. Lee et al, Am J Sports Med, 43:98–104, 2015. 4. Suppauksorn et al, Arthroscopy, 38:365–73, 2022. 5. Nepple et al, Knee Surg Sports Traumatol Arthrosc, 22:730–6, 2014. 6. Utsunomiya et al, Am J Sports Med, 48:2733–9, 2020. 7. Maldonado et al, Am J Sports Med, 50:2462–8, 2022. 8. Storaci et al, Am J Sports Med, 48:2726–32, 2020. 9. Kaplan et al, Arthroscopy, 40:2575–84, 2024.
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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 | 0.001 | 0.000 |
| 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".