MétaCan
Menu
Back to cohort
Record W7116691879 · doi:10.1093/jhps/hnaf069.213

EP79 Multi-Material 3D-Printed Hip Joint Model With Labral Seal for Surgical Planning

2025· article· en· W7116691879 on OpenAlexaffabout
Firas Baklouti, Gerd Melkus, Kawan S. Rahkra, Ariane Parisien, Andrew Speirs, Paul E Beaulé, Thomas K. Uchida

Bibliographic record

VenueJournal of Hip Preservation Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsOttawa HospitalCarleton UniversityUniversity of Ottawa
Fundersnot available
KeywordsFemoroacetabular impingementCadaveric spasmAcetabular labrumDisplacement (psychology)Seal (emblem)LabrumDistractionJoint (building)

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.092
GPT teacher head0.342
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Hip Preservation SurgerySame topicHip disorders and treatmentsFrench-language works237,207