Use of custom three-dimensional printed models improves cam resection quality in arthroscopic treatment of femoral acetabular impingement syndrome
Bibliographic record
Abstract
INTRODUCTION/OBJECTIVES: To investigate whether the use of a three-dimensional (3D) printed model, compared to conventional imaging, resulted in better corrections of osseous deformities following femoral acetabular impingement syndrome (FAIS) hip arthroscopy by comparing radiographic outcomes. METHODS: A retrospective review of patients who underwent hip arthroscopy for FAIS between 2015 and 2019 was performed. Patients were sequentially allocated into the conventional or 3D model group. Radiographic plain films preoperatively and postoperatively assessed bony resection quality, measuring alpha angles and head-neck offset (HNO) ratios using 45° Dunn, frog-leg lateral, and anteroposterior views. Good resection was defined as an alpha angle <55° and poor resection as an alpha angle ≥55°. RESULTS: One hundred forty-eight patients were included (n = 86 in the conventional group and n = 62 in the 3D model group). Compared to conventional imaging, the 3D model group had statistically significantly lower postoperative alpha angles on 45° Dunn (p = 0.002) and frog-leg lateral views (p < 0.001). The change (preoperative to postoperative) in alpha angle was statistically significantly larger for the 3D model group, compared to conventional imaging, in 45° Dunn (p = 0.003) and frog-leg lateral views (p = 0.041). Compared to the conventional imaging group, the postoperative HNO ratio was statistically significantly higher in the 3D model group on 45° Dunn (p = 0.001) and frog-leg lateral views (p < 0.001) and change in HNO ratio was statistically significantly larger for the 3D model group in both 45° Dunn (p = 0.001) and frog-leg lateral views (p = 0.026). When considering the good and poor resections separately for all three radiographic views, the 3D model group showed a statistically significantly higher number of good resections than the conventional imaging group (p < 0.001). CONCLUSIONS: Arthroscopic FAIS treatment shows adequate resection using conventional surgical planning. The use of a 3D model facilitated better cam resection and permitted more patients to return to those within normal radiological values as measured by alpha angles and HNO ratios. LEVEL OF EVIDENCE: III. (retrospective cohort).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".