Computer-assisted subcapital correction osteotomy in slipped capital femoral epiphysis using individualized drill templates
Bibliographic record
Abstract
BACKGROUND: Subcapital osteotomy by means of surgical hip dislocation is a treatment approach offered for moderate-to-severe cases of Slipped Capital Femoral Epiphysis (SCFE). This procedure is demanding, highly dependent on the surgeon's experience, and requires considerable radiation exposure for monitoring and securing the spatial alignment of the femoral head. We propose the use of individualized drill guides as an accurate method for placing K-wires during subcapital correction osteotomies in SCFE patients. METHODS: Five CT scans of the hip joint from otherwise healthy patients with moderate-to-severe SCFE were selected (ages 11-14). Three dimensional models of each patient's femur were reconstructed by manual segmentation and physically replicated using additive manufacturing techniques. Five orthopaedic surgeons virtually identified the optimal entry point and direction of the two threaded wires for each case. 3D printed drill guides were designed specific to each surgical plan, with one side shaped to fit the patient's bone and the other side containing holes to guide the surgical drill. Each surgeon performed three guided (using the drill guides) and three conventional (freehand) simulated procedures on each case. Each femur model was laser scanned and digitally matched to the preoperative model for evaluation of entry points and wire angulations. We compared wire entry point, wire angulation, procedure time and number of x-rays between guided and freehand simulated surgeries. RESULTS: The guided group (1.4 ± 0.9 mm; 2.5° ± 1.4°) was significantly more accurate than the freehand group (5.8 ± 3.2 mm; 5.3° ± 4.4°) for wire entry location and angulation (p < 0.001). Guided surgeries required significantly less drilling time and intraoperative x-rays (90.5 ± 42.2 s, 3 ± 1 scans) compared to the conventional surgeries (246.8 ± 122.1 s, 14 ± 5 scans) (p < 0.001). CONCLUSIONS: We conclude that CT-based preoperative planning and intraoperative navigation using individualized drill guides allow for improved accuracy of wires, reduced operative time and less radiation exposure in simulated hips. CLINICAL RELEVANCE: This preliminary study shows promising results, suggesting potential direct benefits to SCFE patients by necessitating less time under anesthesia and less intra-operative radiation exposure to patients, and increasing surgical accuracy.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".