Comparison of Acetabular Measurements Between 2 Validated Software Programs Used in Hip Preservation Surgery
Bibliographic record
Abstract
Background: Validated software tools (Clinical Graphics [CG] and Hip 2 Norm) permit measurement of the percentage of femoral head coverage (%FHC), which aids in morphological classification and prediction of outcome after hip preservation surgery. Purpose: (1) To assess whether acetabular parameter measurements determined from 2 commonly used software systems are comparable. (2) To determine which parameters influence the correlation or differences between software outputs and measurements. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: The study included 69 patients (90 hips) who underwent periacetabular osteotomy and had comprehensive preoperative imaging available. Lateral center-edge angle (LCEA), acetabular index (AI), and %FHC were determined using 3-dimensional computed tomography (CT) measurements by CG and Hip 2 Norm software. Images of 18 pelvises were segmented to determine spinopelvic parameters and subtended acetabular angles. Between-group measurements were compared using correlation coefficients and Bland-Altman analyses. The difference in the outputs of the 2 programs was defined as delta (Δ). Radiographic parameters were tested to assess whether they were responsible for differences in %FHC between software programs. Results: Strong correlations between LCEA (ρ = 0.862) and AI (ρ = 0.825) measurements were seen between the Hip 2 Norm and CG programs. However, weak correlation was seen in the estimate of %FHC (ρ = 0.358), with the presence of a systematic error. Hip 2 Norm consistently produced lower anterior, posterior, and total %FHC values than CG. The %FHC determined by CG, but not Hip 2 Norm, correlated with acetabular subtended angles ( P < .05). Pelvic tilt measured on CT did not correlate with pelvic tilt estimated by Hip 2 Norm ( P = .56), and ΔPelvicTilt strongly correlated with the difference in %FHC by the 2 software programs (ρ = 0.63; P = .005), pelvic incidence (ρ = 0.73; P < .001), and pelvic tilt (ρ = −0.91; P < .001) as per CT. Conclusion: The correlation of %FHC between Hip 2 Norm and CG was weak (ρ = 0.358). The difference in measurements of %FHC correlated with ΔPelvicTilt. The %FHC determined by CG strongly correlated with the segmented acetabular subtended angles and thus more likely reflected true values. Hip preservation surgeons should be aware of these measurement differences because %FHC is important in the diagnosis and prognosis of acetabular dysplasia.
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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 | 0.006 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".