EP5.22 Characterizing Anatomic Variances in Hip Impingement and Dysplasia using Multidomain Statistical Shape Analysis
Bibliographic record
Abstract
Abstract Introduction: Additional anatomical characteristics may play a key role in the development of symptomatic FAI and DDH, secondary to the characteristic cam, pincer/retroversion and acetabular undercoverage, and may assist in identifying at-risk asymptomatic patients. The aim was to characterize secondary morphologies in hips with cam FAI, acetabular retroversion, and dysplasia using statistical shape modelling (SSM) and determine their anatomical significance using principal component analysis (PCA). Method: Fifty-two cadaveric hips were computed tomography (CT) scanned and sorted into the following cohorts: cam FAI (CAM; axial 3:00 alpha angle > 50.5° or radial 1:30 alpha > 60°), acetabular retroversion (RETRO; crossover sign, posterior wall sign, retroversion index), dysplasia (DDH; lateral centre-edge angle < 20°, Tönnis angle > 10°, femoro-epiphyseal acetabular roof index > 2°), or control (CON; no morphologies). Three-dimensional models of the femurs, pelvises, and sacra were segmented from the CT data and used to develop statistical shape models (SSM). Mean SSMs representing the CON, CAM, RETRO, and DDH cohorts were produced to compare each pathological cohort with the CON group. PCA was applied to capture the variability within the SSMs, with the first mode indicating the most anatomically significant features. Results: Among RETRO and DDH, a highly variable greater trochanter height, intertrochanteric line, and femoral neck extension accounted for 43% and 51% of variance, respectively. In CAM, these features in addition to femoral head asphericity accounted for 57% of variance. Regarding sacropelvic morphology, both CAM and RETRO demonstrated a consistent anterior sacral tilt and acetabular overcoverage in mode 1 (25% and 25% variance, respectively). In contrast, DDH displayed a more consistent posterior sacral tilt and acetabular undercoverage in mode 1 (22% variance). Discussion: Both FAI cohorts (CAM and RETRO) consistently showed a decreased femoral neck-shaft angle which strongly supports an association with symptomatic FAI. The presence of increased anterior sacral tilt in mode 1 alongside the primary features also suggests pelvic incidence (increased in FAI, decreased in DDH) plays a critical role in the pathomechanics of such conditions. Consideration of such characteristics may better enable clinicians to identify at-risk asymptomatic patients, and aid in the further development of non-surgical therapies.
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 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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".