A Novel Method for Correcting Pelvic Tilt on Anteroposterior Pelvic Radiographs
Bibliographic record
Abstract
Background Anteroposterior (AP) pelvic radiographs remain the standard for pre- and postoperative imaging during total hip arthroplasty (THA), despite the known limitation of plain films, including the inability to adequately account for distortion caused by variations in pelvic orientation such as pelvic tilt. The purpose of this study was to develop a reliable method for correcting pelvic tilt on AP pelvic radiographs in patients undergoing THA. Methods CT scans from 20 patients/cadaver specimens (10 male, 10 female) were used to create 3D renderings, from which synthetic radiographs of each pelvis were generated. For each pelvis, 13 synthetic radiographs were generated, showing the pelvis at between -30° and 30° of pelvic tilt, in 5° increments. On each image, eight unique parameters/distances were measured to determine the most appropriate parameters for the calculation of pelvic tilt. The most reliable and accurate of these parameters was determined via regression analysis and used to create gender-specific nomograms from which pelvic tilt measurements could be calculated. The accuracy and reliability of the nomograms and correction method were subsequently validated using both synthetic radiographs (n=50) and stereoradiographic images (n=58). Results Of the eight parameters measured, the vertical distance between the superior margin of the pubic symphysis and the transischial line (PSTI) was determined to be the most reliable (r=-0.96, ICC=0.94). Using that parameter and applying the associated nomograms to 50 synthetic radiographs of random pelvic tilt, the mean difference between the actual pelvic tilt and that calculated using the correction method was 0.1°±5.1° (p=0.98, r=0.96). In 58 stereoradiographic images, the mean difference between actual and measured pelvic tilt was -0.2°±6.4° (p=0.74, r=0.77). The pooled results indicate no significant difference between actual (2.2°±13.9°) and measured pelvic tilt (2.1°±14.3°, p=0.93, r=0.91). No significant differences were noted based on gender. Conclusions Our method of correcting for pelvic tilt using the vertical distance from the pubic symphysis to the transischial line provides a reliable method for correcting for pelvic tilt on AP pelvic radiographs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".