Positional pelvic organ prolapse (POP) evaluation using open, weight-bearing magnetic resonance imaging (MRI)
Bibliographic record
Abstract
INTRODUCTION: Magnetic resonance imaging (MRI) of patients with pelvic organ prolapse (POP) is completed in the supine position. Open magnetic resonance imaging (MRO) uses vertical magnets, allowing imaging in a variety of upright postures. This pilot study used MRO to evaluate the change of prolapse in different positions compared to non-prolapsed images. METHODS: In total, 11 women (6 POP, 5 controls) aged 24 to 65 years had 12 MRO images (midline sagittal pelvic line) consecutively when supine, sitting and standing with a full and empty bladder. Lengths between the lowest point of the bladder to the pubococcygeal (PC) and pubopromontoreal (PP) lines in each image were compared, and the ratio of bladder area under the PC and PP lines to the total bladder area. RESULTS: Significant elongation between the PC line and lowest point of the bladder was evident in subjects with POP comparing supine and standing images (p = 0.03), but not controls (p = 0.07). Similarly, this axis was significantly longer in cystocele subjects versus controls only in the standing position. Bladder area under the PC line was significantly increased between supine and standing positions only among subjects with cystocele (p < 0.01), and significantly larger among the study group in the standing position (p < 0.005), less significant in the supine position (p = 0.015), and not significant in the sitting position (p = 0.3). CONCLUSIONS: MRO imaging allows us to investigate the effects of upright position and weight bearing on the staging of POP. Imaging patients when sitting and standing identified that significant changes occur in the maximal descent of the bladder.
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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".