Relevance of open magnetic resonance imaging position (sitting and standing) to quantify pelvic organ prolapse in women
Bibliographic record
Abstract
INTRODUCTION: In pelvic organ prolapse (POP), posture and gravity impact organ position and symptom severity. The advanced magnet configuration in open magnetic resonance imaging (MRO) allows patients to be imaged when sitting and standing, as well in a conventional supine position. This study evaluated if sitting and standing MRO images are relevant as a means of improving quantification of POP because they allow differences in organ position not seen on supine imaging to be identified. METHODS: Forty women recruited from a university urogynecology clinic had MRO imaging (0.5 T scanner) with axial and sagittal T2-weighted pelvic scans obtained when sitting, standing, and supine. Pelvic reference lines were used to quantify the degree of POP, and the relevance of imaging position on the detection of POP compared. RESULTS: Images from 40 participants were evaluated (20 with POP and 20 asymptomatic controls). Our results indicate that the maximal extent of prolapse is best evaluated in the standing position using H line, M line, mid-pubic line, and perineal line as reference lines to determine POP. CONCLUSIONS: MRO imaging of symptomatic patients in a standing position is relevant in the quantification of POP. Compared with supine images, standing imaging identifies that greater levels of downward movement in the anterior and posterior compartments occur, presumably under the influence of posture and gravity. In contrast, no appreciable benefit was afforded by imaging in the sitting position, which precluded use of some reference lines due to upward movement of the anorectal junction.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".