How best to measure the levator hiatus: evidence for the non‐Euclidean nature of the ‘plane of minimal dimensions’
Bibliographic record
Abstract
OBJECTIVE: To clarify whether the 'plane of minimal dimensions' of the levator hiatus on three-dimensional (3D) ultrasound accurately represents the minimal anatomical transverse hiatal dimension during a Valsalva maneuver. METHODS: In this retrospective study of 3D transperineal ultrasound and magnetic resonance (MR) imaging, datasets from 19 female participants were used to measure the transverse diameter of the levator hiatus using the plane of minimal dimensions on maximum Valsalva maneuver. The term 'apparent minimal transverse diameter' (aMTD) was used to define the transverse diameter measured using axial ultrasound and comparable axial or coronal MR images. Coronal MR images, using the plane of the vagina as a reference, were also obtained on maximum Valsalva. The transverse diameter measured between the caudal margin of the pubococcygeus/puborectalis on the MR coronal image is denoted by the term 'true minimal transverse diameter' (tMTD). Statistical comparisons between the aMTD and tMTD were made using Student's t-test. RESULTS: No significant difference was demonstrated between the aMTD as measured by ultrasonography and MRI. However, there were significant differences found between the aMTD measured by both ultrasound and MRI and the tMTD measured on coronal MR images (both P < 0.01), with mean ( ± SD) values of 4.36 ± 0.85, 4.13 ± 1.09 and 3.23 ± 0.49 cm, respectively. CONCLUSION: This study highlights the complexity and 3D nature of the levator hiatus and pelvic floor muscles. Investigators have previously assumed that the plane of minimal dimensions of the hiatus can be measured in a flat plane, however, the 3D nature of the hiatus means that the true levator hiatus occupies a warped (non-Euclidean) plane. Hiatal measurements on Valsalva may be subject to systematic error if performed in a single section, i.e. using a flat (Euclidean) plane.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".