A Novel Computational Approach for Calculating Sagittal Plane Urogenital Kinematics from Dynamic 2D Ultrasound
Bibliographic record
Abstract
Up to half of women experience stress urinary incontinence (SUI) during tasks that increase intra-abdominal pressure. The exact biomechanics underlying urine leakage remains unclear, but is likely associated with concurrent failures in urethral sphincter function, urethral support, and pelvic floor muscle (PFM) mechanics. The biomechanics of the continence system during functional tasks can be assessed by transperineal ultrasound imaging (USI). However, during imaging, neither the USI probe nor the imaging surface is fixed in 3D space. With the pubic symphysis as the only bony landmark partially visible on sequential images, the impact of probe motion is difficult to assess. In practice, clinical researchers often compare measurements at rest to those at peak dynamic displacement without compensating for probe motion, and omit directionality despite its likely relevance. One proposed method of compensation defines a co-ordinate system with the origin set as the infero-posterior pubic symphysis and one axis running parallel to the urethra. However, we have noted substantial urethral deformation during dynamic tasks performed by many women with SUI, which has led us to question the validity of this approach. Instead, we have developed a new computational method to compensate for in-plane rotation and translation, allowing for more accurate calculation of urogenital kinematics during dynamic tasks known to cause urine leakage. We will present our computational method applied to the study of urogenital kinematics during dynamic tasks including voluntary PFM contraction, cough, and Valsalva maneuvers. The proposed approach may be used to comprehensively study the pathomechanics associated with SUI in women.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".