EP31.16: The “Triangle Sign”: a novel dynamic ultrasound technique for identifying an obliterated cul‐de‐sac in patients with a retroverted uterus
Bibliographic record
Abstract
The identification of an obliterated cul-de-sac in patients with a retroverted uterus due to endometriosis is crucial for proper evaluation of the complexity of surgery for patients with advanced disease. However, the traditional sliding sign on ultrasound may be limited in cases where the uterus is retroverted as the majority of the posterior uterine serosa and the retrocervix are not in contact with bowel. Instead, the uterus lies on the back of the vagina and the bowel often stays out of this space. We propose a novel dynamic transvaginal ultrasound technique, implementing the new terminology, “Triangle Sign,” for identifying cul-de-sac obliteration in these cases. We present a case series of videos depicting the “Triangle Sign,” both when present (i.e. positive) and absent (i.e. negative), that were also surgically confirmed. Our case series also depicts cases where we attempt to use the original sliding sign without success in eliciting sliding in the location of the true obliteration. The technique is based on the observation that with a release of pressure with the transvaginal probe, we visualise a triangle appearance comprised of peritoneal fluid filling the space between the retroverted uterus, cul-de-sac, and rectum. In the abnormal setting when there is obliteration, we cannot elicit the triangle sign as fluid does not fill the densely adherent space. By evaluating the separation between the uterus and posterior structures and identifying the presence of fluid within the cul-de-sac, the “Triangle Sign” technique could improve the accuracy of diagnosis and guide surgical management.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".