Uterine Artery Embolization for Leiomyomas: Pre- and Postprocedural Evaluation with US
Bibliographic record
Abstract
Transabdominal and transvaginal ultrasonography (US) are commonly used to assess the uterus and pelvis prior to and following uterine artery embolization (UAE) for symptomatic leiomyomas (fibroids). Preprocedural US may help identify relative contraindications for UAE, whereas postprocedural US can help determine the quality and quantity of fibroid involution and help identify any complications associated with the procedure. The consulting radiologist should be familiar with certain typical postprocedural US findings, which might otherwise be improperly interpreted, leading to unnecessary intervention. Magnetic resonance (MR) imaging or computed tomography will frequently provide the most accurate information in UAE patients with certain pathologic conditions, and early study results suggest that MR imaging may be helpful in predicting treatment response. Nevertheless, US is a readily available first-line imaging modality and a well-accepted method for both pre- and postprocedural evaluation of patients who undergo UAE. A proper understanding of the US findings in this patient population allows objective determination of treatment response and detection of most of the commonly recognized complications that are associated with UAE.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".