Sonographic Diagnosis of Gestational Trophoblastic Disease and Comparison With Retained Products of Conception
Bibliographic record
Abstract
OBJECTIVE: Gestational trophoblastic disease (GTD) and retained products of conception (RPC) can be difficult to distinguish sonographically. The aim of this study was to determine whether there were any sonographic criteria that could prospectively distinguish one from the other. METHODS: Institutional ethics approval was obtained, and acquisition of consent was waived by the Institutional Review Board. A retrospective review of gynecologic oncology and pathology databases identified 17 cases of GTD and 14 cases of RPC. Findings from the pre-evacuation transvaginal sonographic examinations were analyzed. The scans were independently reviewed by 2 senior radiologists with specific expertise in pelvic sonography using several predetermined sonographic features. The reviewers were blinded to the diagnosis. A consensus reading was obtained. RESULTS: The sonographic features that predicted GTD were a myometrial epicenter (P = .0002; odds ratio [OR] = 28), depth of myometrial invasion of more than one third (P = .001; OR = 20), placental venous lakes (P = .04; OR = 9), maximum mass dimensions of more than 3.45 cm (P = .009), and maximum endometrial thickness of less than 12 mm (P = .02). The remaining criteria were not statistically significant and included the characteristics of the mass, ascites, a "snowstorm" appearance, mass vascularity (including resistive index and peak systolic velocity), and the presence of ovarian cysts. CONCLUSIONS: There are specific transvaginal sonographic features that can accurately differentiate GTD and RPC.
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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 | 0.002 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".