Minimally invasive fetal therapy for hydropic lung masses: three different approaches and review of the literature
Bibliographic record
Abstract
OBJECTIVE: To report three different antenatal therapeutic approaches for fetal lung masses associated with hydrops. METHODS: Three prospectively followed cases are described, and all 30 previously published minimally invasive cases of fetal therapy for hydropic lung masses are reviewed. RESULTS: Three hydropic fetuses with large intrathoracic lung masses presented at 17, 25 and 21 weeks of gestation, respectively. An aortic feeding vessel was identified in each case and thus a bronchopulmonary sequestration (BPS) was suspected. Under ultrasound guidance, the feeding vessel was successfully occluded with interstitial laser (Case 1), radiofrequency ablation (RFA) (Case 2) and thrombogenic coil embolization (Case 3). Complete (Cases 1 and 2) or partial (Case 3) resolution of the lung mass and hydrops was observed. A healthy infant was born at term after laser therapy (Case 1), and the involved lung lobe was resected on day 2 of postnatal life. In Case 2, hydrops resolved completely following RFA, but an iatrogenic congenital diaphragmatic hernia and abdominal wall defect became apparent 4 weeks later. The neonate died from sepsis following spontaneous preterm labor at 33 weeks. In Case 3, despite technical success in complete vascular occlusion with coils, a stillbirth ensued 2 days after embolization. CONCLUSIONS: The prognosis of large microcystic or echogenic fetal chest masses associated with hydrops is dismal. This has prompted attempts at treatment by open fetal surgery, with mixed results, high risk of premature labor and consequences for future pregnancies. We have demonstrated the possibility of improved outcome following ultrasound-guided laser ablation of the systemic arterial supply. Despite technical success, RFA and coil embolization led to procedure-related complications and need further evaluation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".