High Intensity Focused Ultrasound‐Induced Ablation of the Intra‐Abdominal Umbilical Vessels in a Rabbit Fetus: A Model Treatment of Twin‐Reversed Arterial Perfusion Sequence
Bibliographic record
Abstract
OBJECTIVE: To assess the efficacy of high intensity focused ultrasound (HIFU) to target and ablate the fetal intra-umbilical vessels and terminate fetal perfusion in a pregnant rabbit model. METHODS: Pregnant New Zealand white rabbits (gestational age: E25-27, n = 6 rabbits, n = 18 treated fetuses, n = 6 controls) underwent high-resolution MRI for fetal localization, orientation assessment, beam guidance, and treatment monitoring. Ultrafast ultrasound with power Doppler quantified cardiac output and placental perfusion pre- and post-treatment. HIFU (100-120Wac, 16-20s) induced thermal ablation; MR-thermometry monitored intraoperative temperature; histology confirmed ablation. Ultrafast ultrasound imaging and gross examination confirmed termination. RESULTS: . Ultrafast ultrasound imaging confirmed the termination of target fetuses, verifying the treatment success in 11 fetuses. Successfully treated fetuses showed a 95% ± 7.4% decrease in cardiac output compared with 11% ± 4.6% decrease in controls, p = 0.022. Placental perfusion dropped 83% ± 10.0% in successfully treated fetuses compared with 16% ± 5.5% in control fetuses, p = 0.002. Overall, 83% (15/18) of targeted fetuses were terminated, with adjacent controls surviving. Thermal necrosis was present in all targeted livers. CONCLUSIONS: MR-guided HIFU can effectively ablate fetal rabbit umbilical vessels to cause selective termination, modeling a non-invasive treatment for twin reversed arterial perfusion sequence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".