Feasibility of INTACT (INcisionless TArgeted Core Tissue) biopsy procedure for perinatal autopsy
Bibliographic record
Abstract
OBJECTIVES: To determine the feasibility and tissue yield of a perinatal incisionless ultrasound-guided biopsy procedure, the INcisionless Targeted Core Tissue (INTACT) technique, in the context of minimally invasive autopsy. METHODS: Cases of perinatal death in which the parents consented for minimally invasive autopsy underwent postmortem magnetic resonance imaging and an INTACT biopsy procedure, defined as needle biopsy of organs via the umbilical cord, performed under ultrasound guidance. In each case, three cores of tissue were obtained from seven target organs (both lungs, both kidneys, heart, spleen and liver). Biopsy success was predefined as an adequate volume of the intended target organ for pathological analysis, as judged by a pathologist blinded to the case and biopsy procedure. RESULTS: Thirty fetuses underwent organ sampling. Mean gestational age was 30 weeks (range, 18-40 weeks) and mean delivery-to-biopsy interval was 12 days (range, 6-22 days). The overall biopsy success rate was 153/201 (76.1%) samples, with the success rates in individual organs being highest for the heart and lungs (93% and 91%, respectively) and lowest for the spleen (11%). Excluding splenic samples, the biopsy success rate was 150/173 (86.7%). Histological abnormalities were found in 4/201 (2%) samples, all of which occurred in the lungs and kidneys of a fetus with pulmonary hypoplasia and multicystic kidney disease. CONCLUSIONS: Incisionless ultrasound-guided organ biopsy using the INTACT procedure is feasible, with an overall biopsy success rate of over 75%. This novel technique offers the ideal combination of an imaging-led autopsy with organ sampling for parents who decline the conventional invasive approach. © 2019 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".