VP24.09: First trimester screening for open spina bifida: validation of measurement technique of the posterior fossa landmarks for open spina bifida
Bibliographic record
Abstract
The intracranial translucency (ICT) has gained widespread recognition as an effective screening tool for early detection of open spina bifida (OSB), particularly when combined with other fetal cranial posterior fossa markers (brain stem (BS), cisterna magna (CM) and BS to occipital bone (BSOB)). Accurate identification and measurement of these structures, which appear as three parallel echogenic lines of apparent decreasing size, is critical to early detection of OSB, yet the measurement technique has not been previously well-defined. The purpose of this study is to describe and validate a novel technique for measurement of the posterior brain markers for early detection of OSB, and to assess their relative sizes. Prospective cohort study, consented singleton pregnant women undergoing first trimester anatomic scan. Mid-sagittal images of the fetal profile showing the posterior cranial fossa anatomy were collected and stored. Posterior fossa measurements were performed using our unique step-wise technique with specific landmarks for caliper positioning. The fetuses included in the study were all unaffected by OSB. 329 singleton pregnant women were recruited. The posterior fossa structures were successfully measured in 97.6% (321/329) of the participants, confirming the feasibility of the technique in most cases. Measurement Results: mean BS 2.9 mm (2.0 – 3.9 mm), mean ICT 2.1 mm (1.5 – 2.8 mm), mean CM 1.6 mm (0.8 – 2.6 mm), mean BSOB 4.4 mm (3.2 – 5.9mm) and mean BS/BSOB ratio 0.66 (0.46 – 0.95). The mean BS-ICT-CM measurements showed decreasing size. Using this technique, we were able to accurately measure the structures of fetal cranial posterior fossa in almost all participants and demonstrate a pattern of decreasing size. This technique provides a standardised approach which can be complemented by pattern recognition to improve accuracy and consistency of early screening for OSB.
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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 | 0.008 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".