Magnetic Resonance Imaging: A New Tool to Optimize the Prediction of Fetal Anemia?
Bibliographic record
Abstract
INTRODUCTION: The false-positive rate in the prediction of fetal anemia is 10-15%. We investigated if a new, noninvasive MRI method used as a supplement to ultrasound could improve the prediction. METHODS: Fetuses suspected of anemia and controls were scanned in a 1.5-tesla MRI scanner 1-4 times during pregnancy. Cases were scanned before and after intrauterine blood transfusion with a T1-mapping MRI sequence in a cross-section of the umbilical vein. RESULTS: Inclusion of 8 cases and 11 controls resulted in 10 case scans (2 cases were included twice) and 33 control scans. In controls, the T1 relaxation time was 1,005-1,391 ms; in cases with severe anemia, 1,505-1,595 ms, moderate anemia 1,503-1,525 ms, and no/mild anemia 1,245-1,410 ms. After blood transfusions, values dropped to 1,123-1,288 ms. The mean value in moderate and severe anemic cases was 275 ms higher than in controls (95% CI 210-341 ms, p < 0.0001), and after blood transfusion it was comparable to controls (3 ms, 95% CI -62 to 68 ms, p = 0.934). A 1,450-ms cut-off would have identified all cases in need of blood transfusion with no false-positive cases. CONCLUSIONS: Our findings indicate a potential for this new MRI method to improve the prediction of fetal anemia as a supplement to ultrasound.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".