Corroboration of Normal and Abnormal Fetal Cerebral Lamination on Postmortem MR Imaging with Postmortem Examination
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The presence of normal fetal cerebral lamination of the germinal matrix, intermediate zone, subplate layer, and cortex can be used as a marker of normal fetal cerebral development. Our aim was to compare postmortem MR imaging assessment of normal and abnormal fetal cerebral lamination on T1- and T2-weighted images with histopathology. MATERIALS AND METHODS: Fifty-five formalin-fixed brains from postmortem fetuses, ranging from 16 to 30 weeks' gestational age, mean of 23 weeks, underwent T1- and T2- weighted MR imaging and subsequent sectioning and histologic examination. The cerebral lamination was graded as normal or abnormal on T1- and T2-weighted imaging and compared with postmortem findings. The sensitivity, specificity, and positive and negative predictive values of T1 and T2 assessment of cerebral lamination were calculated. RESULTS: Twenty-six fetuses had abnormal and 29 had normal cerebral lamination on histology. On T1, the overall sensitivity, specificity, and positive and negative predictive values of evaluating cerebral lamination were 96.15%(CI, 78.42%-99.80%), 89.66%(CI, 71.50%-97.29%), 89.29%(CI, 70.63%-97.19%), and 96.29%(CI, 79.11%-99.80%), respectively. On T2, the overall sensitivity, specificity, and positive and negative predictive values of evaluating cerebral lamination were 73.08%(CI, 51.95%-87.65%), 96.55%(CI, 80.37%-99.82%), 95.00%(CI, 73.06%-99.74%), and 80.00%(CI, 62.54%-90.94%), respectively. CONCLUSIONS: Postmortem MR imaging has high sensitivity, specificity, and positive and negative predictive values in assessing fetal cerebral lamination compared with histology. T1-weighted imaging has a higher sensitivity and negative predictive value, while T2-weighted imaging has a higher specificity and positive predictive value.
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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 | 0.001 |
| 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".