Temporal lobe dysplasia: a characteristic sonographic finding in thanatophoric dysplasia
Bibliographic record
Abstract
OBJECTIVE: To determine the incidence of temporal lobe dysplasia (TLD) detected on prenatal ultrasound in thanatophoric dysplasia (TD) over an 11-year period in a tertiary referral center. METHODS: An 11-year retrospective review of perinatal autopsies from 2002 to 2013 was performed to identify cases of TD. The ultrasound images and corresponding reports of all TD cases were examined for the presence of TLD. The same set of images subsequently underwent a retrospective review by a perinatal radiologist with knowledge of the features of TLD to determine whether they could be identified. RESULTS: Thirty-one cases of TD underwent perinatal autopsy, and prenatal ultrasound imaging was available for review in 24 (77%). Mean gestational age at diagnosis of TD was 21.3 (range, 18-36) weeks. TLD was identified and reported in 6/24 (25%) cases; all six cases occurred after 2007. Retrospective interpretation of the ultrasound images identified features of TLD in 10 additional cases. In total, 16/24 (67%) cases displayed sonographic evidence of TLD. Temporal trends showed that TLD features were present in 50% (5/10) of all TD cases between 2002 and 2006 and in 79% (11/14) of those detected between 2007 and 2013. CONCLUSIONS: At present, the detection rate of TLD by ultrasound is low but may be increased by modified brain images that enhance visualization of the temporal lobes. Prenatal identification of TLD may help in the prenatal diagnosis of TD and thus provide more accurate prenatal counseling and guide molecular investigations to confirm the specific diagnosis of TD.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".