Ultrasound features of multinodular goiter in DICER1 syndrome
Bibliographic record
Abstract
DICER1 syndrome is caused by germline pathogenic mutations in the DICER1 gene. Multinodular goiter (MNG) is a common clinical feature of DICER1 syndrome in children and adults. The aim of this study was to determine the ultrasound (US) characteristics of MNG in patients with DICER1 syndrome. This retrospective study evaluated thyroid US in patients with DICER1 germline mutations (DICER1mut+) performed between 2011 and 2018 at a single center by the same pediatric endocrinologist, and the images were re-examined by an independent pediatric radiologist from another academic center. Patients < 18 years with DICER1mut+ and DICER1mut+ parents without previous thyroidectomy were included. Ultrasound phenotypes of MNG in the setting of DICER1 mutations were compared with known US features of thyroid malignancy. Thirteen DICER1mut+ patients were identified (10 children, 3 adults). Three children had a normal thyroid US; therefore, thyroid abnormalities were assessed in seven children and three adults. In both children and adults, multiple (≥ 3) mixed (cystic/solid) nodules predominated with single cystic, single cystic septated and single solid nodules, occasionally with a "spoke-like" presentation. All solid lesions were isoechogenic, and in only one with multiple solid nodules, intranodular blood flow on power/color Doppler was observed. Remarkably, macrocalcifications were present in all three adults. The spectrum of ultrasonographic findings of MNG in DICER1mut+ patients is characteristic and largely distinct from typical features of thyroid malignancy and therefore should inform physicians performing thyroid US of the possible presence of underlying DICER1 syndrome.
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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 | 0.001 |
| 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 | 0.000 | 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".