Magnetic Resonance Imaging Verification of a Case of Sacrococcygeal Teratoma
Bibliographic record
Abstract
Although rare, sacrococcygeal teratoma is the most common congenital neoplasm, occurring in 1 in 40,000 infants. Approximately 75% of affected infants are female. The aim of the present study was to correlate ultrasonography and magnetic resonance imaging (MRI) findings in patients with fetal sacrococcygeal teratoma. Three pregnant women in 27th week of gestation underwent fetal MRI after ultrasonography examination, with findings suggestive for fetal sacrococcygeal teratoma. Tumor size, location, extent and content were evaluated both by MRI and ultrasonography. Findings regarding tumor location, size and content were similar for both methods. There was a large well-circumscribed mixed, cystic/solid oval mass, originating from right sacro-gluteal region and projecting into the amniotic cavity, 132 × 110 × 76 mm in size. The mass had a heterogeneous appearance. The T1 high signal suggested fat component of the tumor, while T1 and T2 hypointense components suggested calcified/bony components. There was also T1 hypointense component consistent with cystic and fluid component. The imaging findings were characteristic for sacrococcygeal teratoma. There was not obvious lumbar or thoracic spinal involvement. There was no gross intrapelvic or abdominal extension, and even sacrum and coccyx appeared deformed. The amount of amniotic fluid was increased. MRI was superior to ultrasonography in the evaluation of the exact tumor extent, accurately demonstrating pelvic involvement in all of the three cases. Fetal MRI has shown to be a valuable adjunct to obstetric sonography in the evaluation of fetal sacrococcygeal teratoma, because of its higher accuracy in the determination of tumors extent and content, playing a significant role in the therapeutic planning and increasing the chances of cure for these fetuses.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".