Radioactive seed localization in recurrent thyroid carcinoma: A case report
Bibliographic record
Abstract
Surgery is the preferred treatment for recurrent differentiated thyroid carcinoma. However, scar tissue and tissue plane distortion can significantly limit the safety and the precision of the dissection. Careful preoperative planning is key to minimizing perioperative morbidity and positive margins. We present a case of mixed thyroid carcinoma in a patient with multiple endocrine neoplasia type 1 syndrome. Following the initial surgery, the patient developed two recurrences, resistant to radioactive iodine treatment and had a history of positive margins. A year and a half later, the patient developed a third recurrence that was not palpable. We used a radioactive iodine-125 seed, preoperatively inserted under ultrasonography, to help retrieve the lesion intraoperatively and improve the precision of the dissection. This is the first case report on the use of radioguidance with an iodine-125 seed to enhance the safety and exactitude of the surgical resection of a locally recurrent thyroid carcinoma. Although radioactive seed localization has been mostly used in breast cancer, this technique demonstrates great potential in becoming a useful adjunct to complex thyroid surgery in selected cases.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".