Report of metastatic ileal neuroendocrine tumor to the submandibular gland
Bibliographic record
Abstract
BACKGROUND: Neuroendocrine tumors (NETs) of small intestinal origin are generally slow-growing tumors with a relatively high propensity for metastases to surrounding organs and lymphatic tissue. We present the first case of an ileal NET metastasizing to the submandibular gland in a woman with metastatic carcinoid syndrome. CASE PRESENTATION: A 55-year-old female presented with a four-month history of a palpable, left-sided neck mass. The patient had a history of metastatic neuroendocrine tumor of ileal origin, initially treated with primary resection 4.5 years previously, with known subdiaphragmatic metastases to the liver, mesenteric nodes, and peritoneum. Four years following primary resection she developed carcinoid syndrome leading to therapy with radiolabelled metaiodobenzylguanidine (MIBG), as well as telotristat etiprate in the context of a clinical trial due to progressive symptoms. A fine needle aspiration biopsy of the neck mass revealed an immunohistochemical staining pattern consistent with ileal NET. The patient underwent a left level 1b neck dissection and submandibular gland excision. Pathology was consistent with metastastic ileal NET. CONCLUSION: We report the first case of ileal NET metastasis to the submandibular gland. Familiarity with the carcinoid syndrome and associated physiology should be maintained as it can affect the head and neck on rare occasions. Maintaining a broad differential is key in diagnosis of undifferentiated neck masses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".