Unusual Polypoid Lesions of the Duodenum: A Few Surprises
Bibliographic record
Abstract
The small intestine constitutes most of the gastrointestinal tract but is an unusual site for primary neoplasms. Of small intestinal tumors, the duodenum is the most common site of involvement. The purpose of this study was to analyze the clinicopathologic spectrum of unusual duodenal neoplasms at St Michael’s Hospital, Toronto, in the last 20 years. A retrospective analysis identified a total of 177 duodenal tumors. After excluding adenocarcinoma, 40 cases of unusual duodenal neoplasms reported in the last 20 years were included in the study. Clinical details were noted, and routine H&E-stained paraffin sections and immunohistochemical parameters were studied for histologic subtyping of the tumors. Unusual tumors accounted for 40 (22.6%) of 177 primary duodenal neoplasms. On histopathologic examination, these were categorized as follows: 7 (18%) epithelial tumors consisting of 6 Brunner gland adenomas (5 cases typical, 1 atypical) and pyloric gland adenoma (1 case); 18 (45%) mesenchymal tumors consisting of GIST (5 cases), smooth muscle tumors (4 cases), myofibroblastic tumors (5 cases), lipoma (3 cases), and hemangioma (1 case); 9 (23%) lymphoproliferative tumors and 6 (15%) neuroendocrine tumours. Although rare, adenocarcinomas constitute the largest group of primary duodenal neoplasms, but the duodenum is also the harboring site for a range of unusual neoplasms, including most commonly mesenchymal tumors, followed by lymphoproliferative tumors. Unusual epithelial tumors and neuroendocrine tumors were less commonly seen. Accurate histopathologic examination of these duodenal tumors is important for the correct histologic subtyping of these tumors and collecting prognostic information that influences management.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".