Invasive lobular carcinoma of the breast presenting as retroperitoneal fibrosis: a case report
Bibliographic record
Abstract
INTRODUCTION: Invasive lobular carcinoma of the breast represents approximately 6.3% of mammary malignancies. Distant metastasis of invasive lobular carcinoma to the peritoneum or retroperitoneum has been reported fairly frequently. CASE PRESENTATION: We report the case of a 59-year-old Caucasian-Canadian woman with invasive lobular carcinoma of the breast presenting with retroperitoneal fibrosis and bilateral ureteral obstruction. Intra-operative pathology consultation did not reveal malignancy. The diagnosis, however, was confirmed on permanent sections by histological appearance in addition to immunohistochemistry. To the best of our knowledge, this is the first reported case of invasive lobular carcinoma of the breast presenting with retroperitoneal fibrosis. CONCLUSION: In a case of unexplained ureteric obstruction and retroperitoneal fibrosis, more comprehensive physical examination and additional ancillary studies may be warranted to rule out malignancy as an underlying etiology. This case also emphasizes that intra-operative frozen section consultation cannot always be fully relied upon to exclude a malignancy as the etiology of retroperitoneal fibrosis. Moreover, in permanent histopathology sections, immunohistochemistry testing can be of value to rule out metastatic disease where the morphology is not salient. There is a need for a thorough physical examination of patients with retroperitoneal fibrosis, including the breast and gynecological organs.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| 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".