Benign adrenal and suprarenal retroperitoneal schwannomas can mimic aggressive adrenal malignancies: case report and review of the literature
Bibliographic record
Abstract
The suprarenal retroperitoneum and adrenal gland is a rare site of origin for benign schwannomas which frequently present as larger and more aggressive lesions than schwannomas identified elsewhere. These tumors are often surgically excised. We present a case of an 81-year-old asymptomatic man presenting with an incidental 10 cm left suprarenal retroperitoneal mass identified on CT. The mass was indiscernible from the adrenal gland, demonstrating heterogeneous enhancement with a centrally cystic/necrotic core, and punctate calcifications. Subsequent core needle biopsy demonstrated a benign adrenal schwannoma. The lesion has been managed conservatively with imaging follow up and without complication. DISCUSSION: Our review of the literature identifies 121 reported in vivo benign adrenal and suprarenal schwannomas published to date with imaging features available for 90 cases (74%). All cases were encapsulated with the average size measuring over 6.5 cm. Fifteen percent (13/84) of reported lesions measured over 10 cm at presentation. Punctate calcification was present in 50% (26/52) of reporting cases. Nearly 50% (40/86) of cases demonstrate cystic/necrotic appearances on imaging. Despite aggressive appearances, our case demonstrates that biopsy and surveillance may represent a reasonable alternative to surgery in suboptimal surgical candidates.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".