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Record W3040985150 · doi:10.5582/irdr.2020.01027

Benign adrenal and suprarenal retroperitoneal schwannomas can mimic aggressive adrenal malignancies: case report and review of the literature

2020· article· en· W3040985150 on OpenAlexaff
Mitchell P. Wilson, Prayash Katlariwala, Jing‐Yang Huang, Gavin Low, Edward Wiebe

Bibliographic record

VenueIntractable & Rare Diseases Research · 2020
Typearticle
Languageen
FieldMedicine
TopicAdrenal and Paraganglionic Tumors
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineAsymptomaticAdrenal glandSchwannomaRadiologyBiopsyLesionIncidentalomaCalcificationPathology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.324
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2020
Admission routes1
Has abstractyes

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