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Record W2313152080 · doi:10.1097/rlu.0b013e31820aa28e

Angiomatoid Fibrous Histiocytoma

2011· article· en· W2313152080 on OpenAlexaff
William Makis, Anthony Ciarallo, Marc Hickeson, Vilma Derbekyan

Bibliographic record

VenueClinical Nuclear Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsRoyal Victoria HospitalMcGill UniversityBrandon Regional Health Authority
Fundersnot available
KeywordsMedicineHistopathologySoft tissueBiopsySarcomaMetastasisRadiologySoft tissue sarcomaClear-cell sarcomaImmunohistochemistryPathologyCancerInternal medicine

Abstract

fetched live from OpenAlex

Angiomatoid fibrous histiocytoma is a very rare tumor that accounts for 0.3% of all soft-tissue tumors, and occurs predominantly in the extremities of adolescents and young adults. It has been classified by the World Health Organization as a tumor of uncertain differentiation with intermediate malignant potential, although recent evidence suggests a myoid or myofibroblastic cell origin. Most examples behave in an indolent manner with a regional recurrence rate of 15% and a rate of metastasis of 1%. We present a 29-year-old woman who was referred for an F-18 FDG PET/CT to evaluate a left shoulder mass. She had multiple local FDG-avid lymph nodes, and initial biopsy was suggestive of epithelioid sarcoma. She was treated with chemotherapy, but a post-therapy PET/CT showed minimal response and radical surgical excision was performed. The histopathology and immunohistochemistry was consistent with angiomatoid fibrous histiocytoma. This case highlights a potential new utility for F-18 FDG PET/CT in the staging and evaluation of response to therapy for this very rare soft-tissue tumor.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.160
GPT teacher head0.374
Teacher spread0.214 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations10
Published2011
Admission routes1
Has abstractyes

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