Solitary fibrous tumor of the orbit: The importance of the histopathological diagnosis of the hemangiopericytoma pattern
Bibliographic record
Abstract
Abstract Purpose: The diagnoses of solitary fibrous tumor (SFT) and hemangiopericytoma (HPC) have evolved over the past decades. Due to histopathological similarities, they were grouped as the same entity highlighting the complexity of this rare condition. Previous studies suggest that orbital HPC-pattern tumors are more aggressive than SFTs. We analyzed the histopathological and immunohistochemical features of patients with orbital SFT/HPC to further classify this entity. Materials and Methods: We reviewed eight orbital SFT/HPC cases from McGill University Health Centre (2011–2019). All of them were diagnosed as SFT, three with HPC pattern. Vascular proliferation (HPC) and spindle cell morphology (SFT) were evaluated. The tumors were stained with STAT6, CD34, Ki67, SMA, EMA, and S100 protein and further analyzed. Results: The average age was 49 years, and seven were male. Follow-up ranged from 6 to 96 months. Three patients (two males and one female) had an HPC pattern (average age of 54 years). Five male patients had only SFT pattern (average age of 46 years). In HPC cases, STAT6 was negative, CD34 and SMA were positive, S100 protein and EMA were negative, and Ki67 was low (5%–10%). In SFT cases, STAT6 and SMA were positive, CD34 was positive (in spindle cells and vessels for two cases, vessels only in three), S100 protein and EMA were negative, and Ki67 was low (5%–20%). Conclusion: These results highlight the pathological variability of orbital SFT/HPC. Immunohistochemical profiling helps differentiate between SFT and SFT with HPC pattern, which is essential, as HPC have a higher risk of recurrence and malignant transformation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".