Multinucleate cell angiohistiocytoma: A clinicopathologic study of 62 cases and proposed diagnostic criteria
Bibliographic record
Abstract
BACKGROUND: Multinucleate cell angiohistiocytoma (MCAH) is an uncommon and likely underdiagnosed entity that is thought to be of vascular and fibrohistiocytic origin. METHODS: We retrospectively reviewed all cases diagnosed as MCAH at the Yale Medicine Dermatopathology laboratory between 1 January 1990 and 1 September 2018. Sixty-two cases were retained. We performed immunohistochemistry on the ten most inflamed lesions found and assessed for a possible alteration within the Wnt/ß-catenin signaling pathway, involved in follicular induction in dermatofibroma. We subsequently established histologic diagnostic criteria to differentiate MCAH from its mimickers. RESULTS: MCAH affected both genders equally. The hands or fingers were affected in 51.6% of cases. We found the most specific histologic criteria to be: (a) presence of odd multinucleated fibroblasts, (b) presence of superficial parallel fibrosis, (c) presence and thickening of superficial papillary dermal vessels, and (d) absence of perifollicular fibrosis. As for immunoreactivity, we found positivity to CD138, CD163, and CD117 in the mononuclear inflammatory infiltrate. There was no histopathologic evidence of follicular induction, as can be seen in dermatofibromas, and no expression of nuclear beta-catenin as seen in dermatofibromas with follicular induction. CONCLUSION: This large case series establishes MCAH as a distinct clinical and histopathologic entity.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".