Plexiform ameloblastoma: a potential diagnostic challenge
Bibliographic record
Abstract
OBJECTIVE: Ameloblastoma is a benign, locally aggressive neoplasm of the jaws. Accurate diagnosis is important for providing timely treatment and reducing the risk of recurrence and local destruction. The criteria for diagnosing ameloblastoma are well-defined, however, rare cases have been observed with a multicystic/unicystic plexiform pattern that lacks pathognomonic histologic features, causing difficulties in differentiating them from less aggressive jaw lesions. Our main objective was to review these plexiform ameloblastomas that could prove challenging for pathologists on incisional biopsies. STUDY DESIGN: We reviewed cases of ameloblastoma in the University of Toronto diagnostic biopsy service from 2004 to 2024, n = 200. Cases with a microscopic description of cystic plexiform epithelial proliferation were retrieved for analysis of histopathologic features, clinical and radiographic information. RESULTS: A rare subset of ameloblastoma (4%, 8 of 200) presented a distinctive histologic appearance of cystic plexiform proliferation lacking ameloblast-like cells, but clinical and radiographic features characteristic of ameloblastoma. Immunohistochemical staining for the BRAF p.V600E mutation was positive in 7 of 8 cases, demonstrating the importance of BRAF testing to aid in diagnosis. CONCLUSIONS: Our study highlights an uncommon and potentially challenging histologic pattern of ameloblastoma for which a coordinated approach using clinical, radiographic, histologic, and molecular studies are needed for timely and accurate diagnosis.
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 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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".