Classification of Pediatric Gangliogliomas Based on the Histological Infiltration
Bibliographic record
Abstract
Ganglioglioma is a well-circumscribed low-grade glioneuronal tumor with a broad morphological spectrum. Diffuse glioneuronal tumors are used to describe cases with infiltrative growth. Molecular studies of some of these cases are consistent with ganglioglioma. This work aimed to clarify the growth patterns in ganglioglioma. The available slides and clinical and molecular information for 46 patients (50 samples) with a diagnosis of ganglioglioma under the open pediatric brain tumor atlas from the children’s brain tumor network database were reviewed to confirm the integrated diagnosis and to evaluate the growth patterns in these cases. Ten samples from nine patients were excluded as no slides were available, the integrated diagnoses were changed in seven cases (nine samples), ten cases (ten samples) were diagnosed as low-grade glial/glioneuronal tumors, and the diagnosis of ganglioglioma was confirmed in seventeen samples from sixteen patients (nine females and seven males; age ranges from eight months–19 years with a mean of 9.9 years). Infiltration is defined as the presence of neoplastic cells among the nonneoplastic parenchyma. The growth pattern was predominantly circumscribed in six cases, predominantly infiltrative in five cases, and combined growth patterns in five cases. This work confirmed the presence of an infiltrative/diffuse variant of ganglioglioma as a significant pattern. The differential diagnosis in these cases was mainly infiltrative glioma, usually IDH-wild type in this population, which may introduce a high-grade glioma in the differential. Awareness of infiltrative ganglioglioma variants should be helpful in this scenario.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".