Malignant Transformation of Intracranial Epidermoid Cyst to Squamous Cell Carcinoma, Case Report and Literature Review
Bibliographic record
Abstract
Intracranial Epidermoid cysts (ECs) are rare, benign tumor of central nervous system that appears from maintain ectodermal implants. Malignant transformation of an EC to squamous-cell carcinoma (SCC) is rarely reported. Intracranial squamous cell carcinoma has known as a poor prognosis condition that optimal modalities remain uncertain. We present the case of 43-years old male complained 3 months severe headache and right eye hemianopia. Primary evaluation depicted right homogenous brain mass which was successfully totally removed. Pathological assessment found epidermoid cyst without any sign of malignancy. Six months later, patient was referred with episodes of intermittent headache and right eye blindness. After initial imaging, new tumor was growth in same site of frontal epidermoid cyst. Second surgery was performed and pathological report discloses to be a malignant SCC. SCC transformation was confirmed by two expert neuro- pathologists. The exact underlying mechanism causing malignant transformation is not definitely known and it seems SCC may have been transformed due to chronic inflammatory respond to epidermoid cyst. Literature reviews demonstrate that, although, optimal total resection in addition adjuvant radiotherapy is the recommended management of choice, patient’s general survival of this condition is generally poor and long-term follow-up is important.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".