DIPG-59. RADIATION-INDUCED DIPG IN A CHILD PREVIOUSLY IRRADIATED FOR CRANIOPHARYNGIOMA: CASE REPORT AND LITERATURE REVIEW
Bibliographic record
Abstract
Abstract BACKGROUND Radiation-induced second malignancies occur in a subset of patients following cranial radiation therapy (RT). In Craniopharyngioma (CP), adjuvant RT is commonly recommended for residual tumor or recurrence, and radiation-induced malignant gliomas (RIMGs) are rarely reported. METHODS We report a case of radiation-induced diffuse intrinsic pontine glioma (DIPG) in pediatric Craniopharyngioma and conducted a review of previously reported cases. RESULTS A 14-year-old boy presented with complaints of headaches and vomiting for 1 month; difficulty in walking, and slurred speech for 1 week, with Lansky Performance Score (LPS) of 20. Eight years before this admission, he underwent surgical excision and 3D-conformal RT for Craniopharyngioma. His recent MRI brain was suggestive of DIPG and after a multidisciplinary discussion re-irradiation (30Gy in 10 fractions) was given. He has been alive for 5 months since diagnosis with improved symptoms and LPS (70). Including the index case, 19 cases of RIMGs in CP were identified. All except one were reported from high-income countries. Only 4 involved the pons/brainstem. The median age at CP diagnosis was 7.0 years (2.0-22.0 years), and with RIMG was 18 (6.8-41.0 years). Median latency period was 10.0 years (4.5-25.0 years). The female-to-male ratio was 1.8:1. The median previous RT dose was 54.8 Gy (49.3-60.1 Gy) with 37% cases treated with 3D conformal and 37% with conventional RT (not specified in 26%). Cerebral cortex (66.6%) was the most common site for the RIMG with temporal lobe predisposition. Chemotherapy was given in 56%, surgical excision in 50% and repeat RT in 31% cases with a median survival of 4 months (0-13 months). CONCLUSION We report the first case of radiation-induced DIPG in pediatric Craniopharyngioma in an LMIC. RIMG appears to be a rare occurrence in CP and doesn’t seem to be associated with the RT type. The overall prognosis is extremely poor.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| 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".