Dose–volume metrics and their relation to memory performance in pediatric brain tumor patients: A preliminary study
Bibliographic record
Abstract
BACKGROUND: Advances in radiation treatment (RT), specifically volumetric planning with detailed dose and volumetric data for specific brain structures, have provided new opportunities to study neurobehavioral outcomes of RT in children treated for brain tumor. The present study examined the relationship between biophysical and physical dose metrics and neurocognitive ability, namely learning and memory, 2 years post-RT in pediatric brain tumor patients. PROCEDURE: The sample consisted of 26 pediatric patients with brain tumor, 14 of whom completed neuropsychological evaluations on average 24 months post-RT. Prescribed dose and dose-volume metrics for specific brain regions were calculated including physical metrics (i.e., mean dose and maximum dose) and biophysical metrics (i.e., integral biological effective dose and generalized equivalent uniform dose). We examined the associations between dose-volume metrics (whole brain, right and left hippocampus), and performance on measures of learning and memory (Children's Memory Scale). RESULTS: Biophysical dose metrics were highly correlated with the physical metric of mean dose but not with prescribed dose. Biophysical metrics and mean dose, but not prescribed dose, correlated with measures of learning and memory. CONCLUSIONS: These preliminary findings call into question the value of prescribed dose for characterizing treatment intensity; they also suggest that biophysical dose has only a limited advantage compared to physical dose when calculated for specific regions of the brain. We discuss the implications of the findings for evaluating and understanding the relation between RT and neurocognitive functioning.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".