White matter and information processing speed following treatment with cranial-spinal radiation for pediatric brain tumor.
Bibliographic record
Abstract
OBJECTIVE: We compared the structure of specific white matter tracts and information processing speed between children treated for posterior fossa tumors with cranial-spinal radiation (n = 30), or with surgery +/- focal radiation (n = 29), and healthy children (n = 37). METHOD: Probabilistic diffusion tensor imaging (DTI) tractography was used to delineate the inferior longitudinal fasciculi, optic radiation, inferior frontal occipital fasciculi, and uncinate fasciculi bilaterally. Information processing speed was measured using the coding and symbol search subtests of the Wechsler Intelligence Scales, and visual matching, pair cancellation, and rapid picture naming subtests of the Woodcock-Johnson Test of Cognitive Ability, 3rd revision. We examined group differences using repeated measures MANOVAs and path analyses were used to test the relations between treatment, white matter structure of the tracts, and information processing speed. RESULTS: DTI indices of the optic radiations, the inferior longitudinal fasciculi, and the inferior fronto-occipital fasciculi differed between children treated with cranial-spinal radiation and children treated with surgery +/- focal radiation, and healthy controls (p = .045). Children treated with cranial-spinal radiation also exhibited lower processing speed scores relative to healthy control subjects (p = .002). Notably, we observed that group differences in information processing speed were related to the structure of the right optic radiation (p = .002). CONCLUSION: We show that cranial-spinal radiation may have a negative impact on information processing speed via insult to the right optic radiations. (PsycINFO Database Record
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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 | 0.000 | 0.000 |
| 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".