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Record W2309119811 · doi:10.3171/2016.1.peds15580

Vulnerability of white matter to insult during childhood: evidence from patients treated for medulloblastoma

2016· article· en· W2309119811 on OpenAlexafffund
Iska Moxon‐Emre, Éric Bouffet, Michael D. Taylor, Normand Laperrière, Michael B. Sharpe, Suzanne Laughlin, Ute Bartels, Nadia Scantlebury, Nicole Law, David Malkin, Jovanka Skocic, Logan Richard, Donald Mabbott

Bibliographic record

VenueJournal of Neurosurgery Pediatrics · 2016
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsHospital for Sick ChildrenPrincess Margaret Cancer CentreUniversity of TorontoOntario Institute for Cancer ResearchPediatric Oncology Group
FundersBrain Tumour ResearchHospital for Sick ChildrenGarron Family Cancer CentreGenome British ColumbiaFondation Brain CanadaPediatric Oncology Group of OntarioChildren's Hospital FoundationCanadian Institutes of Health ResearchGenome Canada
KeywordsMedicineFractional anisotropyMedulloblastomaWhite matterNuclear medicineDiffusion MRIRadiologyMagnetic resonance imagingPathology

Abstract

fetched live from OpenAlex

OBJECTIVE Craniospinal irradiation damages the white matter in children treated for medulloblastoma, but the treatment-intensity effects are unclear. In a cross-sectional retrospective study, the effects of treatment with the least intensive radiation protocol versus protocols that delivered more radiation to the brain, in addition to the effects of continuous radiation dose, on white matter architecture were evaluated. METHODS Diffusion tensor imaging was used to assess fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity. First, regional white matter analyses and tract-based spatial statistics were conducted in 34 medulloblastoma patients and 38 healthy controls. Patients were stratified according to those treated with 1) the least intensive radiation protocol, specifically reduced-dose craniospinal irradiation plus a boost to the tumor bed only (n = 17), or 2) any other dose and boost combination that delivered more radiation to the brain, which was also termed the "all-other-treatments" group (n = 17), and comprised patients treated with standard-dose craniospinal irradiation plus a posterior fossa boost, standard-dose craniospinal irradiation plus a tumor bed boost, or reduced-dose craniospinal irradiation plus a posterior fossa boost. Second, voxel-wise dose-distribution analyses were conducted on a separate cohort of medulloblastoma patients (n = 15). RESULTS The all-other-treatments group, but not the reduced-dose craniospinal irradiation plus tumor bed group, had lower fractional anisotropy and higher radial diffusivity than controls in all brain regions (all p < 0.05). The reduced-dose craniospinal irradiation plus tumor bed boost group had higher fractional anisotropy (p = 0.05) and lower radial diffusivity (p = 0.04) in the temporal region, and higher fractional anisotropy in the frontal region (p = 0.04), than the all-other-treatments group. Linear mixed-effects modeling revealed that the dose and age at diagnosis together 1) better predicted fractional anisotropy in the temporal region than models with either alone (p < 0.005), but 2) did not better predict fractional anisotropy in comparison with dose alone in the occipital region (p > 0.05). CONCLUSIONS Together, the results show that white matter damage has a clear association with increasing radiation dose, and that treatment with reduced-dose craniospinal irradiation plus tumor bed boost appears to preserve white matter in some brain regions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.315
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations36
Published2016
Admission routes2
Has abstractyes

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