Pediatric Cancer Predisposition Imaging: Focus on Whole-Body MRI
Bibliographic record
Abstract
The American Association for Cancer Research convened a meeting of international pediatric oncologists, geneticists, genetic counselors, and radiologists expert in childhood cancer predisposition syndromes (CPS) in October 2016 to propose consensus surveillance guidelines. Imaging plays a central role in surveillance for most, though not all, syndromes discussed. While encompassing the full gamut of modalities, there is increasing emphasis on use of nonionizing radiation imaging options such as magnetic resonance imaging (MRI) in children and adolescents, especially in the pediatric CPS population. In view of rapid evolution and widespread adoption of whole-body MRI (WBMRI), the purpose of our review is to address WBMRI in detail. We discuss its place in the surveillance of a range of pediatric CPS, the technical and logistical aspects of acquiring and interpreting these studies, and the inherent limitations of WBMRI. We also address issues associated with sedation and use of gadolinium-based contrast agents in MRI in children.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".