Fast STIR Whole-Body MR Imaging in Children
Bibliographic record
Abstract
Fast spin-echo short inversion time inversion-recovery (STIR) whole-body magnetic resonance (MR) imaging is an evolving technique that allows imaging of the entire body in a reasonable time. Its wide availability and lack of radiation exposure makes this method appealing for the evaluation of children. Since 2001, the authors conducted 140 pediatric whole-body MR imaging studies and correlated the findings with those from conventional imaging examinations. Bone marrow lesions, including marrow infiltration from lymphoma, metastases, and tumor-related edema, appeared with high signal intensity and were more easily detected on STIR images than with scintigraphy. Focal parenchymal lesions could be distinguished by their slightly different signal intensity, but pathologic lymph nodes could not be differentiated from normal nodes on the basis of signal intensity. The STIR technique is highly sensitive for detection of pathologic lesions, but it is not specific for malignancy; thus, the method cannot be used to differentiate benign conditions from malignant neoplastic lesions. Although fast STIR whole-body MR imaging permits evaluation of the entire skeleton and all viscera with a single examination, more experience and data are needed to determine its efficacy for staging neoplasms and assessing other multifocal disease 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".