Whole-Body MR Imaging for Staging of Malignant Tumors in Pediatric Patients: Results of the American College of Radiology Imaging Network 6660 Trial
Bibliographic record
Abstract
PURPOSE: To compare whole-body magnetic resonance (MR) imaging with conventional imaging for detection of distant metastases in pediatric patients with common malignant tumors. MATERIALS AND METHODS: This institutional review board-approved, HIPAA-compliant, multicenter prospective cohort study included 188 patients (109 male, 79 female; mean age, 10.2 years; range, < 1 to 21 years) with newly diagnosed lymphoma, neuroblastoma, or soft-tissue sarcoma. Informed consent was obtained and all patients underwent noncontrast material-enhanced whole-body MR imaging and standard-practice conventional imaging. All images were reviewed centrally by 10 pairs of readers. An independent panel verified the presence or absence of distant metastases. Detection of metastasis with whole-body MR and conventional imaging was quantified by using the area under the receiver operating characteristic curve (AUC). The effects of tumor subtype, patient age, and distant skeletal and pulmonary disease on diagnostic accuracy were also analyzed. RESULTS: Of the 134 eligible patients, 66 (33 positive and 33 negative for metastasis) were selected for image review and analysis. Whole-body MR imaging did not meet the noninferiority criterion for accuracy when compared with conventional imaging for detection of metastasis (difference between average AUCs was -0.03 [95% confidence interval: -0.10, 0.04]); however, the average AUC for solid tumors was significantly higher than that for lymphomas (P = .006). More skeletal metastases were detected by using whole-body MR imaging than by using conventional imaging (P = .03), but fewer lung metastases were detected (P < .001). Patient age did not affect accuracy. CONCLUSION: The noninferior accuracy for diagnosis of distant metastasis in patients with common pediatric tumors was not established for the use of whole-body MR imaging compared with conventional methods. However, improved accuracy was seen with whole-body MR imaging in patients with nonlymphomatous tumors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".