2024 Update of the North American Consensus Guidelines for Pediatric Administered Radiopharmaceutical Activities
Bibliographic record
Abstract
The 2024 update of the North American consensus guidelines for pediatric administered radiopharmaceutical activities (NAGL) is presented. Under the auspices of the Image Gently Alliance, a working group of 19 pediatric nuclear medicine experts, including clinicians, technologists, and physicists, worked for 2 y to update the 2016 NAGL, its most recent version. Building on previous success, the current recommendations regarding pediatric diagnostic nuclear medicine were reviewed systematically regarding their continued pertinence, the need for modification, and whether any recent protocols should be added. The working group reviewed and approved the 2024 update of the NAGL, and the update was subsequently approved by the Image Gently Alliance in the spring of 2024. None of the 23 protocols listed in the 2016 NAGL were removed; however, 9 were modified, and 6 new protocols (<sup>13</sup>N-NH<sub>3</sub> and <sup>83</sup>Rb for cardiac imaging; <sup>18</sup>F-DOPA, <sup>68</sup>Ga-DOTATATE, <sup>68</sup>Ga-DOTATOC, and Na<sup>123</sup>I for thyroid cancer imaging) were added. Five of 6 new protocols involve PET imaging, reflecting an increase in the routine use of PET in children in the past decade. This 2024 update addresses the impact of advances in imaging equipment, reconstruction, image processing, and clinical practice and the introduction of new radiopharmaceutical agents into the practice of pediatric nuclear medicine.
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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 | 0.029 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 0.011 |
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".