Consensus Nomenclature for Radionuclide Therapy: Initial Recommendations from Nuclear Medicine Global Initiative
Bibliographic record
Abstract
Since its inception in 2012, the Nuclear Medicine Global Initiative (NMGI) of the Society of Nuclear Medicine and Molecular Imaging has played an important role in addressing significant challenges in the field of nuclear medicine and molecular imaging. The first 3 projects were dedicated to standardizing pediatric nuclear medicine practices, addressing the global challenges of radionuclide access and availability, and assessing the educational and training initiatives on theranostics across the globe. These efforts aimed to advance human health, foster worldwide educational collaboration, and standardize procedural guidelines to enhance quality and safety in nuclear medicine practice. In its latest project, NMGI aimed to develop a unified nomenclature for systemic radionuclide therapy in nuclear medicine, addressing the diverse terminology currently used. An online survey was distributed to NMGI member organizations, drawing participation from various geographical locations and disciplines. The survey anonymously collected responses from physicians, physicists, scientists, radiopharmacists, radiopharmaceutical scientists, dosimetrists, technologists, and nurse managers, totaling 240 responses from 30 countries. Findings revealed a prevailing use of the term targeted radionuclide therapy for radionuclide therapy, with 52% of respondents expressing a preference for this term. In contrast, approximately 37% favored "radiopharmaceutical therapy," whereas 11% favored "molecular radionuclide therapy." Other key terms under the umbrella of targeted radionuclide therapy were also discussed to achieve a consensus on terminology. NMGI efforts to standardize terminology in this dynamic and fluid field should improve communication within the field, better reflect the technology used, enable comparison of results, and ultimately lead to improved patient outcomes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".