The evidence-based role of catecholaminergic PET tracers in Neuroblastoma. A systematic review and a head-to-head comparison with mIBG scintigraphy
Bibliographic record
Abstract
Abstract Background Molecular imaging is pivotal in staging and response assessment of children with neuroblastoma (NB). [123I]-metaiodobenzylguanidine (mIBG) is the standard imaging method; however, it is characterised by low spatial resolution, time-consuming acquisition procedures and difficult interpretation. Many PET catecholaminergic radiotracers have been proposed as a replacement for [123I]-mIBG, however they have not yet made it into clinical practice. We aimed to review the available literature comparing head-to-head [123I]-mIBG with the most common PET catecholaminergic radiopharmaceuticals. Methods We searched the PubMed database for studies performing a head-to-head comparison between [123I]-mIBG and PET radiopharmaceuticals including meta-hydroxyephedrine ([11C]C-HED), 18F-18F-3,4-dihydroxyphenylalanine ([18F]DOPA) [124I]mIBG and Meta-[18F]fluorobenzylguanidine ([18F]mFBG). Review articles, preclinical studies, small case series (< 5 subjects), case reports, and articles not in English were excluded. From each study, the following characteristics were extracted: bibliographic information, technical parameters, and the sensitivity of the procedure according to a patient-based analysis (PBA) and a lesion-based analysis (LBA). Results Ten studies were selected: two regarding [11C]C-HED, four [18F]DOPA, one [124I]mIBG, and three [18F]mFBG. These studies included 181 patients (range 5–46). For the PBA, the superiority of the PET method was reported in two out of ten studies (both using [18F]DOPA). For LBA, PET detected significantly more lesions than scintigraphy in seven out of ten studies. Conclusions PET/CT using catecholaminergic tracers shows superior diagnostic performance than mIBG scintigraphy. However, it is still unknown if such superiority can influence clinical decision-making. Nonetheless, the PET examination appears promising for clinical practice as it offers faster image acquisition, less need for sedation, and a single-day examination.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.006 |
| Bibliometrics | 0.026 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".