EANM/SNMMI guideline/procedure standard for [18F]FDG hybrid PET use in infection and inflammation in adults v2.0
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Introduction Hybrid [ 18 F]FDG PET imaging is currently the method of choice for a wide variety of infectious and inflammatory disorders and was recently adopted in several clinical guidelines. A large amount of evidence-based articles, guidelines and appropriate use criteria have been published since the first version of this guideline in 2013. Purpose To provide updated evidence-based information to assist physicians in recommending, performing and interpreting hybrid [ 18 F]FDG PET examinations for infectious and inflammatory disorders in the adult population. Methods A systematic literature search of evidence-based articles using whole-body [ 18 F]FDG hybrid imaging on the indications covered within this guideline was performed. All systematic reviews and meta-analyses published within the last 10 years until January 2023 were identified in PubMed/Medline or Cochrane. For each indication covered in this manuscript, diagnostic performance was provided based on meta-analyses or systematic reviews. If not available, results from prospective or retrospective studies were considered based on predefined selection criteria. Results and conclusions Hybrid [ 18 F]FDG PET is extremely useful in the work-up and management of adults with infectious and inflammatory diseases, as supported by extensive and rapidly growing evidence-based literature and adoption in clinical guidelines. Practical recommendations are provided describing evidence-based indications as well as interpretation criteria and pitfalls. Monitoring treatment response is the most challenging but insufficiently studied potential application in infection and inflammation imaging.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 it