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Record W2920645185 · doi:10.1055/a-0828-8654

Whole-Body [18F]-FDG-PET/MRI for Oncology: A Consensus Recommendation

2019· article· en· W2920645185 on OpenAlex
Lale Umutlu, Thomas Beyer, Johannes Grueneisen, Christoph Rischpler, Harald H. Quick, Patrick Veit‐Haibach, Matthias Eiber, Sandra Purz, Gerald Antoch, Sergios Gatidis, Konstantin Nikolaou, Jürgen F. Schaefer, Ivo Rausch, Ken Herrmann

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren · 2019
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineMedical physicsPositron emission tomographyNuclear medicineMagnetic resonance imagingWhole body imagingRadiology

Abstract

fetched live from OpenAlex

Combined PET/MR imaging (PET/MRI) was proposed for patient management in 2006 with first commercial versions of integrated whole-body systems becoming available as of 2010. PET/MRI followed the prior evolution of hybrid imaging as attested by the successful adoption of combined PET/CT and SPECT/CT since the early 2000 s. Today, around 150 whole-body PET/MRI systems have become operational worldwide. One of the main application fields of PET/MRI is oncologic imaging. Despite the increasing use of PET/MRI, little governance regarding standardized PET/MRI protocols has been provided to date. Standardization and harmonization of imaging protocols is, however, mandatory for efficient on-site patient management and multi-center studies. This document summarizes consensus recommendations on key aspects of patient referral and preparation, PET/MRI workflow and imaging protocols, as well as reporting strategies for whole-body [18F]-FDG-PET/MRI. These recommendations were created by early adopters and key experts in the field of PET, MRI and PET/MRI. This document is intended to provide guidance for the harmonization and standardization of PET/MRI today and to support wider clinical adoption of this imaging modality for the benefit of patients. CITATION FORMAT: · Umutlu L, Beyer T, Grueneisen JS et al. Whole-Body [18F]-FDG-PET/MRI for Oncology: A Consensus Recommendation. Fortschr Röntgenstr 2019; 191: 289 - 297.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.031
GPT teacher head0.358
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it