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Record W3084658128 · doi:10.2196/17850

Prospective Comparison of 18F-Choline Positron Emission Tomography/Computed Tomography (PET/CT) and 18F-Fluorodeoxyglucose (FDG) PET/CT in the Initial Workup of Multiple Myeloma: Study Protocol of a Prospective Imaging Trial

2020· article· en· W3084658128 on OpenAlexvenueno aff
Charles Mesguich, Cyrille Hulin, V. Latrabe, Julien Asselineau, Laurence Bordenave, Paul Perez, Elif Hindié, Gérald Marit

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePositron emission tomographyPositron Emission Tomography-Computed TomographyNuclear medicineRadiologyTomographyFluorodeoxyglucosePET-CTProspective cohort studyPreclinical imagingComputed tomographyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: The International Myeloma Working Group recommends the use of 18-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) for treatment response evaluation, as it is superior to magnetic resonance imaging (MRI). However, at initial staging, the sensitivity of FDG-PET remains inferior to that of MRI. Therefore, there is a need for an imaging technique that could have a sensitivity equal to that of MRI at diagnosis and could serve to evaluate therapy. 18F-choline has shown increased sensitivity when compared with 18-FDG, with about 75% more lesions detected in patients with relapsed or progressive multiple myeloma (MM). OBJECTIVE: Our primary objective is to prospectively compare the detection rate of bone lesions by 18F-choline PET/CT (FCH-PET) and FDG-PET in newly diagnosed MM. Our secondary objectives are to assess the accuracy of both PET modalities for the detection of bone lesions and the diagnosis of diffuse disease, to assess the detection rate of extramedullary lesions. METHODS: We will prospectively include 30 patients in a paired comparative accuracy study. Patients with de novo MM will undergo FCH-PET, FDG-PET, and whole-body MRI (WB-MRI) within a 3-week period. WB-MRI will be composed of conventional sequences on the spine and pelvis and of whole-body diffusion axial sequences. The following 6 skeletal areas will be defined: skull, sternum/costal grid, spine, pelvis, superior limbs, and inferior limbs. The number of focal lesions, their respective localization, and intensity of uptake will be retrieved for each skeletal area. Readings will be performed blinded from other imaging techniques. The reference standard will be WB-MRI. Focal lesions present on PET/CT but not on WB-MRI will require a decision made with a consensus of experts based on clinical and imaging data. The number of bone lesions and number of extramedullary lesions will be compared using the Wilcoxon test. The accuracy of FCH-PET and FDG-PET will be compared using the McNemar test. RESULTS: The study started in September 2019, and enrollment is ongoing. As of June 2020, 8 participants have been included. Data collection is expected to be completed in June 2021, and the results are expected to be available in December 2021. CONCLUSIONS: This study will assess if FCH-PET is superior to FDG-PET for the evaluation of MM tumor burden. This will pave the way for future prospective evaluations of the prognostic value of 18-FCH for treatment response evaluation in MM patients. Additionally, this work may provide new perspectives for better assessment of the risk of smoldering MM progressing to MM. TRIAL REGISTRATION: ClinicalTrials.gov NCT03891914; https://clinicaltrials.gov/ct2/show/NCT03891914. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/17850.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.040
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.024
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0070.003

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 head0.125
GPT teacher head0.506
Teacher spread0.381 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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".

Quick stats

Citations4
Published2020
Admission routes1
Has abstractyes

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