Prognostic value of visual IMPeTUs criteria and metabolic tumor burden at baseline [

FDG Imaging MTV Myeloma PET

Journal

EJNMMI research
ISSN: 2191-219X
Titre abrégé: EJNMMI Res
Pays: Germany
ID NLM: 101560946

Informations de publication

Date de publication:
28 May 2024
Historique:
received: 05 04 2024
accepted: 22 05 2024
medline: 29 5 2024
pubmed: 29 5 2024
entrez: 28 5 2024
Statut: epublish

Résumé

2-[ Patients with MM who underwent a baseline [ A total of 40 patients with NDMM were included in the study. The observers agreement in the analysis [18F]FDG PET/CT images was substantial for the presence of spine FL, extra spine FL, at least one fracture and paramedullary disease (Cohen's kappa 0.79, 0.87, 0.75 and 0.64, respectively). For the presence of skull FL and extramedullary disease the agreement was moderate (Cohen's kappa 0.56 and 0.53, respectively). Among [ Our work confirms the reproducibility IMPeTUs criteria. Furthermore, it demonstrates that a high number of FL (n > 10; IMPeTUs F group 4), reflecting a high [

Sections du résumé

BACKGROUND BACKGROUND
2-[
METHODS METHODS
Patients with MM who underwent a baseline [
RESULTS RESULTS
A total of 40 patients with NDMM were included in the study. The observers agreement in the analysis [18F]FDG PET/CT images was substantial for the presence of spine FL, extra spine FL, at least one fracture and paramedullary disease (Cohen's kappa 0.79, 0.87, 0.75 and 0.64, respectively). For the presence of skull FL and extramedullary disease the agreement was moderate (Cohen's kappa 0.56 and 0.53, respectively). Among [
CONCLUSION CONCLUSIONS
Our work confirms the reproducibility IMPeTUs criteria. Furthermore, it demonstrates that a high number of FL (n > 10; IMPeTUs F group 4), reflecting a high [

Identifiants

pubmed: 38806885
doi: 10.1186/s13550-024-01113-6
pii: 10.1186/s13550-024-01113-6
doi:

Types de publication

Journal Article

Langues

eng

Pagination

51

Informations de copyright

© 2024. The Author(s).

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Auteurs

Silvano Marchiori (S)

Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, CHU of Liege, Liège, Belgium. smarchiori@chuliege.be.

François Cousin (F)

Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, CHU of Liege, Liège, Belgium.

Iraklis Papadopoulos (I)

Biostatistics and Research Methods Center (B-STAT), University of Liege, Liège, Belgium.

Claire Bernard (C)

Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, CHU of Liege, Liège, Belgium.

Marie Thys (M)

Medico-Economic Information Department / Data Analysis, CHU of Liège, Liège, Belgium.

Bernard De Prijck (B)

Department of Hematology, CHU de Liège, Liège, Belgium.

Michelle Pirotte (M)

Department of Hematology, CHU de Liège, Liège, Belgium.

Anne-Françoise Donneau (AF)

Biostatistics and Research Methods Center (B-STAT), University of Liege, Liège, Belgium.

Roland Hustinx (R)

Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, CHU of Liege, Liège, Belgium.
GIGA-CRC in Vivo Imaging, University of Liege, Liège, Belgium.

Jo Caers (J)

Department of Hematology, CHU de Liège, Liège, Belgium.
Laboratory of Hematology, GIGA I3, University of Liège, Liège, Belgium.

Nadia Withofs (N)

Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, CHU of Liege, Liège, Belgium.
GIGA-CRC in Vivo Imaging, University of Liege, Liège, Belgium.

Classifications MeSH