Abstract

Background

Static [18F]-F-DOPA PET images are currently used for identifying patients with glioma recurrence/progression after treatment, although the additional diagnostic value of dynamic parameters remains unknown in this setting. The aim of this study was to evaluate the performances of static and dynamic [18F]-F-DOPA PET parameters for detecting patients with glioma recurrence/progression as well as assess further relationships with patient outcome.

Methods

Fifty-one consecutive patients who underwent an [18F]-F-DOPA PET for a suspected glioma recurrence/progression at post-resection MRI, were retrospectively included. Static parameters, including mean and maximum tumor-to-normal-brain (TBR) ratios, tumor-to-striatum (TSR) ratios, and metabolic tumor volume (MTV), as well as dynamic parameters with time-to-peak (TTP) values and curve slope, were tested for predicting the following: (1) glioma recurrence/progression at 6 months after the PET exam and (2) survival on longer follow-up.

Results

All static parameters were significant predictors of glioma recurrence/progression (accuracy ≥ 94%) with all parameters also associated with mean progression-free survival (PFS) in the overall population (all p < 0.001, 29.7 vs. 0.4 months for TBRmax, TSRmax, and MTV). The curve slope was the sole dynamic PET predictor of glioma recurrence/progression (accuracy = 76.5%) and was also associated with mean PFS (p < 0.001, 18.0 vs. 0.4 months). However, no additional information was provided relative to static parameters in multivariate analysis.

Conclusion

Although patients with glioma recurrence/progression can be detected by both static and dynamic [18F]-F-DOPA PET parameters, most of this diagnostic information can be achieved by conventional static parameters.

Details

Title
Use of static and dynamic [18F]-F-DOPA PET parameters for detecting patients with glioma recurrence or progression
Author
Zaragori Timothée 1 ; Ginet Merwan 2 ; Pierre-Yves, Marie 3 ; Roch Véronique 2 ; Grignon, Rachel 2 ; Gauchotte Guillaume 4 ; Rech Fabien 5 ; Blonski, Marie 6 ; Lamiral Zohra 7 ; Taillandier Luc 6 ; Imbert Laëtitia 8 ; Verger Antoine 8   VIAFID ORCID Logo 

 Université de Lorraine, CHRU-Nancy, Department of Nuclear Medicine & Nancyclotep Imaging platform, Nancy, France; Université de Lorraine, IADI, INSERM, UMR 1254, Nancy, France (GRID:grid.29172.3f) (ISNI:0000 0001 2194 6418) 
 Université de Lorraine, CHRU-Nancy, Department of Nuclear Medicine & Nancyclotep Imaging platform, Nancy, France (GRID:grid.29172.3f) 
 Université de Lorraine, CHRU-Nancy, Department of Nuclear Medicine & Nancyclotep Imaging platform, Nancy, France (GRID:grid.29172.3f); Université de Lorraine, INSERM, U1116, Nancy, France (GRID:grid.29172.3f) (ISNI:0000 0001 2194 6418) 
 Université de Lorraine, CHRU-Nancy, Department of Pathology, Nancy, France (GRID:grid.29172.3f); Université de Lorraine, INSERM U1256, Nancy, France (GRID:grid.29172.3f) (ISNI:0000 0001 2194 6418) 
 Université de Lorraine, CHRU-Nancy, Department of Neurosurgery, Nancy, France (GRID:grid.29172.3f); Université de Lorraine, Centre de Recherche en Automatique de Nancy CRAN, CNRS UMR 7039, Nancy, France (GRID:grid.29172.3f) (ISNI:0000 0001 2194 6418) 
 Université de Lorraine, Centre de Recherche en Automatique de Nancy CRAN, CNRS UMR 7039, Nancy, France (GRID:grid.29172.3f) (ISNI:0000 0001 2194 6418); Université de Lorraine, CHRU-Nancy, Department of Neuro-oncology, Nancy, France (GRID:grid.29172.3f) 
 Université de Lorraine, INSERM, U1116, Nancy, France (GRID:grid.29172.3f) (ISNI:0000 0001 2194 6418) 
 Université de Lorraine, CHRU-Nancy, Department of Nuclear Medicine & Nancyclotep Imaging platform, Nancy, France (GRID:grid.29172.3f); Université de Lorraine, IADI, INSERM, UMR 1254, Nancy, France (GRID:grid.29172.3f) (ISNI:0000 0001 2194 6418) 
Publication year
2020
Publication date
Dec 2020
Publisher
Springer Nature B.V.
e-ISSN
2191219X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2407739323
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.