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      Use of static and dynamic [ 18F]-F-DOPA PET parameters for detecting patients with glioma recurrence or progression

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          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 TBR max, TSR max, 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.

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          Most cited references34

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            European Association for Neuro-Oncology (EANO) guideline on the diagnosis and treatment of adult astrocytic and oligodendroglial gliomas.

            The European Association for Neuro-Oncology guideline provides recommendations for the clinical care of adult patients with astrocytic and oligodendroglial gliomas, including glioblastomas. The guideline is based on the 2016 WHO classification of tumours of the central nervous system and on scientific developments since the 2014 guideline. The recommendations focus on pathological and radiological diagnostics, and the main treatment modalities of surgery, radiotherapy, and pharmacotherapy. In this guideline we have also integrated the results from contemporary clinical trials that have changed clinical practice. The guideline aims to provide guidance for diagnostic and management decisions, while limiting unnecessary treatments and costs. The recommendations are a resource for professionals involved in the management of patients with glioma, for patients and caregivers, and for health-care providers in Europe. The implementation of this guideline requires multidisciplinary structures of care, and defined processes of diagnosis and treatment.
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              Joint EANM/EANO/RANO practice guidelines/SNMMI procedure standards for imaging of gliomas using PET with radiolabelled amino acids and [ 18 F]FDG: version 1.0

              These joint practice guidelines, or procedure standards, were developed collaboratively by the European Association of Nuclear Medicine (EANM), the Society of Nuclear Medicine and Molecular Imaging (SNMMI), the European Association of Neurooncology (EANO), and the working group for Response Assessment in Neurooncology with PET (PET-RANO). Brain PET imaging is being increasingly used to supplement MRI in the clinical management of glioma. The aim of these standards/guidelines is to assist nuclear medicine practitioners in recommending, performing, interpreting and reporting the results of brain PET imaging in patients with glioma to achieve a high-quality imaging standard for PET using FDG and the radiolabelled amino acids MET, FET and FDOPA. This will help promote the appropriate use of PET imaging and contribute to evidence-based medicine that may improve the diagnostic impact of this technique in neurooncological practice. The present document replaces a former version of the guidelines published in 2006 (Vander Borght et al. Eur J Nucl Med Mol Imaging. 33:1374–80, 2006), and supplements a recent evidence-based recommendation by the PET-RANO working group and EANO on the clinical use of PET imaging in patients with glioma (Albert et al. Neuro Oncol. 18:1199–208, 2016). The information provided should be taken in the context of local conditions and regulations.
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                Author and article information

                Contributors
                a.verger@chru-nancy.fr
                Journal
                EJNMMI Res
                EJNMMI Res
                EJNMMI Research
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                2191-219X
                29 May 2020
                29 May 2020
                2020
                : 10
                : 56
                Affiliations
                [1 ]Department of Nuclear Medicine & Nancyclotep Imaging platform, Université de Lorraine, CHRU-Nancy, F-54000 Nancy, France
                [2 ]GRID grid.29172.3f, ISNI 0000 0001 2194 6418, IADI, INSERM, UMR 1254, , Université de Lorraine, ; F-54000 Nancy, France
                [3 ]GRID grid.29172.3f, ISNI 0000 0001 2194 6418, INSERM, U1116, , Université de Lorraine, ; F-54000 Nancy, France
                [4 ]Department of Pathology, Université de Lorraine, CHRU-Nancy, F-54000 Nancy, France
                [5 ]GRID grid.29172.3f, ISNI 0000 0001 2194 6418, INSERM U1256, , Université de Lorraine, ; F-54000 Nancy, France
                [6 ]Department of Neurosurgery, Université de Lorraine, CHRU-Nancy, F-54000 Nancy, France
                [7 ]GRID grid.29172.3f, ISNI 0000 0001 2194 6418, Centre de Recherche en Automatique de Nancy CRAN, CNRS UMR 7039, , Université de Lorraine, ; F-54000 Nancy, France
                [8 ]Department of Neuro-oncology, Université de Lorraine, CHRU-Nancy, F-54000 Nancy, France
                Author information
                http://orcid.org/0000-0003-2194-0328
                Article
                645
                10.1186/s13550-020-00645-x
                7260331
                32472232
                52370e51-40bf-4f48-8fc2-c0f10205cdcd
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 March 2020
                : 13 May 2020
                Categories
                Original Research
                Custom metadata
                © The Author(s) 2020

                Radiology & Imaging
                [18f]-f-dopa,glioma,recurrence,dynamic analysis,amino-acid pet
                Radiology & Imaging
                [18f]-f-dopa, glioma, recurrence, dynamic analysis, amino-acid pet

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