18F-DOPA, a Clinically Available PET Tracer to Study Brain Inflammation?

Sala, Quentin; Métellus, Philippe; Taïeb, David; Kaphan, Elsa; Figarella‐Branger, Dominique; Guedj, Éric

doi:10.1097/rlu.0000000000000383

Cited by 42 publications

(37 citation statements)

References 7 publications

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“…Although amino acid PET shows high accuracy for the detection of brain tumours [31], tracer uptake in non-neoplastic brain lesions has to be taken into account. Thus, unspecific amino acid uptake in the brain has been reported in multiple sclerosis and other inflammatory lesions, vascular malformations, ischemic lesions, hematomas, etc [32–36]. Moreover, amino acid PET may be negative in a significant proportion of low-grade gliomas [37, 38].…”

Section: Introductionmentioning

confidence: 99%

Amino acid PET and MR perfusion imaging in brain tumours

Filß

Cicone

Shah

et al. 2017

Clin Transl Imaging

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PurposeDespite the excellent capacity of the conventional MRI to image brain tumours, problems remain in answering a number of critical diagnostic questions. To overcome these diagnostic shortcomings, PET using radiolabeled amino acids and perfusion-weighted imaging (PWI) are currently under clinical evaluation. The role of amino acid PET and PWI in different diagnostic challenges in brain tumours is controversial.MethodsBased on the literature and experience of our centres in correlative imaging with PWI and PET using O-(2-[18F]fluoroethyl)-l-tyrosine or 3,4-dihydroxy-6-[18F]-fluoro-l-phenylalanine, the current role and shortcomings of amino acid PET and PWI in different diagnostic challenges in brain tumours are reviewed. Literature searches were performed on PubMed, and additional literature was retrieved from the reference lists of identified articles. In particular, all studies in which amino acid PET was directly compared with PWI were included.ResultsPWI is more readily available, but requires substantial expertise and is more sensitive to artifacts than amino acid PET. At initial diagnosis, PWI and amino acid PET can help to define a site for biopsy but amino acid PET appears to be more powerful to define the tumor extent. Both methods are helpful to differentiate progression or recurrence from unspecific posttherapeutic changes. Assessment of therapeutic efficacy can be achieved especially with amino acid PET, while the data with PWI are sparse.ConclusionBoth PWI and amino acid PET add valuable diagnostic information to the conventional MRI in the assessment of patients with brain tumours, but further studies are necessary to explore the complementary nature of these two methods.

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Section: Introductionmentioning

confidence: 99%

Amino acid PET and MR perfusion imaging in brain tumours

Filß

Cicone

Shah

et al. 2017

Clin Transl Imaging

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“…Fifty-one of these patients were retrospectively selected on the basis that they had an initial history of surgicallyresected glioma and that the considered 18 F-FDopa PET had been prescribed for differentiating recurrence/tumor progression from post-therapeutic effects after a non-contributive MRI. As usual in our department, a minimum delay of 2 months is always respected between the surgery or the end of the radiotherapy and performing 18 F-FDopa PET in order to reduce the risk of 18 F-FDopa PET false positives [11].…”

Section: Materials and Methods Patientsmentioning

confidence: 99%

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

Zaragori

Ginet

Marie

et al. 2020

Preprint

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Background: Static 18 F-FDopa 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 the present study was to evaluate the performances of static and dynamic 18 F-FDopa PET parameters for detecting patients with glioma recurrence/progression as well as to assess further relationships with patient outcome. Fifty-one consecutive patients who underwent an 18 F-FDopa 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), 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: 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 a 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 the 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 18 F-FDopa PET parameters, most of this diagnostic information can be achieved by conventional static parameters.

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“…Amino-acid PET has been proposed as a criterion for detecting glioma recurrence by the Response Assessment in Neuro-Oncology (RANO) group [3] and has become a current indication for differentiating glioma recurrence from treatment-induced changes, as stated in the recent joint European Association of Nuclear Medicine (EANM)/European Association of Neuro-Oncology (EANO)/RANO practice guidelines [4]. 18 F-FDopa PET is an amino acid PET tracer for which the ability to diagnose glioma recurrence has been previously established [5][6][7]. In particular, 18 F-FDopa PET was found to detect glioma recurrence with an accuracy as high as 82% in a retrospective study of 110 patients, in which the lesion-to-normal-tissue ratio was additionally predictive of PFS [8].…”

Section: Introductionmentioning

confidence: 99%

“…18 F-FDopa PET is an amino acid PET tracer for which the ability to diagnose glioma recurrence has been previously established [5][6][7]. In particular, 18 F-FDopa PET was found to detect glioma recurrence with an accuracy as high as 82% in a retrospective study of 110 patients, in which the lesion-to-normal-tissue ratio was additionally predictive of PFS [8]. More recently, in a study in which glioma recurrence was proven histologically, 18 F-FDopa PET accuracy was reported to reach 84%, using maximum 18 F-FDopa uptake as diagnostic parameter [9].…”

Section: Introductionmentioning

confidence: 99%

“…In particular, 18 F-FDopa PET was found to detect glioma recurrence with an accuracy as high as 82% in a retrospective study of 110 patients, in which the lesion-to-normal-tissue ratio was additionally predictive of PFS [8]. More recently, in a study in which glioma recurrence was proven histologically, 18 F-FDopa PET accuracy was reported to reach 84%, using maximum 18 F-FDopa uptake as diagnostic parameter [9]. This accuracy for detecting glioma recurrence was even higher, reaching 96%, in a prospective, albeit smaller study of 28 patients [10].…”

Section: Introductionmentioning

confidence: 99%

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

Zaragori

Ginet

Marie

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Static 18 F-FDopa 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 18 F-FDopa 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 18 F-FDopa 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: 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 18 F-FDopa PET parameters, most of this diagnostic information can be achieved by conventional static parameters. Further studies are warranted to investigate the relevance of such 18 F-FDopa kinetics in populations involving only high-grade gliomas.

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18F-DOPA, a Clinically Available PET Tracer to Study Brain Inflammation?

Cited by 42 publications

References 7 publications

Amino acid PET and MR perfusion imaging in brain tumours

Amino acid PET and MR perfusion imaging in brain tumours

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

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

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