18F-DOPA uptake parameters in glioma: effects of patients’ characteristics and prior treatment history

Carideo, Luciano; Minniti, Giuseppe; Mamede, Marcelo; Scaringi, Claudia; Russo, Ivana; Scopinaro, Francesco; Cicone, Francesco

doi:10.1259/bjr.20170847

Cited by 21 publications

(13 citation statements)

References 31 publications

(74 reference statements)

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“…Another potential rationale is that a sufficiently high tumor uptake is required for an accurate determination of dynamic parameters, whereas this uptake was too low in the present study in cases of an absence of any glioma recurrence/progression (median TBR mean = 0.84, see Table 2). In contrast to the previous hypotheses, the potential confounding influence of reactive tissue changes, in line with the inflammatory and healing processes induced by surgery and/or radiotherapy and/or chemotherapy [35,36] cannot be used to explain the lower diagnostic performances from dynamic parameters. Both static and dynamic parameters should normally be affected in the same manner by the complex histology of the treated sites, involving varying levels of reactive gliosis, inflammatory cells, and radiationinduced changes.…”

Section: Discussionmentioning

confidence: 80%

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

et al. 2020

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Background: Static [ 18 F]-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 [ 18 F]-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 [ 18 F]-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 [ 18 F]-F-DOPA PET parameters, most of this diagnostic information can be achieved by conventional static parameters.

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Section: Discussionmentioning

confidence: 80%

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

et al. 2020

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“…Another potential rationale is that a sufficiently high tumor uptake is required for an accurate determination of dynamic parameters, whereas this uptake was too low in the present study in cases of an absence of any glioma recurrence/progression (median TBR mean =0.84; see Table 2). In contrast to the previous hypotheses, the potential confounding influence of reactive tissue changes, in line with the inflammatory-and healing-processes induced by surgery and/or radiotherapy and/or chemotherapy [35,36] cannot be used to explain the lower diagnostic performances from dynamic parameters. Both static and dynamic parameters should normally be affected in the same manner by the complex histology of the treated sites, involving varying levels of reactive gliosis, inflammatory cells and radiation-induced changes.…”

Section: Discussionmentioning

confidence: 81%

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 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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“…This is further evidenced by dexamethasone or antiangiogenic treatment with bevacizumab not affecting amino acid uptake by brain tumors [37,38]. Prior or ongoing treatment with temozolomide, however, may impact the tumor-to-background ratio of amino acid uptake and must be considered in therapy response assessments [39].…”

Section: Positron Emission Tomography Of Cns Tumorsmentioning

confidence: 99%

The Emerging Role of Amino Acid PET in Neuro-Oncology

2018

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Imaging plays a critical role in the management of the highly complex and widely diverse central nervous system (CNS) malignancies in providing an accurate diagnosis, treatment planning, response assessment, prognosis, and surveillance. Contrast-enhanced magnetic resonance imaging (MRI) is the primary modality for CNS disease management due to its high contrast resolution, reasonable spatial resolution, and relatively low cost and risk. However, defining tumor response to radiation treatment and chemotherapy by contrast-enhanced MRI is often difficult due to various factors that can influence contrast agent distribution and perfusion, such as edema, necrosis, vascular alterations, and inflammation, leading to pseudoprogression and pseudoresponse assessments. Amino acid positron emission tomography (PET) is emerging as the method of resolving such equivocal lesion interpretations. Amino acid radiotracers can more specifically differentiate true tumor boundaries from equivocal lesions based on their specific and active uptake by the highly metabolic cellular component of CNS tumors. These therapy-induced metabolic changes detected by amino acid PET facilitate early treatment response assessments. Integrating amino acid PET in the management of CNS malignancies to complement MRI will significantly improve early therapy response assessment, treatment planning, and clinical trial design.

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18F-DOPA uptake parameters in glioma: effects of patients’ characteristics and prior treatment history

Cited by 21 publications

References 31 publications

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

Use of static and dynamic [18F]-F-DOPA 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

The Emerging Role of Amino Acid PET in Neuro-Oncology

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