The use of multiparametric 18F-fluoro-L-3,4-dihydroxy-phenylalanine PET/MRI in post-therapy assessment of patients with gliomas

Integration of amide proton transfer-weighted imaging and methionine positron emission tomography histogram parameters enhances the prediction of isocitrate dehydrogenase mutations in adult diffuse gliomas

BACKGROUND

To evaluate whether the combination of amide proton transfer-weighted imaging (APT-WI) and methionine positron emission tomography (MET-PET) enhances the non-invasive prediction of isocitrate dehydrogenase (IDH) mutation status in adult diffuse gliomas.

RESULTS

We retrospectively analysed 28 adult patients with histologically confirmed diffuse gliomas who underwent preoperative APT-WI and MET-PET imaging at our institution. Histogram analyses were conducted for both imaging modalities, extracting parameters such as the 10th, 50th, 70th, and 90th percentiles, mean, variance, skewness, and kurtosis. Parameters between IDH-mutant and IDH-wildtype gliomas were compared using the Mann-Whitney U test. Diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis, and combined models of the two parameters were constructed using multivariable logistic regression. IDH-wildtype gliomas exhibited significantly higher APT-WI 90th percentile (APT90) values (median: 3.51%, interquartile range [IQR]: 1.92-4.23%) compared to IDH-mutant gliomas (median: 2.24%, IQR: 1.52-2.85%, p = 0.039). Similarly, IDH-wildtype gliomas showed elevated MET-PET maximum tumour-to-normal ratios (TNRmax) (median: 2.51, IQR: 2.13-3.41) compared to IDH-mutant gliomas (median: 1.62, IQR: 1.30-2.77, p = 0.020). ROC curve analysis indicated that the combined model of APT90 and TNR kurtosis achieved an area under the curve of 0.85, demonstrating superior diagnostic accuracy compared to that of single-parameter models.

CONCLUSIONS

Combining histogram-derived parameters from APT-WI and MET-PET significantly improves the diagnostic accuracy for predicting IDH mutation status in diffuse gliomas. This non-invasive approach may serve as a valuable adjunct for preoperative evaluation and the development of personalised treatment strategies in patients with gliomas.

Breaking barriers: we need a multidisciplinary approach to tackle cancer drug resistance

Most cancer-related deaths result from drug-resistant disease(1,2). However, cancer drug resistance is not a primary focus in drug development. Effectively mitigating and treating drug-resistant cancer will require advancements in multiple fields, including early detection, drug discovery, and our fundamental understanding of cancer biology. Therefore, successfully tackling drug resistance requires an increasingly multidisciplinary approach. A recent workshop on cancer drug resistance, jointly organised by Cancer Research UK, the Rosetrees Trust, and the UKRI-funded Physics of Life Network, brought together experts in cell biology, physical sciences, computational biology, drug discovery, and clinicians to focus on these key challenges and devise interdisciplinary approaches to address them. In this perspective, we review the outcomes of the workshop and highlight unanswered research questions. We outline the emerging hallmarks of drug resistance and discuss lessons from the COVID-19 pandemic and antimicrobial resistance that could help accelerate information sharing and timely adoption of research discoveries into the clinic. We envisage that initiatives that drive greater interdisciplinarity will yield rich dividends in developing new ways to better detect, monitor, and treat drug resistance, thereby improving treatment outcomes for cancer patients.

Post-treatment imaging of gliomas: challenging the existing dogmas

Gliomas are the commonest malignant central nervous system tumours in adults and imaging is the cornerstone of diagnosis, treatment, and post-treatment follow-up of these patients. With the ever-evolving treatment strategies post-treatment imaging and interpretation in glioma remains challenging, more so with the advent of anti-angiogenic drugs and immunotherapy, which can significantly alter the appearance in this setting, thus making interpretation of routine imaging findings such as contrast enhancement, oedema, and mass effect difficult to interpret. This review details the various methods of management of glioma including the upcoming novel therapies and their impact on imaging findings, with a comprehensive description of the imaging findings in conventional and advanced imaging techniques. A systematic appraisal for the existing and emerging techniques of imaging in these settings and their clinical application including various response assessment guidelines and artificial intelligence based response assessment will also be discussed.

Metabolic Imaging for Radiation Therapy Treatment Planning: The Role of Hybrid PET/MR Imaging

The use of hybrid PET/MR imaging for radiotherapy treatment planning has the potential to reduce tumor and organ displacements caused by different scan times and setup changes. Although with mixed results mainly due to single-center studies with small sample size, PET/MR imaging could provide better target delineation, especially by reducing coregistration discrepancies on computed tomography simulation scan and offering better soft tissue contrast. The main limitation to drive stronger conclusions is due to the relatively low availability of hybrid PET/MR imaging systems, mainly limited to large academic centers.

FDA-approved machine learning algorithms in neuroradiology: A systematic review of the current evidence for approval

Over the past decade, machine learning (ML) and artificial intelligence (AI) have become increasingly prevalent in the medical field. In the United States, the Food and Drug Administration (FDA) is responsible for regulating AI algorithms as "medical devices" to ensure patient safety. However, recent work has shown that the FDA approval process may be deficient. In this study, we evaluate the evidence supporting FDA-approved neuroalgorithms, the subset of machine learning algorithms with applications in the central nervous system (CNS), through a systematic review of the primary literature. Articles covering the 53 FDA-approved algorithms with applications in the CNS published in PubMed, EMBASE, Google Scholar and Scopus between database inception and January 25, 2022 were queried. Initial searches identified 1505 studies, of which 92 articles met the criteria for extraction and inclusion. Studies were identified for 26 of the 53 neuroalgorithms, of which 10 algorithms had only a single peer-reviewed publication. Performance metrics were available for 15 algorithms, external validation studies were available for 24 algorithms, and studies exploring the use of algorithms in clinical practice were available for 7 algorithms. Papers studying the clinical utility of these algorithms focused on three domains: workflow efficiency, cost savings, and clinical outcomes. Our analysis suggests that there is a meaningful gap between the FDA approval of machine learning algorithms and their clinical utilization. There appears to be room for process improvement by implementation of the following recommendations: the provision of compelling evidence that algorithms perform as intended, mandating minimum sample sizes, reporting of a predefined set of performance metrics for all algorithms and clinical application of algorithms prior to widespread use. This work will serve as a baseline for future research into the ideal regulatory framework for AI applications worldwide.

Head-To-Head Comparison of PET and Perfusion Weighted MRI Techniques to Distinguish Treatment Related Abnormalities from Tumor Progression in Glioma

The post-treatment imaging surveillance of gliomas is challenged by distinguishing tumor progression (TP) from treatment-related abnormalities (TRA). Sophisticated imaging techniques, such as perfusion-weighted magnetic resonance imaging (MRI PWI) and positron-emission tomography (PET) with a variety of radiotracers, have been suggested as being more reliable than standard imaging for distinguishing TP from TRA. However, it remains unclear if any technique holds diagnostic superiority. This meta-analysis provides a head-to-head comparison of the diagnostic accuracy of the aforementioned imaging techniques. Systematic literature searches on the use of PWI and PET imaging techniques were carried out in PubMed, Embase, the Cochrane Library, ClinicalTrials.gov and the reference lists of relevant papers. After the extraction of data on imaging technique specifications and diagnostic accuracy, a meta-analysis was carried out. The quality of the included papers was assessed using the QUADAS-2 checklist. Nineteen articles, totaling 697 treated patients with glioma (431 males; mean age ± standard deviation 50.5 ± 5.1 years) were included. The investigated PWI techniques included dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE) and arterial spin labeling (ASL). The PET-tracers studied concerned [S-methyl-¹¹C]methionine, 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG), O-(2-[¹⁸F]fluoroethyl)-L-tyrosine ([¹⁸F]FET) and 6-[¹⁸F]-fluoro-3,4-dihydroxy-L-phenylalanine ([¹⁸F]FDOPA). The meta-analysis of all data showed no diagnostic superior imaging technique. The included literature showed a low risk of bias. As no technique was found to be diagnostically superior, the local level of expertise is hypothesized to be the most important factor for diagnostically accurate results in post-treatment glioma patients regarding the distinction of TRA from TP.

Challenges and opportunities for advanced neuroimaging of glioblastoma

Glioblastoma is the most aggressive of glial tumours in adults. On conventional magnetic resonance (MR) imaging, these tumours are observed as irregular enhancing lesions with areas of infiltrating tumour and cortical expansion. More advanced imaging techniques including diffusion-weighted MRI, perfusion-weighted MRI, MR spectroscopy and positron emission tomography (PET) imaging have found widespread application to diagnostic challenges in the setting of first diagnosis, treatment planning and follow-up. This review aims to educate readers with regard to the strengths and weaknesses of the clinical application of these imaging techniques. For example, this review shows that the (semi)quantitative analysis of the mentioned advanced imaging tools was found useful for assessing tumour aggressiveness and tumour extent, and aids in the differentiation of tumour progression from treatment-related effects. Although these techniques may aid in the diagnostic work-up and (post-)treatment phase of glioblastoma, so far no unequivocal imaging strategy is available. Furthermore, the use and further development of artificial intelligence (AI)-based tools could greatly enhance neuroradiological practice by automating labour-intensive tasks such as tumour measurements, and by providing additional diagnostic information such as prediction of tumour genotype. Nevertheless, due to the fact that advanced imaging and AI-diagnostics is not part of response assessment criteria, there is no harmonised guidance on their use, while at the same time the lack of standardisation severely hampers the definition of uniform guidelines.

Conventional and Advanced Imaging Techniques in Post-treatment Glioma Imaging

Despite decades of advancement in the diagnosis and therapy of gliomas, the most malignant primary brain tumors, the overall survival rate is still dismal, and their post-treatment imaging appearance remains very challenging to interpret. Since the limitations of conventional magnetic resonance imaging (MRI) in the distinction between recurrence and treatment effect have been recognized, a variety of advanced MR and functional imaging techniques including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), perfusion-weighted imaging (PWI), MR spectroscopy (MRS), as well as a variety of radiotracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) have been investigated for this indication along with voxel-based and more quantitative analytical methods in recent years. Machine learning and radiomics approaches in recent years have shown promise in distinguishing between recurrence and treatment effect as well as improving prognostication in a malignancy with a very short life expectancy. This review provides a comprehensive overview of the conventional and advanced imaging techniques with the potential to differentiate recurrence from treatment effect and includes updates in the state-of-the-art in advanced imaging with a brief overview of emerging experimental techniques. A series of representative cases are provided to illustrate the synthesis of conventional and advanced imaging with the clinical context which informs the radiologic evaluation of gliomas in the post-treatment setting.

Role of Dynamic Parameters of 18F-DOPA PET/CT in Pediatric Gliomas

PURPOSE OF THE REPORT

PET with 18F-DOPA can be used to evaluate grading and aggressiveness of pediatric cerebral gliomas. However, standard uptake parameters may underperform in circumscribed lesions and in diffuse pontine gliomas. In this study, we tested whether dynamic 18F-DOPA PET could overcome these limitations.

PATIENTS AND METHODS

Patients with available dynamic 18F-DOPA PET were included retrospectively. Static parameters (tumor/striatum ratio [T/S] and tumor/cortex ratio [T/N]) and dynamic ones, calculated on the tumor time activity curve (TAC), including time-to-peak (TTP), slope steepness, the ratio between tumor and striatum TAC steepness (dynamic slope ratio [DSR]), and TAC shape (accumulation vs plateau), were evaluated as predictors of high/low grading (HG and LG) and of progression-free survival and overall survival.

RESULTS

Fifteen patients were included; T/S, T/N, TTP, TAC slope steepness, and DSR were not significantly different between HG and LG. The accumulation TAC shape was more prevalent in the LG than in the HG group (75% vs 27%). On progression-free survival univariate analysis, TAC accumulation shape predicted longer survival (P < 0.001), whereas T/N and DSR showed borderline significance; on multivariate analyses, only TAC shape was retained (P < 0.01, Harrell C index, 0.93-0.95). On overall survival univariate analysis, T/N (P < 0.05), DSR (P < 0.05), and TAC "accumulating" shape predicted survival (P < 0.001); once more, only this last parameter was retained in the multivariate models (P < 0.05, Harrell C index, 0.86-0.89).

CONCLUSIONS

Dynamic 18F-DOPA PET analysis outperforms the static parameter evaluation in grading assessment and survival prediction. Evaluation of the curve shape is a simple-to-use parameter with strong predictive power.

Role of Molecular Imaging with PET/MR Imaging in the Diagnosis and Management of Brain Tumors

Gliomas are the most common primary brain tumors. Hybrid PET/MR imaging has revolutionized brain tumor imaging, allowing for noninvasive, simultaneous assessment of morphologic, functional, metabolic, and molecular parameters within the brain. Molecular information obtained from PET imaging may aid in the detection, classification, prognostication, and therapeutic decision making for gliomas. ¹⁸F-fluorodeoxyglucose (FDG) has been widely used in the setting of brain tumor imaging, and multiple techniques may be employed to optimize this methodology. More recently, a number of non-¹⁸F-FDG-PET radiotracers have been applied toward brain tumor imaging and are used in clinical practice.

Hybrid [18F]-F-DOPA PET/MRI Interpretation Criteria and Scores for Glioma Follow-up After Radiotherapy

OBJECTIVE

¹⁸F‑fluoro-L‑3,4‑dihydroxyphenylalanine positron emission tomography (F‑DOPA PET) is used in glioma follow-up after radiotherapy to discriminate treatment-related changes (TRC) from tumor progression (TP). We compared the performances of a combined PET and MRI analysis with F‑DOPA current standard of interpretation.

METHODS

We included 76 consecutive patients showing at least one gadolinium-enhanced lesion on the T1‑w MRI sequence (T1G). Two nuclear medicine physicians blindly analyzed PET/MRI images. In addition to the conventional PET analysis, they looked for F‑DOPA uptake(s) outside T1G-enhanced areas (T1G/PET), in the white matter (WM/PET), for T1G-enhanced lesion(s) without sufficiently concordant F‑DOPA uptake (T1G+/PET), and F‑DOPA uptake(s) away from hemorrhagic changes as shown with a susceptibility weighted imaging sequence (SWI/PET). We measured lesions' F‑DOPA uptake ratio using healthy brain background (TBR) and striatum (T/S) as references, and lesions' perfusion with arterial spin labelling cerebral blood flow maps (rCBF). Scores were determined by logistic regression.

RESULTS

53 and 23 patients were diagnosed with TP and TRC, respectively. The accuracies were 74% for T/S, 76% for TBR, and 84% for rCBF, with best cut-off values of 1.3, 3.7 and 1.25, respectively. For hybrid variables, best accuracies were obtained with conventional analysis (82%), T1G+/PET (82%) and SWI/PET (81%). T1G+/PET, SWI/PET and rCBF ≥ 1.25 were selected to construct a 3-point score. It outperformed conventional analysis and rCBF with an AUC of 0.94 and an accuracy of 87%.

CONCLUSIONS

Our scoring approach combining F‑DOPA PET and MRI provided better accuracy than conventional PET analyses for distinguishing TP from TRC in our patients after radiation therapy.

PET/MR Technology: Advancement and Challenges

When this article was written, it coincided with the 11th anniversary of the installation of our PET/MR device in Munich. In fact, this was the first fully integrated device to be in clinical use. During this time, we have observed many interesting behaviors, to put it kindly. However, it is more critical that in this process, our understanding of the system also improved - including the advantages and limitations from a technical, logistical, and medical perspective. The last decade of PET/MRI research has certainly been characterized by most sites looking for a "key application." There were many ideas in this context and before and after the devices became available, some of which were based on the earlier work with integrating data from single devices. These involved validating classical PET methods with MRI (eg, perfusion or oncology diagnostics). More important, however, were the scenarios where intermodal synergies could be expected. In this review, we look back on this decade-long journey, at the challenges overcome and those still to come.

Enzymatic synthesis of fluorinated compounds

Fluorinated compounds are widely used in the fields of molecular imaging, pharmaceuticals, and materials. Fluorinated natural products in nature are rare, and the introduction of fluorine atoms into organic compound molecules can give these compounds new functions and make them have better performance. Therefore, the synthesis of fluorides has attracted more and more attention from biologists and chemists. Even so, achieving selective fluorination is still a huge challenge under mild conditions. In this review, the research progress of enzymatic synthesis of fluorinated compounds is summarized since 2015, including cytochrome P450 enzymes, aldolases, fluoroacetyl coenzyme A thioesterases, lipases, transaminases, reductive aminases, purine nucleoside phosphorylases, polyketide synthases, fluoroacetate dehalogenases, tyrosine phenol-lyases, glycosidases, fluorinases, and multienzyme system. Of all enzyme-catalyzed synthesis methods, the direct formation of the C-F bond by fluorinase is the most effective and promising method. The structure and catalytic mechanism of fluorinase are introduced to understand fluorobiochemistry. Furthermore, the distribution, applications, and future development trends of fluorinated compounds are also outlined. Hopefully, this review will help researchers to understand the significance of enzymatic methods for the synthesis of fluorinated compounds and find or create excellent fluoride synthase in future research.Key points• Fluorinated compounds are distributed in plants and microorganisms, and are used in imaging, medicine, materials science.• Enzyme catalysis is essential for the synthesis of fluorinated compounds.• The loop structure of fluorinase is the key to forming the C-F bond.

Imaging and treatment of brain tumors through molecular targeting: Recent clinical advances

Molecular imaging techniques have rapidly progressed over recent decades providing unprecedented in vivo characterization of metabolic pathways and molecular biomarkers. Many of these new techniques have been successfully applied in the field of neuro-oncological imaging to probe tumor biology. Targeting specific signaling or metabolic pathways could help to address several unmet clinical needs that hamper the management of patients with brain tumors. This review aims to provide an overview of the recent advances in brain tumor imaging using molecular targeting with positron emission tomography and magnetic resonance imaging, as well as the role in patient management and possible therapeutic implications.

Additional Value of 18F-FDOPA Amino Acid Analog Radiotracer to Irradiation Planning Process of Patients With Glioblastoma Multiforme

PURPOSE

To investigate the added value of 6-(18F]-fluoro-L-3,4-dihydroxyphenylalanine (FDOPA) PET to radiotherapy planning in glioblastoma multiforme (GBM).

METHODS

From September 2017 to December 2020, 17 patients with GBM received external beam radiotherapy up to 60 Gy with concurrent and adjuvant temozolamide. Target volume delineations followed the European guideline with a 2-cm safety margin clinical target volume (CTV) around the contrast-enhanced lesion+resection cavity on MRI gross tumor volume (GTV). All patients had FDOPA hybrid PET/MRI followed by PET/CT before radiotherapy planning. PET segmentation followed international recommendation: T/N 1.7 (BTV1.7) and T/N 2 (BTV2.0) SUV thresholds were used for biological target volume (BTV) delineation. For GTV-BTVs agreements, 95% of the Hausdorff distance (HD95%) from GTV to the BTVs were calculated, additionally, BTV portions outside of the GTV and coverage by the 95% isodose contours were also determined. In case of recurrence, the latest MR images were co-registered to planning CT to evaluate its location relative to BTVs and 95% isodose contours.

RESULTS

Average (range) GTV, BTV1.7, and BTV2.0 were 46.58 (6-182.5), 68.68 (9.6-204.1), 42.89 (3.8-147.6) cm3, respectively. HD95% from GTV were 15.5 mm (7.9-30.7 mm) and 10.5 mm (4.3-21.4 mm) for BTV1.7 and BTV2.0, respectively. Based on volumetric assessment, 58.8% (28-100%) of BTV1.7 and 45.7% of BTV2.0 (14-100%) were outside of the standard GTV, still all BTVs were encompassed by the 95% dose. All recurrences were confirmed by follow-up imaging, all occurred within PTV, with an additional outfield recurrence in a single case, which was not DOPA-positive at the beginning of treatment. Good correlation was found between the mean and median values of PET/CT and PET/MRI segmented volumes relative to corresponding brain-accumulated enhancement (r = 0.75; r = 0.72).

CONCLUSION

18FFDOPA PET resulted in substantial larger tumor volumes compared to MRI; however, its added value is unclear as vast majority of recurrences occurred within the prescribed dose level. Use of PET/CT signals proved to be feasible in the absence of direct segmentation possibilities of PET/MR in TPS. The added value of 18FFDOPA may be better exploited in the context of integrated dose escalation.

Comparison of Amino Acid PET to Advanced and Emerging MRI Techniques for Neurooncology Imaging: A Systematic Review of the Recent Studies

Introduction

Standard neuroimaging protocols for brain tumors have well-known limitations. The clinical use of additional modalities including amino acid PET (aaPET) and advanced MRI (aMRI) techniques (including DWI, PWI, and MRS) is emerging in response to the need for more accurate detection of brain tumors. In this systematic review of the past 2 years of the literature, we discuss the most recent studies that directly compare or combine aaPET and aMRI for brain tumor imaging.

Methods

A PubMed search was conducted for human studies incorporating both aaPET and aMRI and published between July 2018 and August 2020.

Results

A total of 22 studies were found in the study period. Recent studies of aaPET with DWI showed a superiority of MET, FET, FDOPA, and AMT PET for detecting tumor, predicting recurrence, diagnosing progression, and predicting survival. Combining modalities further improved performance. Comparisons of aaPET with PWI showed mixed results about spatial correlation. However, both modalities were able to detect high-grade tumors, identify tumor recurrence, differentiate recurrence from treatment effects, and predict survival. aaPET performed better on these measures than PWI, but when combined, they had the strongest results. Studies of aaPET with MRS demonstrated that both modalities have diagnostic potential but MET PET and FDOPA PET performed better than MRS. MRS suffered from some data quality issues that limited analysis in two studies, and, in one study that combined modalities, overall performance actually decreased. Four recent studies compared aaPET with emerging MRI approaches (such as CEST imaging, MR fingerprinting, and SISTINA), but the initial results remain inconclusive.

Conclusions

aaPET outperformed the aMRI imaging techniques in most recent studies. DWI and PWI added meaningful complementary data, and the combination of aaPET with aMRI yielded the best results in most studies.

Hybrid PET-MRI Imaging in Paediatric and TYA Brain Tumours: Clinical Applications and Challenges

(1) Background: Standard magnetic resonance imaging (MRI) remains the gold standard for brain tumour imaging in paediatric and teenage and young adult (TYA) patients. Combining positron emission tomography (PET) with MRI offers an opportunity to improve diagnostic accuracy. (2) Method: Our single-centre experience of ¹⁸F-fluorocholine (FCho) and ¹⁸fluoro-L-phenylalanine (FDOPA) PET–MRI in paediatric/TYA neuro-oncology patients is presented. (3) Results: Hybrid PET–MRI shows promise in the evaluation of gliomas and germ cell tumours in (i) assessing early treatment response and (ii) discriminating tumour from treatment-related changes. (4) Conclusions: Combined PET–MRI shows promise for improved diagnostic and therapeutic assessment in paediatric and TYA brain tumours.

PET Imaging of Tumor Perfusion: A Potential Cancer Biomarker?

Perfusion, as measured by imaging, is considered a standard of care biomarker for the evaluation of many tumors. Measurements of tumor perfusion may be used in a number of ways, including improving the visual detection of lesions, differentiating malignant from benign findings, assessing aggressiveness of tumors, identifying ischemia and by extension hypoxia within tumors, and assessing treatment response. While most clinical perfusion imaging is currently performed with CT or MR, a number of methods for PET imaging of tumor perfusion have been described. The inert PET radiotracer 15O-water PET represents the recognized gold standard for absolute quantification of tissue perfusion in both normal tissue and a variety of pathological conditions including cancer. Other cancer PET perfusion imaging strategies include the use of radiotracers with high first-pass uptake, analogous to those used in cardiac perfusion PET. This strategy produces more visually pleasing high-contrast images that provide relative rather than absolute perfusion quantification. Lastly, multiple timepoint imaging of PET tracers such as 18F-FDG, are not specifically optimized for perfusion, but have advantages related to availability, convenience, and reimbursement. Multiple obstacles have thus far blocked the routine use of PET imaging for tumor perfusion, including tracer production and distribution, image processing, patient body coverage, clinical validation, regulatory approval and reimbursement, and finally feasible clinical workflows. Fortunately, these obstacles are being overcome, especially within larger imaging centers, opening the door for PET imaging of tumor perfusion to become standard clinical practice. In the foreseeable future, it is possible that whole-body PET perfusion imaging with 15O-water will be able to be performed in a single imaging session concurrent with standard PET imaging techniques such as 18F-FDG-PET. This approach could establish an efficient clinical workflow. The resultant ability to measure absolute tumor blood flow in combination with glycolysis will provide important complementary information to inform prognosis and clinical decisions.

Usefulness of 18F-FDOPA PET for the management of primary brain tumors: a systematic review of the literature

Contrast-enhanced magnetic resonance imaging is currently the standard of care in the management of primary brain tumors, although certain limitations remain. Metabolic imaging has proven useful for an increasing number of indications in oncology over the past few years, most particularly 18F-FDG PET/CT. In neuro-oncology, 18F-FDG was insufficient to clearly evaluate brain tumors. Amino-acid radiotracers such as 18F-FDOPA were then evaluated in the management of brain diseases, notably tumoral diseases. Even though European guidelines on the use of amino-acid PET in gliomas have been published, it is crucial that future studies standardize acquisition and interpretation parameters. The aim of this article was to systematically review the potential effect of this metabolic imaging technique in numerous steps of the disease: primary and recurrence diagnosis, grading, local and systemic treatment assessment, and prognosis. A total of 41 articles were included and analyzed in this review. It appears that 18F-FDOPA PET holds promise as an effective additional tool in the management of gliomas. More consistent prospective studies are still needed.