[German guidelines for brain tumour imaging by PET and SPECT using labelled amino acids]

Automated Brain Tumor Detection and Segmentation for Treatment Response Assessment Using Amino Acid PET

Evaluation of metabolic tumor volume (MTV) changes using amino acid PET has become an important tool for response assessment in brain tumor patients. MTV is usually determined by manual or semiautomatic delineation, which is laborious and may be prone to intra- and interobserver variability. The goal of our study was to develop a method for automated MTV segmentation and to evaluate its performance for response assessment in patients with gliomas. Methods: In total, 699 amino acid PET scans using the tracer O-(2-[18F]fluoroethyl)-l-tyrosine (18F-FET) from 555 brain tumor patients at initial diagnosis or during follow-up were retrospectively evaluated (mainly glioma patients, 76%). 18F-FET PET MTVs were segmented semiautomatically by experienced readers. An artificial neural network (no new U-Net) was configured on 476 scans from 399 patients, and the network performance was evaluated on a test dataset including 223 scans from 156 patients. Surface and volumetric Dice similarity coefficients (DSCs) were used to evaluate segmentation quality. Finally, the network was applied to a recently published 18F-FET PET study on response assessment in glioblastoma patients treated with adjuvant temozolomide chemotherapy for a fully automated response assessment in comparison to an experienced physician. Results: In the test dataset, 92% of lesions with increased uptake (n = 189) and 85% of lesions with iso- or hypometabolic uptake (n = 33) were correctly identified (F1 score, 92%). Single lesions with a contiguous uptake had the highest DSC, followed by lesions with heterogeneous, noncontiguous uptake and multifocal lesions (surface DSC: 0.96, 0.93, and 0.81 respectively; volume DSC: 0.83, 0.77, and 0.67, respectively). Change in MTV, as detected by the automated segmentation, was a significant determinant of disease-free and overall survival, in agreement with the physician's assessment. Conclusion: Our deep learning-based 18F-FET PET segmentation allows reliable, robust, and fully automated evaluation of MTV in brain tumor patients and demonstrates clinical value for automated response assessment.

DeepDixon synthetic CT for [18F]FET PET/MRI attenuation correction of post-surgery glioma patients with metal implants

Purpose

Conventional magnetic resonance imaging (MRI) can for glioma assessment be supplemented by positron emission tomography (PET) imaging with radiolabeled amino acids such as O-(2-[¹⁸F]fluoroethyl)-L-tyrosine ([¹⁸F]FET), which provides additional information on metabolic properties. In neuro-oncology, patients often undergo brain and skull altering treatment, which is known to challenge MRI-based attenuation correction (MR-AC) methods and thereby impact the simplified semi-quantitative measures such as tumor-to-brain ratio (TBR) used in clinical routine. The aim of the present study was to examine the applicability of our deep learning method, DeepDixon, for MR-AC in [¹⁸F]FET PET/MRI scans of a post-surgery glioma cohort with metal implants.

Methods

The MR-AC maps were assessed for all 194 included post-surgery glioma patients (318 studies). The subgroup of 147 patients (222 studies, 200 MBq [¹⁸F]FET PET/MRI) with tracer uptake above 1 ml were subsequently reconstructed with DeepDixon, vendor-default atlas-based method, and a low-dose computed tomography (CT) used as reference. The biological tumor volume (BTV) was delineated on each patient by isocontouring tracer uptake above a TBR threshold of 1.6. We evaluated the MR-AC methods using the recommended clinical metrics BTV and mean and maximum TBR on a patient-by-patient basis against the reference with CT-AC.

Results

Ninety-seven percent of the studies (310/318) did not have any major artifacts using DeepDixon, which resulted in a Dice coefficient of 0.89/0.83 for tissue/bone, respectively, compared to 0.84/0.57 when using atlas. The average difference between DeepDixon and CT-AC was within 0.2% across all clinical metrics, and no statistically significant difference was found. When using DeepDixon, only 3 out of 222 studies (1%) exceeded our acceptance criteria compared to 72 of the 222 studies (32%) with the atlas method.

Conclusion

We evaluated the performance of a state-of-the-art MR-AC method on the largest post-surgical glioma patient cohort to date. We found that DeepDixon could overcome most of the issues arising from irregular anatomy and metal artifacts present in the cohort resulting in clinical metrics within acceptable limits of the reference CT-AC in almost all cases. This is a significant improvement over the vendor-provided atlas method and of particular importance in response assessment.

Combination of pre-treatment dynamic [18F]FET PET radiomics and conventional clinical parameters for the survival stratification in patients with IDH-wildtype glioblastoma

PURPOSE

The aim of this study was to build and evaluate a prediction model which incorporates clinical parameters and radiomic features extracted from static as well as dynamic [18F]FET PET for the survival stratification in patients with newly diagnosed IDH-wildtype glioblastoma.

METHODS

A total of 141 patients with newly diagnosed IDH-wildtype glioblastoma and dynamic [18F]FET PET prior to surgical intervention were included. Patients with a survival time ≤ 12 months were classified as short-term survivors. First order, shape, and texture radiomic features were extracted from pre-treatment static (tumor-to-background ratio; TBR) and dynamic (time-to-peak; TTP) images, respectively, and randomly divided into a training (n = 99) and a testing cohort (n = 42). After feature normalization, recursive feature elimination was applied for feature selection using 5-fold cross-validation on the training cohort, and a machine learning model was constructed to compare radiomic models and combined clinical-radiomic models with selected radiomic features and clinical parameters. The area under the ROC curve (AUC), accuracy, sensitivity, specificity, and positive and negative predictive values were calculated to assess the predictive performance for identifying short-term survivors in both the training and testing cohort.

RESULTS

A combined clinical-radiomic model comprising six clinical parameters and six selected dynamic radiomic features achieved highest predictability of short-term survival with an AUC of 0.74 (95% confidence interval, 0.60-0.88) in the independent testing cohort.

CONCLUSIONS

This study successfully built and evaluated prediction models using [18F]FET PET-based radiomic features and clinical parameters for the individualized assessment of short-term survival in patients with a newly diagnosed IDH-wildtype glioblastoma. The combination of both clinical parameters and dynamic [18F]FET PET-based radiomic features reached highest accuracy in identifying patients at risk. Although the achieved accuracy level remained moderate, our data shows that the integration of dynamic [18F]FET PET radiomic data into clinical prediction models may improve patient stratification beyond established prognostic markers.

Dynamic 11C-Methionine PET-CT: Prognostic Factors for Disease Progression and Survival in Patients with Suspected Glioma Recurrence

Simple Summary

Recurrence after initial treatments is an expected event in glioma patients, particularly for high-grade glioma, with a median progression-free survival of 8–11 weeks. The prognostic evaluation of disease is a crucial step in the planning of therapeutic strategies, in both the primary and recurrence stages of disease. The aim of our retrospective study was to assess the prognostic value of ¹¹C-methionine PET-CT dynamic and semiquantitative parameters in patients with suspected glioma recurrence at MR, in terms of progression-free survival and overall survival. In a population of sixty-seven consecutive patients, both static and kinetic analyses provided parameters (i.e., tumour-to-background ratio and SUVmax associated with time-to-peak, respectively) able to predict both progression-free and overall survival in the whole population and in the high-grade glioma subgroup of patients. Dynamic ¹¹C-methionine PET-CT can be a useful diagnostic tool, in patients with suspicion of glioma recurrence, able to produce significant prognostic indices.

Abstract

Purpose: The prognostic evaluation of glioma recurrence patients is important in the therapeutic management. We investigated the prognostic value of ¹¹C-methionine PET-CT (MET-PET) dynamic and semiquantitative parameters in patients with suspected glioma recurrence. Methods: Sixty-seven consecutive patients who underwent MET-PET for suspected glioma recurrence at MR were retrospectively included. Twenty-one patients underwent static MET-PET; 46/67 underwent dynamic MET-PET. In all patients, SUVmax, SUVmean and tumour-to-background ratio (T/B) were calculated. From dynamic acquisition, the shape and slope of time-activity curves, time-to-peak and its SUVmax (SUVmax_TTP) were extrapolated. The prognostic value of PET parameters on progression-free (PFS) and overall survival (OS) was evaluated using Kaplan–Meier survival estimates and Cox regression. Results: The overall median follow-up was 19 months from MET-PET. Recurrence patients (38/67) had higher SUVmax (p = 0.001), SUVmean (p = 0.002) and T/B (p < 0.001); deceased patients (16/67) showed higher SUVmax (p = 0.03), SUVmean (p = 0.03) and T/B (p = 0.006). All static parameters were associated with PFS (all p < 0.001); T/B was associated with OS (p = 0.031). Regarding kinetic analyses, recurrence (27/46) and deceased (14/46) patients had higher SUVmax_TTP (p = 0.02, p = 0.01, respectively). SUVmax_TTP was the only dynamic parameter associated with PFS (p = 0.02) and OS (p = 0.006). At univariate analysis, SUVmax, SUVmean, T/B and SUVmax_TTP were predictive for PFS (all p < 0.05); SUVmax_TTP was predictive for OS (p = 0.02). At multivariate analysis, SUVmax_TTP remained significant for PFS (p = 0.03). Conclusion: Semiquantitative parameters and SUVmax_TTP were associated with clinical outcomes in patients with suspected glioma recurrence. Dynamic PET-CT acquisition, with static and kinetic parameters, can be a valuable non-invasive prognostic marker, identifying patients with worse prognosis who require personalised therapy.

Prediction of TERTp-mutation status in IDH-wildtype high-grade gliomas using pre-treatment dynamic [18F]FET PET radiomics

Purpose

To evaluate radiomic features extracted from standard static images (20–40 min p.i.), early summation images (5–15 min p.i.), and dynamic [¹⁸F]FET PET images for the prediction of TERTp-mutation status in patients with IDH-wildtype high-grade glioma.

Methods

A total of 159 patients (median age 60.2 years, range 19–82 years) with newly diagnosed IDH-wildtype diffuse astrocytic glioma (WHO grade III or IV) and dynamic [¹⁸F]FET PET prior to surgical intervention were enrolled and divided into a training (n = 112) and a testing cohort (n = 47) randomly. First-order, shape, and texture radiomic features were extracted from standard static (20–40 min summation images; TBR_20–40), early static (5–15 min summation images; TBR_5–15), and dynamic (time-to-peak; TTP) images, respectively. Recursive feature elimination was used for feature selection by 10-fold cross-validation in the training cohort after normalization, and logistic regression models were generated using the radiomic features extracted from each image to differentiate TERTp-mutation status. The areas under the ROC curve (AUC), accuracy, sensitivity, specificity, and positive and negative predictive value were calculated to illustrate diagnostic power in both the training and testing cohort.

Results

The TTP model comprised nine selected features and achieved highest predictability of TERTp-mutation with an AUC of 0.82 (95% confidence interval 0.71–0.92) and sensitivity of 92.1% in the independent testing cohort. Weak predictive capability was obtained in the TBR_5–15 model, with an AUC of 0.61 (95% CI 0.42–0.80) in the testing cohort, while no predictive power was observed in the TBR_20–40 model.

Conclusions

Radiomics based on TTP images extracted from dynamic [¹⁸F]FET PET can predict the TERTp-mutation status of IDH-wildtype diffuse astrocytic high-grade gliomas with high accuracy preoperatively.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05526-6.

Evaluation of FET PET Radiomics Feature Repeatability in Glioma Patients

Simple Summary

Initial studies suggested the additional diagnostic value of amino acid positron emission tomography (PET) radiomics using the tracer O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET) in brain tumor patient management. However, to ensure the reliable performance of the generated FET PET radiomics models for clinical diagnostics, repeatability of radiomics features is essential. Hence, we assessed the impact of brain tumor volumes and key molecular alterations such as an isocitrate dehydrogenase (IDH) mutation on the repeatability of FET PET radiomics features in 50 newly diagnosed glioma patients. In a test–retest approach based on routinely acquired FET PET scans, we identified 297 repeatable features. The IDH genotype did not affect feature repeatability. Moreover, these robust features were able to differentiate patients with IDH-wildtype glioma from those with an IDH mutation. Our results suggest that robust radiomics features can be obtained from routinely acquired FET PET scans, which are valuable for further standardization of radiomics analyses in neurooncology.

Abstract

Amino acid PET using the tracer O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET) has attracted considerable interest in neurooncology. Furthermore, initial studies suggested the additional diagnostic value of FET PET radiomics in brain tumor patient management. However, the conclusiveness of radiomics models strongly depends on feature generalizability. We here evaluated the repeatability of feature-based FET PET radiomics. A test–retest analysis based on equivalent but statistically independent subsamples of FET PET images was performed in 50 newly diagnosed and histomolecularly characterized glioma patients. A total of 1,302 radiomics features were calculated from semi-automatically segmented tumor volumes-of-interest (VOIs). Furthermore, to investigate the influence of the spatial resolution of PET on repeatability, spherical VOIs of different sizes were positioned in the tumor and healthy brain tissue. Feature repeatability was assessed by calculating the intraclass correlation coefficient (ICC). To further investigate the influence of the isocitrate dehydrogenase (IDH) genotype on feature repeatability, a hierarchical cluster analysis was performed. For tumor VOIs, 73% of first-order features and 71% of features extracted from the gray level co-occurrence matrix showed high repeatability (ICC 95% confidence interval, 0.91–1.00). In the largest spherical tumor VOIs, 67% of features showed high repeatability, significantly decreasing towards smaller VOIs. The IDH genotype did not affect feature repeatability. Based on 297 repeatable features, two clusters were identified separating patients with IDH-wildtype glioma from those with an IDH mutation. Our results suggest that robust features can be obtained from routinely acquired FET PET scans, which are valuable for further standardization of radiomics analyses in neurooncology.

Comparison of [18F]Fluoroethyltyrosine PET and Sodium MRI in Cerebral Gliomas: a Pilot Study

PURPOSE

Positron emission tomography (PET) using O-(2-[¹⁸F]fluoroethyl)-L-tyrosine ([¹⁸F]FET) improves the diagnostics of cerebral gliomas compared with conventional magnetic resonance imaging (MRI). Sodium MRI is an evolving method to assess tumor metabolism. In this pilot study, we explored the relationship of [¹⁸F]FET-PET and sodium MRI in patients with cerebral gliomas in relation to the mutational status of the enzyme isocitrate dehydrogenase (IDH).

PROCEDURES

Ten patients with untreated cerebral gliomas and one patient with a recurrent glioblastoma (GBM) were investigated by dynamic [¹⁸F]FET-PET and sodium MRI using an enhanced simultaneous single-quantum- and triple-quantum-filtered imaging of ²³Na (SISTINA) sequence to estimate total (NaT), weighted non-restricted (NaNR, mainly extracellular), and restricted (NaR, mainly intracellular) sodium in tumors and normal brain tissue. [¹⁸F]FET uptake and sodium parameters in tumors with a different IDH mutational status were compared. After biopsy or resection, histology and the IDH mutational status were determined neuropathologically.

RESULTS

NaT (p = 0.05), tumor-to-brain ratios (TBR) of NaT (p = 0.02), NaNR (p = 0.003), and the ratio of NaT/NaR (p < 0.001) were significantly higher in IDH-mutated than in IDH-wild-type gliomas (n = 5 patients each) while NaR was significantly lower in IDH-mutated gliomas (p = 0.01). [¹⁸F]FET parameters (TBR, time-to-peak) were not predictive of IDH status in this small cohort of patients. There was no obvious relationship between sodium distribution and [¹⁸F]FET uptake. The patient with a recurrent GBM exhibited an additional radiation injury with strong abnormalities in sodium MRI.

CONCLUSIONS

Sodium MRI appears to be more strongly related to the IDH mutational status than are [¹⁸F]FET-PET parameters. A further evaluation of the combination of the two methods in a larger group of high- and low-grade gliomas seems promising.

FET PET Radiomics for Differentiating Pseudoprogression from Early Tumor Progression in Glioma Patients Post-Chemoradiation

Simple Summary

Following chemoradiation with alkylating agents in glioma patients, structural magnetic resonance imaging (MRI) may suggest tumor progression which subsequently improves during the course of the disease without any treatment change. This phenomenon has been termed pseudoprogression. Despite advances in medical imaging, a reliable diagnosis of pseudoprogression remains a challenging task. Radiomics is a subdiscipline of artificial intelligence and allows the identification and extraction of imaging features from various routine imaging modalities. These features can be used for the generation of mathematical models to improve diagnostics in patients with brain tumors. The present study highlights the potential of radiomics obtained from amino acid positron emission tomography (PET) for the diagnosis of pseudoprogression. In 34 patients with suspicious MRI early after chemoradiation completion, our radiomics model correctly identified all patients with pseudoprogression.

Abstract

Currently, a reliable diagnostic test for differentiating pseudoprogression from early tumor progression is lacking. We explored the potential of O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET) positron emission tomography (PET) radiomics for this clinically important task. Thirty-four patients (isocitrate dehydrogenase (IDH)-wildtype glioblastoma, 94%) with progressive magnetic resonance imaging (MRI) changes according to the Response Assessment in Neuro-Oncology (RANO) criteria within the first 12 weeks after completing temozolomide chemoradiation underwent a dynamic FET PET scan. Static and dynamic FET PET parameters were calculated. For radiomics analysis, the number of datasets was increased to 102 using data augmentation. After randomly assigning patients to a training and test dataset, 944 features were calculated on unfiltered and filtered images. The number of features for model generation was limited to four to avoid data overfitting. Eighteen patients were diagnosed with early tumor progression, and 16 patients had pseudoprogression. The FET PET radiomics model correctly diagnosed pseudoprogression in all test cohort patients (sensitivity, 100%; negative predictive value, 100%). In contrast, the diagnostic performance of the best FET PET parameter (TBR_max) was lower (sensitivity, 81%; negative predictive value, 80%). The results suggest that FET PET radiomics helps diagnose patients with pseudoprogression with a high diagnostic performance. Given the clinical significance, further studies are warranted.

Non-Invasive Prediction of IDH Mutation in Patients with Glioma WHO II/III/IV Based on F-18-FET PET-Guided In Vivo 1H-Magnetic Resonance Spectroscopy and Machine Learning

Simple Summary

Approximately 75–80% of according to the classification of world health organization (WHO) grade II and III gliomas are characterized by a mutation of the isocitrate dehydrogenase (IDH) enzymes, which are very important in glioma cell metabolism. Patients with IDH mutated glioma have a significantly better prognosis than patients with IDH wildtype status, typically seen in glioblastoma WHO grade IV. Here we used a prospective O-(2-¹⁸F-fluoroethyl)-L-tyrosine (¹⁸F-FET) positron emission tomography guided single-voxel ¹H-magnetic resonance spectroscopy approach to predict the IDH status before surgery. Finally, 34 patients were included in this neuroimaging study, of whom eight had additionally tissue analysis. Using a machine learning technique, we predicted IDH status with an accuracy of 88.2%, a sensitivity of 95.5% and a specificity of 75.0%. It was newly recognized, that two metabolites (myo-inositol and glycine) have a particularly important role in the determination of the IDH status.

Abstract

Isocitrate dehydrogenase (IDH)-1 mutation is an important prognostic factor and a potential therapeutic target in glioma. Immunohistological and molecular diagnosis of IDH mutation status is invasive. To avoid tumor biopsy, dedicated spectroscopic techniques have been proposed to detect D-2-hydroxyglutarate (2-HG), the main metabolite of IDH, directly in vivo. However, these methods are technically challenging and not broadly available. Therefore, we explored the use of machine learning for the non-invasive, inexpensive and fast diagnosis of IDH status in standard ¹H-magnetic resonance spectroscopy (¹H-MRS). To this end, 30 of 34 consecutive patients with known or suspected glioma WHO grade II-IV were subjected to metabolic positron emission tomography (PET) imaging with O-(2-¹⁸F-fluoroethyl)-L-tyrosine (¹⁸F-FET) for optimized voxel placement in ¹H-MRS. Routine ¹H-magnetic resonance (¹H-MR) spectra of tumor and contralateral healthy brain regions were acquired on a 3 Tesla magnetic resonance (3T-MR) scanner, prior to surgical tumor resection and molecular analysis of IDH status. Since 2-HG spectral signals were too overlapped for reliable discrimination of IDH mutated (IDHmut) and IDH wild-type (IDHwt) glioma, we used a nested cross-validation approach, whereby we trained a linear support vector machine (SVM) on the complete spectral information of the ¹H-MRS data to predict IDH status. Using this approach, we predicted IDH status with an accuracy of 88.2%, a sensitivity of 95.5% (95% CI, 77.2–99.9%) and a specificity of 75.0% (95% CI, 42.9–94.5%), respectively. The area under the curve (AUC) amounted to 0.83. Subsequent ex vivo ¹H-nuclear magnetic resonance (¹H-NMR) measurements performed on metabolite extracts of resected tumor material (eight specimens) revealed myo-inositol (M-ins) and glycine (Gly) to be the major discriminators of IDH status. We conclude that our approach allows a reliable, non-invasive, fast and cost-effective prediction of IDH status in a standard clinical setting.

Treatment Monitoring of Immunotherapy and Targeted Therapy Using 18F-FET PET in Patients with Melanoma and Lung Cancer Brain Metastases: Initial Experiences

We investigated the value of O-(2-¹⁸F-fluoroethyl)-l-tyrosine (¹⁸F-FET) PET for treatment monitoring of immune checkpoint inhibition (ICI) or targeted therapy (TT) alone or in combination with radiotherapy in patients with brain metastasis (BM) since contrast-enhanced MRI often remains inconclusive. Methods: We retrospectively identified 40 patients with 107 BMs secondary to melanoma (n = 29 with 75 BMs) or non-small cell lung cancer (n = 11 with 32 BMs) treated with ICI or TT who had ¹⁸F-FET PET (n = 60 scans) for treatment monitoring from 2015 to 2019. Most patients (n = 37; 92.5%) had radiotherapy during the course of the disease. In 27 patients, ¹⁸F-FET PET was used to differentiate treatment-related changes from BM relapse after ICI or TT. In 13 patients, ¹⁸F-FET PET was performed for response assessment to ICI or TT using baseline and follow-up scans (median time between scans, 4.2 mo). In all lesions, static and dynamic ¹⁸F-FET PET parameters were obtained (i.e., mean tumor-to-brain ratios [TBR], time-to-peak values). Diagnostic accuracies of PET parameters were evaluated by receiver-operating-characteristic analyses using the clinical follow-up or neuropathologic findings as a reference. Results: A TBR threshold of 1.95 differentiated BM relapse from treatment-related changes with an accuracy of 85% (P = 0.003). Metabolic responders to ICI or TT on ¹⁸F-FET PET had a significantly longer stable follow-up (threshold of TBR reduction relative to baseline, ≥10%; accuracy, 82%; P = 0.004). Furthermore, at follow-up, time to peak in metabolic responders increased significantly (P = 0.019). Conclusion: ¹⁸F-FET PET may add valuable information for treatment monitoring in BM patients treated with ICI or TT.

Interventions to reduce the time to diagnosis of brain tumours

BACKGROUND

Brain tumours are recognised as one of the most difficult cancers to diagnose because presenting symptoms, such as headache, cognitive symptoms, and seizures, may be more commonly attributable to other, more benign conditions. Interventions to reduce the time to diagnosis of brain tumours include national awareness initiatives, expedited pathways, and protocols to diagnose brain tumours, based on a person's presenting symptoms and signs; and interventions to reduce waiting times for brain imaging pathways. If such interventions reduce the time to diagnosis, it may make it less likely that people experience clinical deterioration, and different treatment options may be available.

OBJECTIVES

To systematically evaluate evidence on the effectiveness of interventions that may influence: symptomatic participants to present early (shortening the patient interval), thresholds for primary care referral (shortening the primary care interval), and time to imaging diagnosis (shortening the secondary care interval and diagnostic interval). To produce a brief economic commentary, summarising the economic evaluations relevant to these interventions.

SEARCH METHODS

For evidence on effectiveness, we searched CENTRAL, MEDLINE, and Embase from January 2000 to January 2020; Clinicaltrials.gov to May 2020, and conference proceedings from 2014 to 2018. For economic evidence, we searched the UK National Health Services Economic Evaluation Database from 2000 to December 2014.

SELECTION CRITERIA

We planned to include studies evaluating any active intervention that may influence the diagnostic pathway, e.g. clinical guidelines, direct access imaging, public health campaigns, educational initiatives, and other interventions that might lead to early identification of primary brain tumours. We planned to include randomised and non-randomised comparative studies. Included studies would include people of any age, with a presentation that might suggest a brain tumour.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed titles identified by the search strategy, and the full texts of potentially eligible studies. We resolved discrepancies through discussion or, if required, by consulting another review author.

MAIN RESULTS

We did not identify any studies for inclusion in this review. We excluded 115 studies. The main reason for exclusion of potentially eligible intervention studies was their study design, due to a lack of control groups. We found no economic evidence to inform a brief economic commentary on this topic.

AUTHORS' CONCLUSIONS

In this version of the review, we did not identify any studies that met the review inclusion criteria for either effectiveness or cost-effectiveness. Therefore, there is no evidence from good quality studies on the best strategies to reduce the time to diagnosis of brain tumours, despite the prioritisation of research on early diagnosis by the James Lind Alliance in 2015. This review highlights the need for research in this area.

Photopenic defects on O-(2-[18F]-fluoroethyl)-L-tyrosine PET: clinical relevance in glioma patients

BACKGROUND

O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) PET has a sensitivity of more than 90% to detect gliomas. In the remaining small fraction of gliomas without increased tracer uptake, some tumors even show photopenic defects whose clinical significance is unclear.

METHODS

Glioma patients with a negative FET PET scan prior to neuropathological confirmation were identified retrospectively. Gliomas were rated visually as (i) having indifferent FET uptake or (ii) photopenic, if FET uptake was below background activity. FET uptake in the area of signal hyperintensity on the T2/fluid attenuated inversion recovery-weighted MRI was evaluated by mean standardized uptake value (SUV) and mean tumor-to-brain ratio (TBR). The progression-free survival (PFS) of photopenic gliomas was compared with that of gliomas with indifferent FET uptake.

RESULTS

Of 100 FET-negative gliomas, 40 cases with photopenic defects were identified. Fifteen of these 40 cases (38%) had World Health Organization (WHO) grades III and IV gliomas. FET uptake in photopenic gliomas was significantly decreased compared with both the healthy-appearing brain tissue (SUV, 0.89 ± 0.26 vs 1.08 ± 0.23; P < 0.001) and gliomas with indifferent FET uptake (TBR, 0.82 ± 0.09 vs 0.96 ± 0.13; P < 0.001). Irrespective of the applied treatment, isocitrate dehydrogenase (IDH)-mutated WHO grade II diffuse astrocytoma patients with indifferent FET uptake (n = 25) had a significantly longer PFS than patients with IDH-mutated diffuse astrocytomas (WHO grade II) with photopenic defects (n = 11) (51 vs 24 mo; P = 0.027). The multivariate survival analysis indicated that photopenic defects predict an unfavorable PFS (P = 0.009).

CONCLUSION

Photopenic gliomas in negative FET PET scans should be managed more actively, as they seem to have a higher risk of harboring a higher-grade glioma and an unfavorable outcome.

Prognostic Value of O-(2-[18F]Fluoroethyl)-L-Tyrosine PET/CT in Newly Diagnosed WHO 2016 Grade II and III Glioma

PURPOSE

The use of [¹⁸F]fluoroethyl)-L-tyrosine ([¹⁸F]FET) positron emission tomography/computed tomography (PET/CT) has proven valuable in brain tumor management. This study aimed to investigate the prognostic value of radiotracer uptake in newly diagnosed grade II or III gliomas according to the current 2016 World Health Organization (WHO) classification.

PROCEDURES

A total of 35 treatment-naive patients (mean age, 48 ± 17 years) with histologically proven WHO grade II or III gliomas as defined by the current 2016 WHO classification were included. Static PET/CT imaging was performed 20 min after intravenous [¹⁸F]FET injection. Images were assessed visually and semi-quantitatively using regions of interest for both tumor (SUVmax, SUVmean) and background (BKGmean) to calculate tumor-to-background (TBR) ratios. The association among histological results, molecular markers (including isocitrate dehydrogenase enzyme and methylguanine-DNA methyltransferase status), clinical features (age), and PET findings was tested and compared with outcome (progression-free [PFS] and overall survival [OS]).

RESULTS

Fourteen patients presented with grade II (diffuse astrocytoma n = 10, oligodendroglioma n = 4) and 21 patients with grade III glioma (anaplastic astrocytoma n = 15, anaplastic oligodendroglioma n = 6). Twenty-seven out of the 35 patients were PET-positive (grade II n = 8/14, grade III n = 19/21), with grade III tumors exhibiting significantly higher amino acid uptake (TBR_mean and TBR_max; p = 0.03 and p = 0.02, respectively). PET-negative lesions demonstrated significantly prolonged PFS (p = 0.003) as compared to PET-positive gliomas. PET-positive disease had a complementary value in prognostication in addition to patient age, glioma grade, and molecular markers.

CONCLUSIONS

Amino acid uptake as assessed by [¹⁸F]FET-PET/CT imaging is useful as non-invasive read-out for tumor biology and prognosis in newly diagnosed, treatment-naive gliomas according to the 2016 WHO classification.

Prediction of survival in patients with IDH-wildtype astrocytic gliomas using dynamic O-(2-[18F]-fluoroethyl)-L-tyrosine PET

PURPOSE

Integrated histomolecular diagnostics of gliomas according to the World Health Organization (WHO) classification of 2016 has refined diagnostic accuracy and prediction of prognosis. This study aimed at exploring the prognostic value of dynamic O-(2-[¹⁸F]-fluoroethyl)-L-tyrosine (FET) PET in newly diagnosed, histomolecularly classified astrocytic gliomas of WHO grades III or IV.

METHODS

Before initiation of treatment, dynamic FET PET imaging was performed in patients with newly diagnosed glioblastoma (GBM) and anaplastic astrocytoma (AA). Static FET PET parameters such as maximum and mean tumour/brain ratios (TBR_max/mean), the metabolic tumour volume (MTV) as well as the dynamic FET PET parameters time-to-peak (TTP) and slope, were obtained. The predictive ability of FET PET parameters was evaluated concerning the progression-free and overall survival (PFS, OS). Using ROC analyses, threshold values for FET PET parameters were obtained. Subsequently, univariate Kaplan-Meier and multivariate Cox regression survival analyses were performed to assess the predictive power of these parameters for survival.

RESULTS

Sixty patients (45 GBM and 15 AA patients) of two university centres were retrospectively identified. Patients with isocitrate dehydrogenase (IDH)-mutant or O⁶-methylguanine-DNA-methyltransferase (MGMT) promoter-methylated tumours had a significantly longer PFS and OS (both P < 0.001). Furthermore, ROC analysis of IDH-wildtype glioma patients (n = 45) revealed that a TTP > 25 min (AUC, 0.90; sensitivity, 90%; specificity, 87%; P < 0.001) was highly prognostic for longer PFS (13 vs. 7 months; P = 0.005) and OS (29 vs. 12 months; P < 0.001). In contrast, at a lower level of significance, TBR_max, TBR_mean, and MTV were only prognostic for longer OS (P = 0.004, P = 0.038, and P = 0.048, respectively). Besides complete resection and a methylated MGMT promoter, TTP remained significant in multivariate survival analysis (all P ≤ 0.02), indicating an independent predictor for OS.

CONCLUSIONS

Our data suggest that dynamic FET PET allows the identification of patients with longer OS among patients with newly diagnosed IDH-wildtype GBM and AA.

Quantitative biparametric analysis of hybrid 18F-FET PET/MR-neuroimaging for differentiation between treatment response and recurrent glioma

We investigated the diagnostic potential of simultaneous ¹⁸F-FET PET/MR-imaging for differentiation between recurrent glioma and post-treatment related effects (PTRE) using quantitative volumetric (3D-VOI) lesion analysis. In this retrospective study, a total of 42 patients including 32 patients with histologically proven glioma relapse and 10 patients with PTRE (histopathologic follow-up, n = 4, serial imaging follow-up, n = 6) were evaluated regarding recurrence. PET/MR-imaging was semi-automatically analysed based on FET tracer uptake using conservative SUV thresholding (isocontour 80%) with emphasis on the metabolically most active regions. Mean (relative) apparent diffusion coefficient (ADCmean, rADCmean), standardised-uptake-value (SUV) including target-to-background (TBR) ratio were determined. Glioma relapse presented higher ADCmean (MD ± SE, 284 ± 91, p = 0.003) and TBRmax (MD ± SE, 1.10 ± 0.45, p = 0.02) values than treatment-related changes. Both ADCmean (AUC ± SE = 0.82 ± 0.07, p-value < 0.001) and TBRmax (AUC ± SE = 0.81 ± 0.08, p-value < 0.001) achieved reliable diagnostic performance in differentiating glioma recurrence from PTRE. Bivariate analysis based on a combination of ADCmean and TBRmax demonstrated highest diagnostic accuracy (AUC ± SE = 0.90 ± 0.05, p-value < 0.001), improving clinical (false negative and false positive) classification. In conclusion, biparametric analysis using DWI and FET PET, both providing distinct information regarding the underlying pathophysiology, presented best diagnostic accuracy and clinical benefit in differentiating recurrent glioma from treatment-related changes.

Influence of Dexamethasone on O-(2-[18F]-Fluoroethyl)-L-Tyrosine Uptake in the Human Brain and Quantification of Tumor Uptake

PURPOSE

O-(2-[¹⁸F]fluoroethyl)-L-tyrosine ([¹⁸F]FET) is an established positron emission tomography (PET) tracer for brain tumor imaging. This study explores the influence of dexamethasone therapy on [¹⁸F]FET uptake in the normal brain and its influence on the maximum and mean tumor-to-brain ratio (TBR).

PROCEDURES

[¹⁸F]FET PET scans of 160 brain tumor patients were evaluated (80 dexamethasone treated, 80 untreated; each group with 40 men/40 women). The standardized uptake value of [¹⁸F]FET uptake in the normal brain (SUV_brain) in the different groups was compared. Nine patients were examined repeatedly with and without dexamethasone therapy.

RESULTS

SUV_brain of [¹⁸F]FET uptake was significantly higher in dexamethasone-treated patients than in untreated patients (SUV_brain 1.33 ± 0.1 versus 1.06 ± 0.16 in male and 1.45 ± 0.25 versus 1.31 ± 0.28 in female patients). Similar results were observed in patients with serial PET scans. Furthermore, compared to men, a significantly higher SUV_brain was found in women, both with and without dexamethasone treatment. There were no significant differences between the different groups for TBR_max and TBR_mean, which could have been masked by the high standard deviation. In a patient with a stable brain metastasis investigated twice with and without dexamethasone, the TBR_max and the biological tumor volume (BTV) decreased considerably after dexamethasone due to an increased SUV_brain.

CONCLUSION

Dexamethasone treatment appears to increase the [¹⁸F]FET uptake in the normal brain. An effect on TBR_max, TBR_mean, and BTV cannot be excluded which should be considered especially for treatment monitoring and the estimation of BTV using [¹⁸F]FET PET.

Investigation of cis-4-[18F]Fluoro-D-Proline Uptake in Human Brain Tumors After Multimodal Treatment

PURPOSE

Cis-4-[¹⁸F]fluoro-D-proline (D-cis-[¹⁸F]FPro) has been shown to pass the intact blood-brain barrier and to accumulate in areas of secondary neurodegeneration and necrosis in the rat brain while uptake in experimental brain tumors is low. This pilot study explores the uptake behavior of D-cis-[¹⁸F]FPro in human brain tumors after multimodal treatment.

PROCEDURES

In a prospective study, 27 patients with suspected recurrent brain tumor after treatment with surgery, radiotherapy, and/or chemotherapy (SRC) were investigated by dynamic positron emission tomography (PET) using D-cis-[¹⁸F]FPro (22 high-grade gliomas, one unspecified glioma, and 4 metastases). Furthermore, two patients with untreated lesions were included (one glioblastoma, one reactive astrogliosis). Data were compared with the results of PET using O-(2-[¹⁸F]fluoroethyl)-L-tyrosine ([¹⁸F]FET) which detects viable tumor tissue. Tracer distribution, mean and maximum lesion-to-brain ratios (LBR_mean, LBR_max), and time-to-peak (TTP) of the time activity curve (TAC) of tracer uptake were evaluated. Final diagnosis was determined by histology (n = 9), clinical follow-up (n = 10), or by [¹⁸F]FET PET (n = 10).

RESULTS

D-cis-[¹⁸F]FPro showed high uptake in both recurrent brain tumors (n = 11) and lesions classified as treatment-related changes (TRC) only (n = 16) (LBR_mean 2.2 ± 0.7 and 2.1 ± 0.6, n.s.; LBR_max 3.4 ± 1.2 and 3.2 ± 1.3, n.s.). The untreated glioblastoma and the lesion showing reactive astrogliosis exhibited low D-cis-[¹⁸F]FPro uptake. Distribution of [¹⁸F]FET and D-cis-[¹⁸F]FPro uptake was discordant in 21/29 cases indicating that the uptake mechanisms are different.

CONCLUSION

The high accumulation of D-cis-[¹⁸F]FPro in pretreated brain tumors and TRC supports the hypothesis that tracer uptake is related to cell death. Further studies before and after therapy are needed to assess the potential of D-cis-[¹⁸F]FPro for treatment monitoring.

Combining multimodal imaging and treatment features improves machine learning-based prognostic assessment in patients with glioblastoma multiforme

Background

For Glioblastoma (GBM), various prognostic nomograms have been proposed. This study aims to evaluate machine learning models to predict patients' overall survival (OS) and progression‐free survival (PFS) on the basis of clinical, pathological, semantic MRI‐based, and FET‐PET/CT‐derived information. Finally, the value of adding treatment features was evaluated.

Methods

One hundred and eighty‐nine patients were retrospectively analyzed. We assessed clinical, pathological, and treatment information. The VASARI set of semantic imaging features was determined on MRIs. Metabolic information was retained from preoperative FET‐PET/CT images. We generated multiple random survival forest prediction models on a patient training set and performed internal validation. Single feature class models were created including "clinical," "pathological," "MRI‐based," and "FET‐PET/CT‐based" models, as well as combinations. Treatment features were combined with all other features.

Results

Of all single feature class models, the MRI‐based model had the highest prediction performance on the validation set for OS (C‐index: 0.61 [95% confidence interval: 0.51‐0.72]) and PFS (C‐index: 0.61 [0.50‐0.72]). The combination of all features did increase performance above all single feature class models up to C‐indices of 0.70 (0.59‐0.84) and 0.68 (0.57‐0.78) for OS and PFS, respectively. Adding treatment information further increased prognostic performance up to C‐indices of 0.73 (0.62‐0.84) and 0.71 (0.60‐0.81) on the validation set for OS and PFS, respectively, allowing significant stratification of patient groups for OS.

Conclusions

MRI‐based features were the most relevant feature class for prognostic assessment. Combining clinical, pathological, and imaging information increased predictive power for OS and PFS. A further increase was achieved by adding treatment features.

Joint EANM/EANO/RANO practice guidelines/SNMMI procedure standards for imaging of gliomas using PET with radiolabelled amino acids and [18F]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.

FET PET reveals considerable spatial differences in tumour burden compared to conventional MRI in newly diagnosed glioblastoma

PURPOSE

Areas of contrast enhancement (CE) on MRI are usually the target for resection or radiotherapy target volume definition in glioblastomas. However, the solid tumour mass may extend beyond areas of CE. Amino acid PET can detect parts of the tumour that show no CE. We systematically investigated tumour volumes delineated by amino acid PET and MRI in patients with newly diagnosed, untreated glioblastoma.

METHODS

Preoperatively, 50 patients with neuropathologically confirmed glioblastoma underwent O-(2-[¹⁸F]-fluoroethyl)-L-tyrosine (FET) PET, and fluid-attenuated inversion recovery (FLAIR) and contrast-enhanced MRI. Areas of CE were manually segmented. FET PET tumour volumes were segmented using a tumour-to-brain ratio of ≥1.6. The percentage overlap volumes, and Dice and Jaccard spatial similarity coefficients (DSC, JSC) were calculated. FLAIR images were evaluated visually.

RESULTS

In 43 patients (86%), the FET tumour volume was significantly larger than the CE volume (21.5 ± 14.3 mL vs. 9.4 ± 11.3 mL; P < 0.001). Forty patients (80%) showed both increased uptake of FET and CE. In these 40 patients, the spatial similarity between FET uptake and CE was low (mean DSC 0.39 ± 0.21, mean JSC 0.26 ± 0.16). Ten patients (20%) showed no CE, and one of these patients showed no FET uptake. In five patients (10%), increased FET uptake was present outside areas of FLAIR hyperintensity.

CONCLUSION

Our results show that the metabolically active tumour volume delineated by FET PET is significantly larger than tumour volume delineated by CE. Furthermore, the results strongly suggest that the information derived from both imaging modalities should be integrated into the management of patients with newly diagnosed glioblastoma.

Voxel-wise analysis of dynamic 18F-FET PET: a novel approach for non-invasive glioma characterisation

BACKGROUND

Glioma grading with dynamic ¹⁸F-FET PET (0-40 min p.i.) is typically performed by analysing the mean time-activity curve of the entire tumour or a suspicious area within a heterogeneous tumour. This work aimed to ensure a reader-independent glioma characterisation and identification of aggressive sub-volumes by performing a voxel-based analysis with diagnostically relevant kinetic and static ¹⁸F-FET PET parameters. One hundred sixty-two patients with a newly diagnosed glioma classified according to histologic and molecular genetic properties were evaluated. The biological tumour volume (BTV) was segmented in static 20-40 min p.i. ¹⁸F-FET PET images using the established threshold of 1.6 × background activity. For each enclosed voxel, the time-to-peak (TTP), the late slope (Slope_15-40), and the tumour-to-background ratios (TBR_5-15, TBR_20-40) obtained from 5 to 15 min p.i. and 20 to 40 min p.i. images were determined. The percentage portion of these values within the BTV was evaluated with percentage volume fractions (PVFs) and cumulated percentage volume histograms (PVHs). The ability to differentiate histologic and molecular genetic classes was assessed and compared to volume-of-interest (VOI)-based parameters.

RESULTS

Aggressive WHO grades III and IV and IDH-wildtype gliomas were dominated by a high proportion of voxels with an early peak, negative slope, and high TBR, whereby the PVHs with TTP < 20 min p.i., Slope_15-40 < 0 SUV/h, and TBR_5-15 and TBR_20-40 > 2 yielded the most significant differences between glioma grades. We found significant differences of the parameters between WHO grades and IDH mutation status, where the effect size was predominantly higher for voxel-based PVHs compared to the corresponding VOI-based parameters. A low overlap of BTV sub-volumes defined by TTP < 20 min p.i. and negative Slope_15-40 with TBR_5-15 > 2- and TBR_{20-40 > 2}-defined hotspots was observed.

CONCLUSIONS

The presented approach applying voxel-wise analysis of dynamic ¹⁸F-FET PET enables an enhanced characterisation of gliomas and might potentially provide a fast identification of aggressive sub-volumes within the BTV. Parametric 3D ¹⁸F-FET PET information as investigated in this study has the potential to guide individual therapy instrumentation and may be included in future biopsy studies.

Predicting IDH genotype in gliomas using FET PET radiomics

Mutations in the isocitrate dehydrogenase (IDH mut) gene have gained paramount importance for the prognosis of glioma patients. To date, reliable techniques for a preoperative evaluation of IDH genotype remain scarce. Therefore, we investigated the potential of O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET radiomics using textural features combined with static and dynamic parameters of FET uptake for noninvasive prediction of IDH genotype. Prior to surgery, 84 patients with newly diagnosed and untreated gliomas underwent FET PET using a standard scanner (15 of 56 patients with IDH mut) or a dedicated high-resolution hybrid PET/MR scanner (11 of 28 patients with IDH mut). Static, dynamic and textural parameters of FET uptake in the tumor area were evaluated. Diagnostic accuracy of the parameters was evaluated using the neuropathological result as reference. Additionally, FET PET and textural parameters were combined to further increase the diagnostic accuracy. The resulting models were validated using cross-validation. Independent of scanner type, the combination of standard PET parameters with textural features increased significantly diagnostic accuracy. The highest diagnostic accuracy of 93% for prediction of IDH genotype was achieved with the hybrid PET/MR scanner. Our findings suggest that the combination of conventional FET PET parameters with textural features provides important diagnostic information for the non-invasive prediction of the IDH genotype.

Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis

Background

The aim of this study was to investigate the potential of combined textural feature analysis of contrast-enhanced MRI (CE-MRI) and static O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET) PET for the differentiation between local recurrent brain metastasis and radiation injury since CE-MRI often remains inconclusive.

Methods

Fifty-two patients with new or progressive contrast-enhancing brain lesions on MRI after radiotherapy (predominantly stereotactic radiosurgery) of brain metastases were additionally investigated using FET PET. Based on histology (n = 19) or clinicoradiological follow-up (n = 33), local recurrent brain metastases were diagnosed in 21 patients (40%) and radiation injury in 31 patients (60%). Forty-two textural features were calculated on both unfiltered and filtered CE-MRI and summed FET PET images (20–40 min p.i.), using the software LIFEx. After feature selection, logistic regression models using a maximum of five features to avoid overfitting were calculated for each imaging modality separately and for the combined FET PET/MRI features. The resulting models were validated using cross-validation. Diagnostic accuracies were calculated for each imaging modality separately as well as for the combined model.

Results

For the differentiation between radiation injury and recurrence of brain metastasis, textural features extracted from CE-MRI had a diagnostic accuracy of 81% (sensitivity, 67%; specificity, 90%). FET PET textural features revealed a slightly higher diagnostic accuracy of 83% (sensitivity, 88%; specificity, 75%). However, the highest diagnostic accuracy was obtained when combining CE-MRI and FET PET features (accuracy, 89%; sensitivity, 85%; specificity, 96%).

Conclusions

Our findings suggest that combined FET PET/CE-MRI radiomics using textural feature analysis offers a great potential to contribute significantly to the management of patients with brain metastases.

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Differentiation between brain metastasis recurrence and radiation injury is of high clinical importance.

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Differentiation based on contrast-enhanced conventional MRI is often inconclusive.

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Radiomics and hybrid amino acid PET/MR imaging are increasingly gaining attention in Neuro-Oncology.

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We investigated the potential of combined PET/MRI radiomics analysis using MRI and FET PET in patients with brain metastases.

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Combined PET/MRI radiomics allows the differentiation of brain metastasis recurrence from radiation injury with high accuracy.

Correlation of Dynamic O-(2-[18F]Fluoroethyl)-L-Tyrosine Positron Emission Tomography, Conventional Magnetic Resonance Imaging, and Whole-Brain Histopathology in a Pretreated Glioblastoma: A Postmortem Study

OBJECTIVE

Amino acid positron emission tomography (PET) using O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET) provides important additional information on the extent of viable tumor tissue of glioblastoma compared with magnetic resonance imaging (MRI). Especially after radiochemotherapy, progression of contrast enhancement in MRI is equivocal and may represent either tumor progression or treatment-related changes. Here, the first case comparing postmortem whole-brain histology of a patient with pretreated glioblastoma with dynamic in vivo FET PET and MRI is presented.

METHODS

A 61-year-old patient with glioblastoma initially underwent partial tumor resection and died 11 weeks after completion of chemoradiation with concurrent temozolomide. Three days before the patient died, a follow-up FET PET and MRI scan indicated tumor progression. Autopsy was performed 48 hours after death. After formalin fixation, a 7-cm bihemispherical segment of the brain containing the entire tumor mass was cut into 3500 consecutive 20μm coronal sections. Representative sections were stained with hematoxylin and eosin stain, cresyl violet, and glial fibrillary acidic protein immunohistochemistry. An experienced neuropathologist identified areas of dense and diffuse neoplastic infiltration, astrogliosis, and necrosis. In vivo FET PET, MRI datasets, and postmortem histology were co-registered and compared by 3 experienced physicians.

RESULTS

Increased uptake of FET in the area of equivocal contrast enhancement on MRI correlated very well with dense infiltration by vital tumor cells and showed tracer kinetics typical for malignant gliomas. An area of predominantly reactive astrogliosis showed only moderate uptake of FET and tracer kinetics usually observed in benign lesions.

CONCLUSIONS

This case report impressively documents the correct imaging of a progressive glioblastoma by FET PET.

Quantification of O-(2-[18F]fluoroethyl)-L-tyrosine kinetics in glioma

BACKGROUND

This study identified the optimal tracer kinetic model for quantification of dynamic O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) positron emission tomography (PET) studies in seven patients with diffuse glioma (four glioblastoma, three lower grade glioma). The performance of more simplified approaches was evaluated by comparison with the optimal compartment model. Additionally, the relationship with cerebral blood flow-determined by [15O]H2O PET-was investigated.

RESULTS

The optimal tracer kinetic model was the reversible two-tissue compartment model. Agreement analysis of binding potential estimates derived from reference tissue input models with the distribution volume ratio (DVR)-1 derived from the plasma input model showed no significant average difference and limits of agreement of - 0.39 and 0.37. Given the range of DVR-1 (- 0.25 to 1.5), these limits are wide. For the simplified methods, the 60-90 min tumour-to-blood ratio to parent plasma concentration yielded the highest correlation with volume of distribution VT as calculated by the plasma input model (r = 0.97). The 60-90 min standardized uptake value (SUV) showed better correlation with VT (r = 0.77) than SUV based on earlier intervals. The 60-90 min SUV ratio to contralateral healthy brain tissue showed moderate agreement with DVR with no significant average difference and limits of agreement of - 0.24 and 0.30. A significant but low correlation was found between VT and CBF in the tumour regions (r = 0.61, p = 0.007).

CONCLUSION

Uptake of [18F]FET was best modelled by a reversible two-tissue compartment model. Reference tissue input models yielded estimates of binding potential which did not correspond well with plasma input-derived DVR-1. In comparison, SUV ratio to contralateral healthy brain tissue showed slightly better performance, if measured at the 60-90 min interval. SUV showed only moderate correlation with VT. VT shows correlation with CBF in tumour.

[18F]Fluciclovine PET discrimination between high- and low-grade gliomas

BACKGROUND

The ability to accurately and non-invasively distinguish high-grade glioma from low-grade glioma remains a challenge despite advances in molecular and magnetic resonance imaging. We investigated the ability of fluciclovine (18F) PET as a means to identify and distinguish these lesions in patients with known gliomas and to correlate uptake with Ki-67.

RESULTS

Sixteen patients with a total of 18 newly diagnosed low-grade gliomas (n = 6) and high grade gliomas (n = 12) underwent fluciclovine PET imaging after histopathologic assessment. Fluciclovine PET analysis comprised tumor SUVmax and SUVmean, as well as metabolic tumor thresholds (1.3*, 1.6*, 1.9*) to normal brain background (TBmax, and TBmean). Comparison was additionally made to the proliferative status of the tumor as indicated by Ki-67 values. Fluciclovine uptake greater than normal brain parenchyma was found in all lesions studied. Time activity curves demonstrated statistically apparent flattening of the curves for both high-grade gliomas and low-grade gliomas starting 30 min after injection, suggesting an influx/efflux equilibrium. The best semiquantitative metric in discriminating HGG from LGG was obtained utilizing a metabolic 1 tumor threshold of 1.3* contralateral normal brain parenchyma uptake to create a tumor: background (TBmean1.3) cutoff of 2.15 with an overall sensitivity of 97.5% and specificity of 95.5%. Additionally, using a SUVmax > 4.3 cutoff gave a sensitivity of 90.9% and specificity of 97.5%. Tumor SUVmean and tumor SUVmax as a ratio to mean normal contralateral brain were both found to be less relevant predictors of tumor grade. Both SUVmax (R = 0.71, p = 0.0227) and TBmean (TBmean1.3: R = 0.81, p = 0.00081) had a high correlation with the tumor proliferative index Ki-67.

CONCLUSIONS

Fluciclovine PET produces high-contrast images between both low-grade and high grade gliomas and normal brain by visual and semiquantitative analysis. Fluciclovine PET appears to discriminate between low-grade glioma and high-grade glioma, but must be validated with a larger sample size.

Early treatment response evaluation using FET PET compared to MRI in glioblastoma patients at first progression treated with bevacizumab plus lomustine

BACKGROUND

The goal of this prospective study was to compare the value of both conventional MRI and O-(2-¹⁸F-fluoroethyl)-L-tyrosine (FET) PET for response evaluation in glioblastoma patients treated with bevacizumab plus lomustine (BEV/LOM) at first progression.

METHODS

After chemoradiation with concomitant and adjuvant temozolomide, 21 IDH wild-type glioblastoma patients at first progression (age range, 33-75 years; MGMT promoter unmethylated, 81%) were treated with BEV/LOM. Contrast-enhanced MRI and FET-PET scans were performed at baseline and after 8-10 weeks. We obtained FET metabolic tumor volumes (MTV) and tumor/brain ratios. Threshold values of FET-PET parameters for treatment response were established by ROC analyses using the post-progression overall survival (OS) ≤/>9 months as the reference. MRI response assessment was based on RANO criteria. The predictive ability of FET-PET thresholds and MRI changes on early response assessment was evaluated subsequently concerning OS using uni- and multivariate survival estimates.

RESULTS

Early treatment response as assessed by RANO criteria was not predictive for an OS>9 months (P = 0.203), whereas relative reductions of all FET-PET parameters significantly predicted an OS>9 months (P < 0.05). The absolute MTV at follow-up enabled the most significant OS prediction (sensitivity, 85%; specificity, 88%; P = 0.001). Patients with an absolute MTV below 5 ml at follow-up survived significantly longer (12 vs. 6 months, P < 0.001), whereas early responders defined by RANO criteria lived only insignificantly longer (9 vs. 6 months; P = 0.072). The absolute MTV at follow-up remained significant in the multivariate survival analysis (P = 0.006).

CONCLUSIONS

FET-PET appears to be useful for identifying responders to BEV/LOM early after treatment initiation.

Biological tumour volumes of gliomas in early and standard 20-40 min 18F-FET PET images differ according to IDH mutation status

PURPOSE

For the clinical evaluation of O-(2-¹⁸F-fluoroethyl)-L-tyrosine (¹⁸F-FET) PET images, the use of standard summation images obtained 20-40 min after injection is recommended. However, early summation images obtained 5-15 min after injection have been reported to allow better differentiation between low-grade glioma (LGG) and high-grade glioma (HGG) by capturing the early ¹⁸F-FET uptake peak specific for HGG. We compared early and standard summation images with regard to delineation of the PET-derived biological tumour volume (BTV) in correlation with the molecular genetic profile according the updated 2016 WHO classification.

METHODS

The analysis included 245 patients with newly diagnosed, histologically verified glioma and a positive ¹⁸F-FET PET scan prior to any further treatment. BTVs were delineated during the early 5-15 min and standard 20-40 min time frames using a threshold of 1.6 × background activity and were compared intraindividually. Volume differences between early and late summation images of >20% were considered significant and were correlated with WHO grade and the molecular genetic profile (IDH mutation and 1p/19q codeletion status).

RESULTS

In 52.2% of the patients (128/245), a significant difference in BTV of >20% between early and standard summation images was found. While 44.3% of WHO grade II gliomas (31 of 70) showed a significantly smaller BTV in the early summation images, 35.0% of WHO grade III gliomas (28/80) and 37.9% of WHO grade IV gliomas (36/95) had a significantly larger BTVs. Among IDH-wildtype gliomas, an even higher portion (44.4%, 67/151) showed significantly larger BTVs in the early summation images, which was observed in 5.3% (5/94) of IDH-mutant gliomas only: most of the latter had significantly smaller BTVs in the early summation images, i.e. 51.2% of IDH-mutant gliomas without 1p/19q codeletion (21/41) and 39.6% with 1p/19q codeletion (21/53).

CONCLUSION

BTVs delineated in early and standard summation images differed significantly in more than half of gliomas. While the standard summation images seem appropriate for delineation of LGG as well as IDH-mutant gliomas, a remarkably high percentage of HGG and, particularly, IDH-wildtype gliomas were depicted with significantly larger volumes in early summation images. This finding might be of interest for optimization of treatment planning (e.g. radiotherapy) in accordance with the individual IDH mutation status.

Hybrid MR-PET of brain tumours using amino acid PET and chemical exchange saturation transfer MRI

PURPOSE

PET using radiolabelled amino acids has become a promising tool in the diagnostics of gliomas and brain metastasis. Current research is focused on the evaluation of amide proton transfer (APT) chemical exchange saturation transfer (CEST) MR imaging for brain tumour imaging. In this hybrid MR-PET study, brain tumours were compared using 3D data derived from APT-CEST MRI and amino acid PET using O-(2-¹⁸F-fluoroethyl)-L-tyrosine (¹⁸F-FET).

METHODS

Eight patients with gliomas were investigated simultaneously with ¹⁸F-FET PET and APT-CEST MRI using a 3-T MR-BrainPET scanner. CEST imaging was based on a steady-state approach using a B₁ average power of 1μT. B₀ field inhomogeneities were corrected a Prametric images of magnetisation transfer ratio asymmetry (MTR_asym) and differences to the extrapolated semi-solid magnetisation transfer reference method, APT# and nuclear Overhauser effect (NOE#), were calculated. Statistical analysis of the tumour-to-brain ratio of the CEST data was performed against PET data using the non-parametric Wilcoxon test.

RESULTS

A tumour-to-brain ratio derived from APT# and ¹⁸F-FET presented no significant differences, and no correlation was found between APT# and ¹⁸F-FET PET data. The distance between local hot spot APT# and ¹⁸F-FET were different (average 20 ± 13 mm, range 4-45 mm).

CONCLUSION

For the first time, CEST images were compared with ¹⁸F-FET in a simultaneous MR-PET measurement. Imaging findings derived from¹⁸F-FET PET and APT CEST MRI seem to provide different biological information. The validation of these imaging findings by histological confirmation is necessary, ideally using stereotactic biopsy.

Evaluation of factors influencing 18F-FET uptake in the brain

PET using the amino-acid O-(2-¹⁸F-fluoroethyl)-l-tyrosine (¹⁸F-FET) is gaining increasing interest for brain tumour management. Semi-quantitative analysis of tracer uptake in brain tumours is based on the standardized uptake value (SUV) and the tumour-to-brain ratio (TBR). The aim of this study was to explore physiological factors that might influence the relationship of SUV of ¹⁸F-FET uptake in various brain areas, and thus affect quantification of ¹⁸F-FET uptake in brain tumours. Negative ¹⁸F-FET PET scans of 107 subjects, showing an inconspicuous brain distribution of ¹⁸F-FET, were evaluated retrospectively. Whole-brain quantitative analysis with Statistical Parametric Mapping (SPM) using parametric SUV PET images, and volumes of interest (VOIs) analysis with fronto-parietal, temporal, occipital, and cerebellar SUV background areas were performed to study the effect of age, gender, height, weight, injected activity, body mass index (BMI), and body surface area (BSA). After multivariate analysis, female gender and high BMI were found to be two independent factors associated with increased SUV of ¹⁸F-FET uptake in the brain. In women, SUV_mean of ¹⁸F-FET uptake in the brain was 23% higher than in men (p < 0.01). SUV_mean of ¹⁸F-FET uptake in the brain was positively correlated with BMI (r = 0.29; p < 0.01). The influence of these factors on SUV of ¹⁸F-FET was similar in all brain areas. In conclusion, SUV of ¹⁸F-FET in the normal brain is influenced by gender and weakly by BMI, but changes are similar in all brain areas.

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SUV_mean of ¹⁸F-FET in the normal brain is influenced by gender.

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SUV_mean of ¹⁸F-FET in the normal brain is weekly influenced by BMI.

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The influence of these factors on SUV of ¹⁸F-FET is similar in all brain areas.

Dynamic O-(2-18F-fluoroethyl)-L-tyrosine positron emission tomography differentiates brain metastasis recurrence from radiation injury after radiotherapy

Background

The aim of this study was to investigate the potential of dynamic O-(2-[18F]fluoroethyl)-L-tyrosine (18F-FET) PET for differentiating local recurrent brain metastasis from radiation injury after radiotherapy since contrast-enhanced MRI often remains inconclusive.

Methods

Sixty-two patients (mean age, 55 ± 11 y) with single or multiple contrast-enhancing brain lesions (n = 76) on MRI after radiotherapy of brain metastases (predominantly stereotactic radiosurgery) were investigated with dynamic 18F-FET PET. Maximum and mean tumor-to-brain ratios (TBRmax, TBRmean) of 18F-FET uptake were determined (20-40 min postinjection) as well as tracer uptake kinetics (ie, time-to-peak and slope of time-activity curves). Diagnoses were confirmed histologically (34%; 26 lesions in 25 patients) or by clinical follow-up (66%; 50 lesions in 37 patients). Diagnostic accuracies of PET parameters for the correct identification of recurrent brain metastasis were evaluated by receiver-operating-characteristic analyses or the chi-square test.

Results

TBRs were significantly higher in recurrent metastases (n = 36) than in radiation injuries (n = 40) (TBRmax 3.3 ± 1.0 vs 2.2 ± 0.4, P < .001; TBRmean 2.2 ± 0.4 vs 1.7 ± 0.3, P < .001). The highest accuracy (88%) for diagnosing local recurrent metastasis could be obtained with TBRs in combination with the slope of time-activity curves (P < .001).

Conclusions

The results of this study confirm previous preliminary observations that the combined evaluation of the TBRs of 18F-FET uptake and the slope of time-activity curves can differentiate local brain metastasis recurrence from radiation-induced changes with high accuracy. 18F-FET PET may thus contribute significantly to the management of patients with brain metastases.

RESOLUTE PET/MRI Attenuation Correction for O-(2-18F-fluoroethyl)-L-tyrosine (FET) in Brain Tumor Patients with Metal Implants

Aim: Positron emission tomography (PET) imaging is a useful tool for assisting in correct differentiation of tumor progression from reactive changes, and the radiolabeled amino acid analog tracer O-(2-¹⁸F-fluoroethyl)-L-tyrosine (FET)-PET is amongst the most frequently used. The FET-PET images need to be quantitatively correct in order to be used clinically, which require accurate attenuation correction (AC) in PET/MRI. The aim of this study was to evaluate the use of the subject-specific MR-derived AC method RESOLUTE in post-operative brain tumor patients.

Methods: We analyzed 51 post-operative brain tumor patients (68 examinations, 200 MBq [18F]-FET) investigated in a PET/MRI scanner. MR-AC maps were acquired using: (1) the Dixon water fat separation sequence, (2) the ultra short echo time (UTE) sequences, (3) calculated using our new RESOLUTE methodology, and (4) a same day low-dose CT used as reference “gold standard.” For each subject and each AC method the tumor was delineated by isocontouring tracer uptake above a tumor(T)-to-brain background (B) activity ratio of 1.6. We measured B, tumor mean and maximal activity (T_MEAN, T_MAX), biological tumor volume (BTV), and calculated the clinical metrics T_MEAN/B and T_MAX/B.

Results: When using RESOLUTE 5/68 studies did not meet our predefined acceptance criteria of T_MAX/B difference to CT-AC < ±0.1 or 5%, T_MEAN/B < ±0.05 or 5%, and BTV < ±2 mL or 10%. In total, 46/68 studies failed our acceptance criteria using Dixon, and 26/68 using UTE. The 95% limits of agreement for T_MAX/B was for RESOLUTE (−3%; 4%), Dixon (−9%; 16%), and UTE (−7%; 10%). The absolute error when measuring BTV was 0.7 ± 1.9 mL (N.S) with RESOLUTE, 5.3 ± 10 mL using Dixon, and 1.7 ± 3.7 mL using UTE. RESOLUTE performed best in the identification of the location of peak activity and in brain tumor follow-up monitoring using clinical FET PET metrics.

Conclusions: Overall, we found RESOLUTE to be the AC method that most robustly reproduced the CT-AC clinical metrics per se, during follow-up, and when interpreted into defined clinical use cut-off criteria and into the patient history. RESOLUTE is especially suitable for brain tumor patients, as these often present with distorted anatomy where other methods based on atlas/template information might fail.

Towards standardization of 18F-FET PET imaging: do we need a consistent method of background activity assessment?

Background

PET with O-(2-¹⁸F-fluoroethyl)-L-tyrosine (¹⁸F-FET) has reached increasing clinical significance for patients with brain neoplasms. For quantification of standard PET-derived parameters such as the tumor-to-background ratio, the background activity is assessed using a region of interest (ROI) or volume of interest (VOI) in unaffected brain tissue. However, there is no standardized approach regarding the assessment of the background reference. Therefore, we evaluated the intra- and inter-reader variability of commonly applied approaches for clinical ¹⁸F-FET PET reading.

The background activity of 20 ¹⁸F-FET PET scans was independently evaluated by 6 readers using a (i) simple 2D-ROI, (ii) spherical VOI with 3.0 cm diameter, and (iii) VOI consisting of crescent-shaped ROIs; each in the contralateral, non-affected hemisphere including white and gray matter in line with the European Association of Nuclear Medicine (EANM) and German guidelines. To assess intra-reader variability, each scan was evaluated 10 times by each reader. The coefficient of variation (CoV) was assessed for determination of intra- and inter-reader variability. In a second step, the best method was refined by instructions for a guided background activity assessment and validated by 10 further scans.

Results

Compared to the other approaches, the crescent-shaped VOIs revealed most stable results with the lowest intra-reader variabilities (median CoV 1.52%, spherical VOI 4.20%, 2D-ROI 3.69%; p < 0.001) and inter-reader variabilities (median CoV 2.14%, spherical VOI 4.02%, 2D-ROI 3.83%; p = 0.001). Using the guided background assessment, both intra-reader variabilities (median CoV 1.10%) and inter-reader variabilities (median CoV 1.19%) could be reduced even more.

Conclusions

The commonly applied methods for background activity assessment show different variability which might hamper ¹⁸F-FET PET quantification and comparability in multicenter settings. The proposed background activity assessment using a (guided) crescent-shaped VOI allows minimization of both intra- and inter-reader variability and might facilitate comprehensive methodological standardization of amino acid PET which is of interest in the light of the anticipated EANM technical guidelines.

The use of O-(2-18F-fluoroethyl)-L-tyrosine PET in the diagnosis of gliomas located in the brainstem and spinal cord

Background

Despite an increasing number of O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET) PET studies in supratentorial gliomas, studies regarding the usefulness of 18F-FET PET in brainstem and spinal cord gliomas to date remain scarce.

Methods

Thirty-six 18F-FET PET scans were performed in 29 patients with brainstem (n = 29 scans) or spinal cord glioma (n = 7 scans). In 32 of 36 PET scans, a dynamic acquisition was performed. Fifteen scans in 15 patients were performed to assess newly diagnosed lesions, and 21 scans were obtained during follow-up: for diagnosing tumor progression (n = 15 scans in 14 patients) as well as for treatment monitoring (n = 6 scans in 3 patients). Four patients underwent additional serial scans (range, 1-2), and 3 of these 4 patients were examined for more than one indication. Maximum and mean tumor/brain ratios (TBRmax/mean) of 18F-FET uptake (20-40 min post injection) as well as kinetic 18F-FET uptake parameters were determined. Final diagnoses were confirmed histologically (54%) or by clinical follow-up (46%).

Results

In all newly diagnosed high-grade (n = 3 patients) and in 5 of 11 patients with low-grade gliomas, 18F-FET uptake was increased (TBRmax ≥2.5 and/or TBRmean ≥1.9). In 2 patients with newly diagnosed gliomas without MR contrast enhancement, 18F-FET PET nevertheless showed increased metabolism. At suspected progression, the combination of TBRs with kinetic 18F-FET parameters correctly identified presence or absence of progressive disease in 9 of 11 patients (82%).

Conclusions

This preliminary study suggests that 18F-FET PET adds valuable diagnostic information in brainstem and spinal cord glioma, particularly when the diagnostic information derived from MRI is equivocal.

Clinical PET/MRI in neurooncology: opportunities and challenges from a single-institution perspective

Purpose

Magnetic resonance imaging (MRI) plays a key role in neurooncology, i.e., for diagnosis, treatment evaluation and detection of recurrence. However, standard MRI cannot always separate malignant tissue from other pathologies or treatment-induced changes. Advanced MRI techniques such as diffusion-weighted imaging, perfusion imaging and spectroscopy show promising results in discriminating malignant from benign lesions. Further, supplemental imaging with amino acid positron emission tomography (PET) has been shown to increase accuracy significantly and is used routinely at an increasing number of sites. Several centers are now implementing hybrid PET/MRI systems allowing for multiparametric imaging, combining conventional MRI with advanced MRI and amino acid PET imaging. Neurooncology is an obvious focus area for PET/MR imaging.

Methods

Based on the literature and our experience from more than 300 PET/MRI examinations of brain tumors with ¹⁸F-fluoro-ethyl-tyrosine, the clinical use of PET/MRI in adult and pediatric neurooncology is critically reviewed.

Results

Although the results are increasingly promising, the added value and range of indications for multiparametric imaging with PET/MRI are yet to be established. Robust solutions to overcome the number of issues when using a PET/MRI scanner are being developed, which is promising for a more routine use in the future.

Conclusions

In a clinical setting, a PET/MRI scan may increase accuracy in discriminating recurrence from treatment changes, although sequential same-day imaging on separate systems will often constitute a reliable and cost-effective alternative. Pediatric patients who require general anesthesia will benefit the most from simultaneous PET and MR imaging.

Radiation injury vs. recurrent brain metastasis: combining textural feature radiomics analysis and standard parameters may increase 18F-FET PET accuracy without dynamic scans

OBJECTIVES

We investigated the potential of textural feature analysis of O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (¹⁸F-FET) PET to differentiate radiation injury from brain metastasis recurrence.

METHODS

Forty-seven patients with contrast-enhancing brain lesions (n = 54) on MRI after radiotherapy of brain metastases underwent dynamic ¹⁸F-FET PET. Tumour-to-brain ratios (TBRs) of ¹⁸F-FET uptake and 62 textural parameters were determined on summed images 20-40 min post-injection. Tracer uptake kinetics, i.e., time-to-peak (TTP) and patterns of time-activity curves (TAC) were evaluated on dynamic PET data from 0-50 min post-injection. Diagnostic accuracy of investigated parameters and combinations thereof to discriminate between brain metastasis recurrence and radiation injury was compared.

RESULTS

Diagnostic accuracy increased from 81 % for TBR_mean alone to 85 % when combined with the textural parameter Coarseness or Short-zone emphasis. The accuracy of TBR_max alone was 83 % and increased to 85 % after combination with the textural parameters Coarseness, Short-zone emphasis, or Correlation. Analysis of TACs resulted in an accuracy of 70 % for kinetic pattern alone and increased to 83 % when combined with TBR_max.

CONCLUSIONS

Textural feature analysis in combination with TBRs may have the potential to increase diagnostic accuracy for discrimination between brain metastasis recurrence and radiation injury, without the need for dynamic ¹⁸F-FET PET scans.

KEY POINTS

• Textural feature analysis provides quantitative information about tumour heterogeneity • Textural features help improve discrimination between brain metastasis recurrence and radiation injury • Textural features might be helpful to further understand tumour heterogeneity • Analysis does not require a more time consuming dynamic PET acquisition.

18F-FET PET Uptake Characteristics in Patients with Newly Diagnosed and Untreated Brain Metastasis

In patients with brain metastasis, PET using labeled amino acids has gained clinical importance, mainly regarding the differentiation of viable tumor tissue from treatment-related effects. However, there is still limited knowledge concerning the uptake characteristics in patients with newly diagnosed and untreated brain metastases. Hence, we evaluated the uptake characteristics in these patients using dynamic O-(2-¹⁸F-fluoroethyl)-l-tyrosine (¹⁸F-FET) PET. Methods: Patients with newly diagnosed brain metastases without prior local therapy and ¹⁸F-FET PET scanning were retrospectively identified in 2 centers. Static and dynamic PET parameters (maximal/mean tumor-to-brain-ratio [TBR_max/TBR_mean], biologic tumor volume [BTV], and time-activity curves with minimal time to peak [TTP_min]) were evaluated and correlated with MRI parameters (maximal lesion diameter, volume of contrast enhancement) and originating primary tumor. Results: Forty-five brain metastases in 30 patients were included. Forty of 45 metastases (89%) had a TBR_max ≥ 1.6 and were classified as ¹⁸F-FET-positive (median TBR_max, 2.53 [range, 1.64-9.47]; TBR_mean, 1.86 [range, 1.63-5.48]; and BTV, 3.59 mL [range, 0.04-23.98 mL], respectively). In 39 of 45 brain metastases eligible for dynamic analysis, a wide range of TTP_min was observed (median, 22.5 min; range, 4.5-47.5 min). All ¹⁸F-FET-negative metastases had a diameter of ≤ 1.0 cm, whereas metastases with a > 1.0 cm diameter all showed pathologic ¹⁸F-FET uptake, which did not correlate with lesion size. The highest variability of uptake intensity was observed within the group of melanoma metastases. Conclusion: Untreated metastases predominantly show increased ¹⁸F-FET uptake, and only a third of metastases < 1.0 cm were ¹⁸F-FET-negative, most likely because of scanner resolution and partial-volume effects. In metastases > 1.0 cm, ¹⁸F-FET uptake intensity was highly variable and independent of tumor size (even intraindividually). ¹⁸F-FET PET might provide additional information beyond the tumor extent by reflecting molecular features of a metastasis and might be a useful tool for future clinical applications, for example, response assessment.

Epileptic Activity Increases Cerebral Amino Acid Transport Assessed by 18F-Fluoroethyl-l-Tyrosine Amino Acid PET: A Potential Brain Tumor Mimic

O-(2-¹⁸F-fluoroethyl)-l-tyrosine (¹⁸F-FET) PET is a well-established method increasingly used for diagnosis, treatment planning, and monitoring in gliomas. Epileptic activity, frequently occurring in glioma patients, can influence MRI findings. Whether seizures also affect ¹⁸F-FET PET imaging is currently unknown. The aim of this retrospective analysis was to investigate the brain amino acid metabolism during epileptic seizures by ¹⁸F-FET PET and to elucidate the pathophysiologic background.

METHODS

Ten patients with 11 episodes of serial seizures or status epilepticus, who underwent MRI and ¹⁸F-FET PET, were studied. The main diagnosis was glioma World Health Organization grade II-IV (n = 8); 2 patients suffered from nonneoplastic diseases. Immunohistochemical assessment of LAT1/LAT2/CD98 amino acid transporters was performed in seizure-affected cortex (n = 2) and compared with glioma tissues (n = 3).

RESULTS

All patients exhibited increased seizure-associated strict gyral ¹⁸F-FET uptake, which was reversible in follow-up studies or negative shortly before and without any histologic or clinical signs of tumor recurrence. ¹⁸F-FET uptake corresponded to structural MRI changes, compatible with cortical vasogenic and cytotoxic edema, partial contrast enhancement, and hyperperfusion. Patients with prolonged postictal symptoms lasting up to 8 wk displayed intensive and widespread (≥ 1 lobe) cortical ¹⁸F-FET uptake. LAT1/LAT2/CD98 was strongly expressed in neurons and endothelium of seizure-affected brains and less in reactive astrocytosis.

CONCLUSION

Seizure activity, in particular status epilepticus, increases cerebral amino acid transport with a strict gyral ¹⁸F-FET uptake pattern. Such periictal pseudoprogression represents a potential pitfall of ¹⁸F-FET PET and may mimic brain tumor. Our data also indicate a seizure-induced upregulation of neuronal, endothelial, and less astroglial LAT1/LAT2/CD98 amino acid transporter expression.

The use of dynamic O-(2-18F-fluoroethyl)-l-tyrosine PET in the diagnosis of patients with progressive and recurrent glioma

BACKGROUND

We evaluated the diagnostic value of static and dynamic O-(2-[(18)F]fluoroethyl)-L-tyrosine ((18)F-FET) PET parameters in patients with progressive or recurrent glioma.

METHODS

We retrospectively analyzed 132 dynamic (18)F-FET PET and conventional MRI scans of 124 glioma patients (primary World Health Organization grade II, n = 55; grade III, n = 19; grade IV, n = 50; mean age, 52 ± 14 y). Patients had been referred for PET assessment with clinical signs and/or MRI findings suggestive of tumor progression or recurrence based on Response Assessment in Neuro-Oncology criteria. Maximum and mean tumor/brain ratios of (18)F-FET uptake were determined (20-40 min post-injection) as well as tracer uptake kinetics (ie, time to peak and patterns of the time-activity curves). Diagnoses were confirmed histologically (95%) or by clinical follow-up (5%). Diagnostic accuracies of PET and MR parameters for the detection of tumor progression or recurrence were evaluated by receiver operating characteristic analyses/chi-square test.

RESULTS

Tumor progression or recurrence could be diagnosed in 121 of 132 cases (92%). MRI and (18)F-FET PET findings were concordant in 84% and discordant in 16%. Compared with the diagnostic accuracy of conventional MRI to diagnose tumor progression or recurrence (85%), a higher accuracy (93%) was achieved by (18)F-FET PET when a mean tumor/brain ratio ≥2.0 or time to peak <45 min was present (sensitivity, 93%; specificity, 100%; accuracy, 93%; positive predictive value, 100%; P < .001).

CONCLUSION

Static and dynamic (18)F-FET PET parameters differentiate progressive or recurrent glioma from treatment-related nonneoplastic changes with higher accuracy than conventional MRI.

Dual-time-point O-(2-[(18)F]fluoroethyl)-L-tyrosine PET for grading of cerebral gliomas

OBJECTIVE

We aimed to evaluate the diagnostic potential of dual-time-point imaging with positron emission tomography (PET) using O-(2-[(18)F]fluoroethyl)-L-tyrosine ((18)F-FET) for non-invasive grading of cerebral gliomas compared with a dynamic approach.

METHODS

Thirty-six patients with histologically confirmed cerebral gliomas (21 primary, 15 recurrent; 24 high-grade, 12 low-grade) underwent dynamic PET from 0 to 50 min post-injection (p.i.) of (18)F-FET, and additionally from 70 to 90 min p.i. Mean tumour-to-brain ratios (TBRmean) of (18)F-FET uptake were determined in early (20-40 min p.i.) and late (70-90 min p.i.) examinations. Time-activity curves (TAC) of the tumours from 0 to 50 min after injection were assigned to different patterns. The diagnostic accuracy of changes of (18)F-FET uptake between early and late examinations for tumour grading was compared to that of curve pattern analysis from 0 to 50 min p.i. of (18)F-FET.

RESULTS

The diagnostic accuracy of changes of the TBRmean of (18)F-FET PET uptake between early and late examinations for the identification of HGG was 81% (sensitivity 83%; specificity 75%; cutoff - 8%; p < 0.001), and 83% for curve pattern analysis (sensitivity 88%; specificity 75%; p < 0.001).

CONCLUSION

Dual-time-point imaging of (18)F-FET uptake in gliomas achieves diagnostic accuracy for tumour grading that is similar to the more time-consuming dynamic data acquisition protocol.

KEY POINTS

• Dual-time-point imaging is equivalent to dynamic FET PET for grading of gliomas. • Dual-time-point imaging is less time consuming than dynamic FET PET. • Costs can be reduced due to higher patient throughput. • Reduced imaging time increases patient comfort and sedation might be avoided. • Quicker image interpretation is possible, as no curve evaluation is necessary.

Tumor-associated macrophages in glioblastoma multiforme-a suitable target for somatostatin receptor-based imaging and therapy?

Background

Glioblastoma multiforme (GBM) is the most common primary brain tumor in adults. Tumor-associated macrophages (TAM) have been shown to promote malignant growth and to correlate with poor prognosis. [1,4,7,10-tetraazacyclododecane-NN′,N″,N′″-tetraacetic acid]-d-Phe1,Tyr3-octreotate (DOTATATE) labeled with Gallium-68 selectively binds to somatostatin receptor 2A (SSTR2A) which is specifically expressed and up-regulated in activated macrophages. On the other hand, the role of SSTR2A expression on the cell surface of glioma cells has not been fully elucidated yet. The aim of this study was to non-invasively assess SSTR2A expression of both glioma cells as well as macrophages in GBM.

Methods

15 samples of patient-derived GBM were stained immunohistochemically for macrophage infiltration (CD68), proliferative activity (Ki67) as well as expression of SSTR2A. Anti-CD45 staining was performed to distinguish between resident microglia and tumor-infiltrating macrophages. In a subcohort, positron emission tomography (PET) imaging using ⁶⁸Ga-DOTATATE was performed and the semiquantitatively evaluated tracer uptake was compared to the results of immunohistochemistry.

Results

The amount of microglia/macrophages ranged from <10% to >50% in the tumor samples with the vast majority being resident microglial cells. A strong SSTR2A immunostaining was observed in endothelial cells of proliferating vessels, in neurons and neuropile. Only faint immunostaining was identified on isolated microglial and tumor cells. Somatostatin receptor imaging revealed areas of increased tracer accumulation in every patient. However, retention of the tracer did not correlate with immunohistochemical staining patterns.

Conclusion

SSTR2A seems not to be overexpressed in GBM samples tested, neither on the cell surface of resident microglia or infiltrating macrophages, nor on the surface of tumor cells. These data suggest that somatostatin receptor directed imaging and treatment strategies are less promising in GBM.

The usefulness of dynamic O-(2-18F-fluoroethyl)-L-tyrosine PET in the clinical evaluation of brain tumors in children and adolescents

Experience regarding O-(2-(18)F-fluoroethyl)-L-tyrosine ((18)F-FET) PET in children and adolescents with brain tumors is limited.

METHODS

Sixty-nine (18)F-FET PET scans of 48 children and adolescents (median age, 13 y; range, 1-18 y) were analyzed retrospectively. Twenty-six scans to assess newly diagnosed cerebral lesions, 24 scans for diagnosing tumor progression or recurrence, 8 scans for monitoring of chemotherapy effects, and 11 scans for the detection of residual tumor after resection were obtained. Maximum and mean tumor-to-brain ratios (TBRs) were determined at 20-40 min after injection, and time-activity curves of (18)F-FET uptake were assigned to 3 different patterns: constant increase; peak at greater than 20-40 min after injection, followed by a plateau; and early peak (≤ 20 min), followed by a constant descent. The diagnostic accuracy of (18)F-FET PET was assessed by receiver-operating-characteristic curve analyses using histology or clinical course as a reference.

RESULTS

In patients with newly diagnosed cerebral lesions, the highest accuracy (77%) to detect neoplastic tissue (19/26 patients) was obtained when the maximum TBR was 1.7 or greater (area under the curve, 0.80 ± 0.09; sensitivity, 79%; specificity, 71%; positive predictive value, 88%; P = 0.02). For diagnosing tumor progression or recurrence, the highest accuracy (82%) was obtained when curve patterns 2 or 3 were present (area under the curve, 0.80 ± 0.11; sensitivity, 75%; specificity, 90%; positive predictive value, 90%; P = 0.02). During chemotherapy, a decrease of TBRs was associated with a stable clinical course, and in 2 patients PET detected residual tumor after presumably complete tumor resection.

CONCLUSION

Our findings suggest that (18)F-FET PET can add valuable information for clinical decision making in pediatric brain tumor patients.

Diagnosis of pseudoprogression in patients with glioblastoma using O-(2-[18F]fluoroethyl)-L-tyrosine PET

PURPOSE

The follow-up of glioblastoma patients after radiochemotherapy with conventional MRI can be difficult since reactive alterations to the blood-brain barrier with contrast enhancement may mimic tumour progression (i.e. pseudoprogression, PsP). The aim of this study was to assess the clinical value of O-(2-(18)F-fluoroethyl)-L-tyrosine ((18)F-FET) PET in the differentiation of PsP and early tumour progression (EP) after radiochemotherapy of glioblastoma.

METHODS

A group of 22 glioblastoma patients with new contrast-enhancing lesions or lesions showing increased enhancement (>25 %) on standard MRI within the first 12 weeks after completion of radiochemotherapy with concomitant temozolomide (median 7 weeks) were additionally examined using amino acid PET with (18)F-FET. Maximum and mean tumour-to-brain ratios (TBRmax, TBRmean) were determined. (18)F-FET uptake kinetic parameters (i.e. patterns of time-activity curves, TAC) were also evaluated. Classification as PsP or EP was based on the clinical course (no treatment change at least for 6 months), follow-up MR imaging and/or histopathological findings. Imaging results were also related to overall survival (OS).

RESULTS

PsP was confirmed in 11 of the 22 patients. In patients with PsP, (18)F-FET uptake was significantly lower than in patients with EP (TBRmax 1.9 ± 0.4 vs. 2.8 ± 0.5, TBRmean 1.8 ± 0.2 vs. 2.3 ± 0.3; both P < 0.001) and presence of MGMT promoter methylation was significantly more frequent (P = 0.05). Furthermore, a TAC type II or III was more frequently present in patients with EP (P = 0.04). Receiver operating characteristic analysis showed that the optimal (18)F-FET TBRmax cut-off value for identifying PsP was 2.3 (sensitivity 100 %, specificity 91 %, accuracy 96 %, AUC 0.94 ± 0.06; P < 0.001). Univariate survival analysis showed that a TBRmax <2.3 predicted a significantly longer OS (median OS 23 vs. 12 months; P = 0.046).

CONCLUSION

(18)F-FET PET may facilitate the diagnosis of PsP following radiochemotherapy of glioblastoma.