Diagnosis of glioma recurrence using multiparametric dynamic 18F-fluoroethyl-tyrosine PET-MRI

The Value of Multidisciplinary Neuro-oncological Tumor Boards to Increase the Accuracy of FET PET for Identifying Brain Tumor Relapse

PURPOSE

Especially in Europe, amino acid PET is increasingly integrated into multidisciplinary neuro-oncological tumor boards (MNTBs) to overcome diagnostic uncertainties such as treatment-related changes. We evaluated the accuracy of MNTB decisions that included the O -(2-[ 18 F]-fluoroethyl)-L-tyrosine (FET) PET information compared with FET PET results alone to differentiate tumor relapse from treatment-related changes.

PATIENTS AND METHODS

In a single academic center, we retrospectively evaluated 180 MNTB decisions of 151 patients with CNS WHO grade 3 or 4 gliomas (n = 122) or brain metastases (n = 29) presenting equivocal MRI findings following anticancer treatment. All patients underwent FET PET imaging besides MRI before MNTB discussion. Additionally, the patient's clinical status and pretreatment were considered for decision-making. The diagnostic performance was calculated for FET PET findings alone and MNTB decisions that included FET PET results using 2 × 2 contingency tables. MNTB decisions were validated using the neuropathological result in 43% (n = 78) or clinicoradiologically in 57% (n = 102).

RESULTS

FET PET results alone yielded an accuracy of 87% (sensitivity, 90%; specificity, 65%; positive predictive value, 95%). When integrating FET PET results for decision-making in the MNTB setting, the accuracy increased to 95% (sensitivity, 99%; specificity, 70%; positive predictive value, 96%; P = 0.002). In MNTB decisions concerning glioblastoma patients, the median survival was 2.4 times longer when FET PET suggested treatment-related changes (15.6 vs 6.4 months; P = 0.009).

CONCLUSIONS

Our results suggest that MNTB discussion further enhances the FET PET value for identifying brain tumor relapse. A prospective evaluation of FET PET results with and without integration in an MNTB is warranted.

Advances in Glioblastoma Diagnosis: Integrating Genetics, Noninvasive Sampling, and Advanced Imaging

Glioblastoma is the most common primary brain tumor in adult patients, and despite standard-of-care treatment, median survival has remained less than two years. Advances in our understanding of molecular mutations have led to changes in the diagnostic criteria of glioblastoma, with the WHO classification integrating important mutations into the grading system in 2021. We sought to review the basics of the important genetic mutations associated with glioblastoma, including known mechanisms and roles in disease pathogenesis/treatment. We also examined new advances in image processing as well as less invasive and noninvasive diagnostic tools that can aid in the diagnosis and surveillance of those undergoing treatment for glioblastoma. Our review is intended to serve as an overview of the current state-of-the-art in the diagnosis and management of glioblastoma.

The State-of-the-Art PET Tracers in Glioblastoma and High-grade Gliomas and Implications for Theranostics

MR imaging is currently the main imaging modality used for the diagnosis and post therapeutic assessment of glioblastomas. Recently, several innovative PET radioactive tracers have been investigated for the evaluation of glioblastomas (GBM). These radiotracers target several biochemical and pathophysiological processes seen in tumors. These include glucose metabolism, DNA synthesis and cell proliferation, amino acid transport, cell membrane biosynthesis, specific membrane antigens such as prostatic specific membrane antigens, fibroblast activation protein inhibitor, translocator protein and hypoxia sensing agents, and antibodies targeting specific cell receptor antigen. This review aims to discuss the clinical value of these PET radiopharmaceuticals in the evaluation and treatment of GBMs.

A physics-informed deep learning framework for dynamic susceptibility contrast perfusion MRI

BACKGROUND

Perfusion magnetic resonance imaging (MRI)s plays a central role in the diagnosis and monitoring of neurovascular or neurooncological disease. However, conventional processing techniques are limited in their ability to capture relevant characteristics of the perfusion dynamics and suffer from a lack of standardization.

PURPOSE

We propose a physics-informed deep learning framework which is capable of analyzing dynamic susceptibility contrast perfusion MRI data and recovering the dynamic tissue response with high accuracy.

METHODS

The framework uses physics-informed neural networks (PINNs) to learn the voxel-wise TRF, which represents the dynamic response of the local vascular network to the contrast agent bolus. The network output is stabilized by total variation and elastic net regularization. Parameter maps of normalized cerebral blood flow (nCBF) and volume (nCBV) are then calculated from the predicted residue functions. The results are validated using extensive comparisons to values derived by conventional Tikhonov-regularized singular value decomposition (TiSVD), in silico simulations and an in vivo dataset of perfusion MRI exams of patients with high-grade gliomas.

RESULTS

The simulation results demonstrate that PINN-derived residue functions show a high concordance with the true functions and that the calculated values of nCBF and nCBV converge towards the true values for higher contrast-to-noise ratios. In the in vivo dataset, we find high correlations between conventionally derived and PINN-predicted perfusion parameters (Pearson's rho for nCBF:0.84 ± 0.03 $0.84 \pm 0.03$ and nCBV:0.92 ± 0.03 $0.92 \pm 0.03$ ) and very high indices of image similarity (structural similarity index for nCBF:0.91 ± 0.03 $0.91 \pm 0.03$ and for nCBV:0.98 ± 0.00 $0.98 \pm 0.00$ ).

CONCLUSIONS

PINNs can be used to analyze perfusion MRI data and stably recover the response functions of the local vasculature with high accuracy.

Contribution of [18F]FET PET in the Management of Gliomas, from Diagnosis to Follow-Up: A Review

Gliomas, the most common type of primary malignant brain tumors in adults, pose significant challenges in diagnosis and management due to their heterogeneity and potential aggressiveness. This review evaluates the utility of O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) positron emission tomography (PET), a promising imaging modality, to enhance the clinical management of gliomas. We reviewed 82 studies involving 4657 patients, focusing on the application of [18F]FET in several key areas: diagnosis, grading, identification of IDH status and presence of oligodendroglial component, guided resection or biopsy, detection of residual tumor, guided radiotherapy, detection of malignant transformation in low-grade glioma, differentiation of recurrence versus treatment-related changes and prognostic factors, and treatment response evaluation. Our findings confirm that [18F]FET helps delineate tumor tissue, improves diagnostic accuracy, and aids in therapeutic decision-making by providing crucial insights into tumor metabolism. This review underscores the need for standardized parameters and further multicentric studies to solidify the role of [18F]FET PET in routine clinical practice. By offering a comprehensive overview of current research and practical implications, this paper highlights the added value of [18F]FET PET in improving management of glioma patients from diagnosis to follow-up.

11C-Methionine uptake in meningiomas after stereotactic radiotherapy

OBJECTIVE

11C-Methionine positron emission tomography (MET-PET) is used for stereotactic radiotherapy planning in meningioma patients. The role of MET-PET during subsequent follow-up (FU) is unclear. We analyzed the uptake of 11C-Methionine before and after stereotactic radiotherapy (SRT) in patients with a complex meningioma and investigated if there was a difference between patients with progressive disease (PD) and stable disease (SD) during FU.

METHODS

This retrospective study investigates 62 MET-PETs in 29 complex meningioma patients. Standardized uptake value (SUV)max and SUVpeak tumor-to-normal ratios (T/N-ratios) were calculated, comparing the tumor region with both the mirroring intracranial area and the right frontal gray matter. The difference in 11C-Methionine uptake pre- and post-SRT was analyzed, as well as the change in uptake between PD or SD.

RESULTS

Median (IQR) FU duration was 67 months (50.5-91.0). The uptake of 11C-Methionine in meningiomas remained increased after SRT. Neither a statistically significant difference between MET-PETs before and after SRT was encountered, nor a significant difference in one of the four T/N-ratios between patients with SD versus PD with median (IQR) SUVmax T/NR front 2.65 (2.13-3.68) vs 2.97 (1.55-3.54) [p = 0.66]; SUVmax T/Nmirror 2.92 (2.19-3.71) vs 2.95 (1.74-3.60) [p = 0.61]; SUVpeak T/NR front 2.35 (1.64-3.40) vs 2.25 (1.44-3.74) [p = 0.80]; SUVpeak T/Nmirror 2.38 (1.91-3.36) vs 2.35 (1.56-3.72) [p = 0.95].

CONCLUSIONS

Our data do not support use of MET-PET during FU of complex intracranial meningiomas after SRT. MET-PET could not differentiate between progressive or stable disease.

Hybrid Positron Emission Tomography and Magnetic Resonance Imaging Guided Microsurgical Management of Glial Tumors: Case Series and Review of the Literature

In this case series, we aimed to report our clinical experience with hybrid positron emission tomography (PET) and magnetic resonance imaging (MRI) navigation in the management of recurrent glial brain tumors. Consecutive recurrent neuroglial brain tumor patients who underwent PET/MRI at preoperative or intraoperative periods were included, whereas patients with non-glial intracranial tumors including metastasis, lymphoma and meningioma were excluded from the study. A total of eight patients (mean age 50.1 ± 11.0 years) with suspicion of recurrent glioma tumor were evaluated. Gross total tumor resection of the PET/MRI-positive area was achieved in seven patients, whereas one patient was diagnosed with radiation necrosis, and surgery was avoided. All patients survived at 1-year follow-up. Five (71.4%) of the recurrent patients remained free of recurrence for the entire follow-up period. Two patients with glioblastoma had tumor recurrence at the postoperative sixth and eighth months. According to our results, hybrid PET/MRI provides reliable and accurate information to distinguish recurrent glial tumor from radiation necrosis. With the help of this differential diagnosis, hybrid imaging may provide the gross total resection of recurrent tumors without harming eloquent brain areas.

Multiparametric Analysis Combining DSC-MR Perfusion and [18F]FET-PET is Superior to a Single Parameter Approach for Differentiation of Progressive Glioma from Radiation Necrosis

PURPOSE

Perfusion-weighted (PWI) magnetic resonance imaging (MRI) and O‑(2-[18F]fluoroethyl-)-l-tyrosine ([18F]FET) positron emission tomography (PET) are both useful for discrimination of progressive disease (PD) from radiation necrosis (RN) in patients with gliomas. Previous literature showed that the combined use of FET-PET and MRI-PWI is advantageous; hhowever the increased diagnostic performances were only modest compared to the use of a single modality. Hence, the goal of this study was to further explore the benefit of combining MRI-PWI and [18F]FET-PET for differentiation of PD from RN. Secondarily, we evaluated the usefulness of cerebral blood flow (CBF), mean transit time (MTT) and time to peak (TTP) as previous studies mainly examined cerebral blood volume (CBV).

METHODS

In this single center study, we retrospectively identified patients with WHO grades II-IV gliomas with suspected tumor recurrence, presenting with ambiguous findings on structural MRI. For differentiation of PD from RN we used both MRI-PWI and [18F]FET-PET. Dynamic susceptibility contrast MRI-PWI provided normalized parameters derived from perfusion maps (r(relative)CBV, rCBF, rMTT, rTTP). Static [18F]FET-PET parameters including mean and maximum tumor to brain ratios (TBRmean, TBRmax) were calculated. Based on histopathology and radioclinical follow-up we diagnosed PD in 27 and RN in 10 cases. Using the receiver operating characteristic (ROC) analysis, area under the curve (AUC) values were calculated for single and multiparametric models. The performances of single and multiparametric approaches were assessed with analysis of variance and cross-validation.

RESULTS

After application of inclusion and exclusion criteria, we included 37 patients in this study. Regarding the in-sample based approach, in single parameter analysis rTBRmean (AUC = 0.91, p < 0.001), rTBRmax (AUC = 0.89, p < 0.001), rTTP (AUC = 0.87, p < 0.001) and rCBVmean (AUC = 0.84, p < 0.001) were efficacious for discrimination of PD from RN. The rCBFmean and rMTT did not reach statistical significance. A classification model consisting of TBRmean, rCBVmean and rTTP achieved an AUC of 0.98 (p < 0.001), outperforming the use of rTBRmean alone, which was the single parametric approach with the highest AUC. Analysis of variance confirmed the superiority of the multiparametric approach over the single parameter one (p = 0.002). While cross-validation attributed the highest AUC value to the model consisting of TBRmean and rCBVmean, it also suggested that the addition of rTTP resulted in the highest accuracy. Overall, multiparametric models performed better than single parameter ones.

CONCLUSION

A multiparametric MRI-PWI and [18F]FET-PET model consisting of TBRmean, rCBVmean and PWI rTTP significantly outperformed the use of rTBRmean alone, which was the best single parameter approach. Secondarily, we firstly report the potential usefulness of PWI rTTP for discrimination of PD from RN in patients with glioma; however, for validation of our findings the prospective studies with larger patient samples are necessary.

Detection of recurrent high-grade glioma using microstructure characteristics of distinct metabolic compartments in a multimodal and integrative 18F-FET PET/fast-DKI approach

OBJECTIVES

Differentiation between high-grade glioma (HGG) and post-treatment-related effects (PTRE) is challenging, but advanced imaging techniques were shown to provide benefit. We aim to investigate microstructure characteristics of metabolic compartments identified from amino acid PET and to evaluate the diagnostic potential of this multimodal and integrative O-(2-18F-fluoroethyl)-L-tyrosine-(FET)-PET and fast diffusion kurtosis imaging (DKI) approach for the detection of recurrence and IDH genotyping.

METHODS

Fifty-nine participants with neuropathologically confirmed recurrent HGG (n = 39) or PTRE (n = 20) were investigated using static 18F-FET PET and a fast-DKI variant. PET and advanced diffusion metrics of metabolically defined (80-100% and 60-75% areas of 18F-FET uptake) compartments were assessed. Comparative analysis was performed using Mann-Whitney U tests with Holm-Šídák multiple-comparison test and Wilcoxon signed-rank test. Receiver operating characteristic (ROC) curves, regression, and Spearman's correlation analysis were used for statistical evaluations.

RESULTS

Compared to PTRE, recurrent HGG presented increased 18F-FET uptake and diffusivity (MD60), but lower (relative) mean kurtosis tensor (rMKT60) and fractional anisotropy (FA60) (respectively p < .05). Diffusion metrics determined from the metabolic periphery showed improved diagnostic performance - most pronounced for FA60 (AUC = 0.86, p < .001), which presented similar benefit to 18F-FET PET (AUC = 0.86, p < .001) and was negatively correlated with amino acid uptake (rs =  - 0.46, p < .001). When PET and DKI metrics were evaluated in a multimodal biparametric approach, TBRmax + FA60 showed highest diagnostic accuracy (AUC = 0.93, p < .001), which improved the detection of relapse compared to PET alone (difference in AUC = 0.069, p = .04). FA60 and MD60 distinguished the IDH genotype in the post-treatment setting.

CONCLUSION

Detection of glioma recurrence benefits from a multimodal and integrative PET/DKI approach, which presented significant diagnostic advantage to the assessment based on PET alone.

CLINICAL RELEVANCE STATEMENT

A multimodal and integrative 18F-FET PET/fast-DKI approach for the non-invasive microstructural characterization of metabolic compartments provided improved diagnostic capability for differentiation between recurrent glioma and post-treatment-related changes, suggesting a role for the diagnostic workup of patients in post-treatment settings.

KEY POINTS

• Multimodal PET/MRI with integrative analysis of 18F-FET PET and fast-DKI presents clinical benefit for the assessment of CNS cancer, particularly for the detection of recurrent high-grade glioma. • Microstructure markers of the metabolic periphery yielded biologically pertinent estimates characterising the tumour microenvironment, and, thereby, presented improved diagnostic accuracy with similar accuracy to amino acid PET. • Combined 18F-FET PET/fast-DKI achieved the best diagnostic performance for detection of high-grade glioma relapse with significant benefit to the assessment based on PET alone.

Assessment of Brain Tumour Perfusion Using Early-Phase 18F-FET PET: Comparison with Perfusion-Weighted MRI

PURPOSE

Morphological imaging using MRI is essential for brain tumour diagnostics. Dynamic susceptibility contrast (DSC) perfusion-weighted MRI (PWI), as well as amino acid PET, may provide additional information in ambiguous cases. Since PWI is often unavailable in patients referred for amino acid PET, we explored whether maps of relative cerebral blood volume (rCBV) in brain tumours can be extracted from the early phase of PET using O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET).

PROCEDURE

Using a hybrid brain PET/MRI scanner, PWI and dynamic 18F-FET PET were performed in 33 patients with cerebral glioma and four patients with highly vascularized meningioma. The time interval from 0 to 2 min p.i. was selected to best reflect the blood pool phase in 18F-FET PET. For each patient, maps of MR-rCBV, early 18F-FET PET (0-2 min p.i.) and late 18F-FET PET (20-40 min p.i.) were generated and coregistered. Volumes of interest were placed on the tumour (VOI-TU) and normal-appearing brain (VOI-REF). The correlation between tumour-to-brain ratios (TBR) of the different parameters was analysed. In addition, three independent observers evaluated MR-rCBV and early 18F-FET maps (18F-FET-rCBV) for concordance in signal intensity, tumour extent and intratumoural distribution.

RESULTS

TBRs calculated from MR-rCBV and 18F-FET-rCBV showed a significant correlation (r = 0.89, p < 0.001), while there was no correlation between late 18F-FET PET and MR-rCBV (r = 0.24, p = 0.16) and 18F-FET-rCBV (r = 0.27, p = 0.11). Visual rating yielded widely agreeing findings or only minor differences between MR-rCBV maps and 18F-FET-rCBV maps in 93 % of the tumours (range of three independent raters 91-94%, kappa among raters 0.78-1.0).

CONCLUSION

Early 18F-FET maps (0-2 min p.i.) in gliomas provide similar information to MR-rCBV maps and may be helpful when PWI is not possible or available. Further studies in gliomas are needed to evaluate whether 18F-FET-rCBV provides the same clinical information as MR-rCBV.

Comparing [18F]FET PET and [18F]FDOPA PET for glioma recurrence diagnosis: a systematic review and meta-analysis

Purpose

The purpose of our meta-analysis and systematic review was to evaluate and compare the diagnostic effectiveness of [18F]FET PET and [18F]FDOPA PET in detecting glioma recurrence.

Methods

Sensitivities and specificities were assessed using the DerSimonian and Laird methodology, and subsequently transformed using the Freeman-Tukey double inverse sine transformation. Confidence intervals were computed employing the Jackson method, while heterogeneity within and between groups was evaluated through the Cochrane Q and I² statistics. If substantial heterogeneity among the studies was observed (P < 0.10 or I² > 50%), we conducted meta-regression and sensitivity analyses. Publication bias was assessed through the test of a funnel plot and the application of Egger's test. For all statistical tests, except for assessing heterogeneity (P < 0.10), statistical significance was determined when the two-tailed P value fell below 0.05.

Results

Initially, 579 publications were identified, and ultimately, 22 studies, involving 1514 patients(1226 patients for [18F]FET PET and 288 patients for [18F]FDOPA PET), were included in the analysis. The sensitivity and specificity of [18F]FET PET were 0.84 (95% CI, 0.75-0.90) and 0.86 (95% CI, 0.80-0.91), respectively, while for [18F]FDOPA PET, the values were 0.95 (95% CI, 0.86-1.00) for sensitivity and 0.90 (95% CI, 0.77-0.98) for specificity. A statistically significant difference in sensitivity existed between these two radiotracers (P=0.04), while no significant difference was observed in specificity (P=0.58).

Conclusion

It seems that [18F]FDOPA PET demonstrates superior sensitivity and similar specificity to [18F] FET PET. Nevertheless, it's crucial to emphasize that [18F]FDOPA PET results were obtained from studies with limited sample sizes. Further larger prospective studies, especially head-to-head comparisons, are needed in this issue.

Systematic Review Registration

identifier CRD42023463476.

18F-Fluoroethyl-L Tyrosine Positron Emission Tomography Radiomics in the Differentiation of Treatment-Related Changes from Disease Progression in Patients with Glioblastoma

The follow-up of glioma patients after therapeutic intervention remains a challenging topic, as therapy-related changes can emulate true progression in contrast-enhanced magnetic resonance imaging. 18F-fluoroethyl-tyrosine (18F-FET) is a radiopharmaceutical that accumulates in glioma cells due to an increased expression of L-amino acid transporters and, contrary to gadolinium, does not depend on blood-brain barrier disruption to reach tumoral cells. It has demonstrated a high diagnostic value in the differentiation of tumoral viability and pseudoprogression or any other therapy-related changes, especially when combining traditional visual analysis with modern radiomics. In this review, we aim to cover the potential role of 18F-FET positron emission tomography in everyday clinical practice when applied to the follow-up of patients after the first therapeutical intervention, early response evaluation, and the differential diagnosis between therapy-related changes and progression.

Clinical Value of Hybrid PET/MR Imaging: Brain Imaging Using PET/MR Imaging

Hybrid PET/MR imaging offers a unique opportunity to acquire MR imaging and PET information during a single imaging session. PET/MR imaging has numerous advantages, including enhanced diagnostic accuracy, improved disease characterization, and better treatment planning and monitoring. It enables the immediate integration of anatomic, functional, and metabolic imaging information, allowing for personalized characterization and monitoring of neurologic diseases. This review presents recent advances in PET/MR imaging and highlights advantages in clinical practice for neuro-oncology, epilepsy, and neurodegenerative disorders. PET/MR imaging provides valuable information about brain tumor metabolism, perfusion, and anatomic features, aiding in accurate delineation, treatment response assessment, and prognostication.

Radiomics: The New Promise for Differentiating Progression, Recurrence, Pseudoprogression, and Radionecrosis in Glioma and Glioblastoma Multiforme

Glioma and glioblastoma multiform (GBM) remain among the most debilitating and life-threatening brain tumors. Despite advances in diagnosing approaches, patient follow-up after treatment (surgery and chemoradiation) is still challenging for differentiation between tumor progression/recurrence, pseudoprogression, and radionecrosis. Radiomics emerges as a promising tool in initial diagnosis, grading, and survival prediction in patients with glioma and can help differentiate these post-treatment scenarios. Preliminary published studies are promising about the role of radiomics in post-treatment glioma/GBM. However, this field faces significant challenges, including a lack of evidence-based solid data, scattering publication, heterogeneity of studies, and small sample sizes. The present review explores radiomics's capabilities in following patients with glioma/GBM status post-treatment and to differentiate tumor progression, recurrence, pseudoprogression, and radionecrosis.

Prediction of Glioma Grade and IDH Status Using 18F-FET PET/CT Dynamic and Multiparametric Texture Analysis

Mutations in isocitrate dehydrogenase (IDH) represent an independent predictor of better survival in patients with gliomas. We aimed to assess grade and IDH mutation status in patients with untreated gliomas, by evaluating the respective value of 18F-FET PET/CT via dynamic and texture analyses. A total of 73 patients (male: 48, median age: 47) who underwent an 18F-FET PET/CT for initial glioma evaluation were retrospectively included. IDH status was available in 61 patients (20 patients with WHO grade 2 gliomas, 41 with grade 3-4 gliomas). Time-activity curve type and 20 parameters obtained from static analysis using LIFEx© v6.30 software were recorded. Respective performance was assessed using receiver operating characteristic curve analysis and stepwise multivariate regression analysis adjusted for patients' age and sex. The time-activity curve type and texture parameters derived from the static parameters showed satisfactory-to-good performance in predicting glioma grade and IDH status. Both time-activity curve type (stepwise OR: 101.6 (95% CI: 5.76-1791), p = 0.002) and NGLDM coarseness (stepwise OR: 2.08 × 1043 (95% CI: 2.76 × 1012-1.57 × 1074), p = 0.006) were independent predictors of glioma grade. No independent predictor of IDH status was found. Dynamic and texture analyses of 18F-FET PET/CT have limited predictive value for IDH status when adjusted for confounding factors. However, they both help predict glioma grade.

[18F]-fluoroethyl-L-tyrosine (FET) in glioblastoma (FIG) TROG 18.06 study: protocol for a prospective, multicentre PET/CT trial

INTRODUCTION

Glioblastoma is the most common aggressive primary central nervous system cancer in adults characterised by uniformly poor survival. Despite maximal safe resection and postoperative radiotherapy with concurrent and adjuvant temozolomide-based chemotherapy, tumours inevitably recur. Imaging with O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) positron emission tomography (PET) has the potential to impact adjuvant radiotherapy (RT) planning, distinguish between treatment-induced pseudoprogression versus tumour progression as well as prognostication.

METHODS AND ANALYSIS

The FET-PET in Glioblastoma (FIG) study is a prospective, multicentre, non-randomised, phase II study across 10 Australian sites and will enrol up to 210 adults aged ≥18 years with newly diagnosed glioblastoma. FET-PET will be performed at up to three time points: (1) following initial surgery and prior to commencement of chemoradiation (FET-PET1); (2) 4 weeks following concurrent chemoradiation (FET-PET2); and (3) within 14 days of suspected clinical and/or radiological progression on MRI (performed at the time of clinical suspicion of tumour recurrence) (FET-PET3). The co-primary outcomes are: (1) to investigate how FET-PET versus standard MRI impacts RT volume delineation and (2) to determine the accuracy and management impact of FET-PET in distinguishing pseudoprogression from true tumour progression. The secondary outcomes are: (1) to investigate the relationships between FET-PET parameters (including dynamic uptake, tumour to background ratio, metabolic tumour volume) and progression-free survival and overall survival; (2) to assess the change in blood and tissue biomarkers determined by serum assay when comparing FET-PET data acquired prior to chemoradiation with other prognostic markers, looking at the relationships of FET-PET versus MRI-determined site/s of progressive disease post chemotherapy treatment with MRI and FET-PET imaging; and (3) to estimate the health economic impact of incorporating FET-PET into glioblastoma management and in the assessment of post-treatment pseudoprogression or recurrence/true progression. Exploratory outcomes include the correlation of multimodal imaging, blood and tumour biomarker analyses with patterns of failure and survival.

ETHICS AND DISSEMINATION

The study protocol V.2.0 dated 20 November 2020 has been approved by a lead Human Research Ethics Committee (Austin Health, Victoria). Other clinical sites will provide oversight through local governance processes, including obtaining informed consent from suitable participants. The study will be conducted in accordance with the principles of the Declaration of Helsinki and Good Clinical Practice. Results of the FIG study (TROG 18.06) will be disseminated via relevant scientific and consumer forums and peer-reviewed publications.

TRIAL REGISTRATION NUMBER

ANZCTR ACTRN12619001735145.

Hybrid PET/MRI in Cerebral Glioma: Current Status and Perspectives

Advanced MRI methods and PET using radiolabelled amino acids provide valuable information, in addition to conventional MR imaging, for brain tumour diagnostics. These methods are particularly helpful in challenging situations such as the differentiation of malignant processes from benign lesions, the identification of non-enhancing glioma subregions, the differentiation of tumour progression from treatment-related changes, and the early assessment of responses to anticancer therapy. The debate over which of the methods is preferable in which situation is ongoing, and has been addressed in numerous studies. Currently, most radiology and nuclear medicine departments perform these examinations independently of each other, leading to multiple examinations for the patient. The advent of hybrid PET/MRI allowed a convergence of the methods, but to date simultaneous imaging has reached little relevance in clinical neuro-oncology. This is partly due to the limited availability of hybrid PET/MRI scanners, but is also due to the fact that PET is a second-line examination in brain tumours. PET is only required in equivocal situations, and the spatial co-registration of PET examinations of the brain to previous MRI is possible without disadvantage. A key factor for the benefit of PET/MRI in neuro-oncology is a multimodal approach that provides decisive improvements in the diagnostics of brain tumours compared with a single modality. This review focuses on studies investigating the diagnostic value of combined amino acid PET and 'advanced' MRI in patients with cerebral gliomas. Available studies suggest that the combination of amino acid PET and advanced MRI improves grading and the histomolecular characterisation of newly diagnosed tumours. Few data are available concerning the delineation of tumour extent. A clear additive diagnostic value of amino acid PET and advanced MRI can be achieved regarding the differentiation of tumour recurrence from treatment-related changes. Here, the PET-guided evaluation of advanced MR methods seems to be helpful. In summary, there is growing evidence that a multimodal approach can achieve decisive improvements in the diagnostics of cerebral gliomas, for which hybrid PET/MRI offers optimal conditions.

Hybrid 18F-Fluoroethyltyrosine PET and MRI with Perfusion to Distinguish Disease Progression from Treatment-Related Change in Malignant Brain Tumors: The Quest to Beat the Toughest Cases

Conventional MRI has important limitations when assessing for progression of disease (POD) versus treatment-related changes (TRC) in patients with malignant brain tumors. We describe the observed impact and pitfalls of implementing 18F-fluoroethyltyrosine (18F-FET) perfusion PET/MRI into routine clinical practice. Methods: Through expanded-access investigational new drug use of 18F-FET, hybrid 18F-FET perfusion PET/MRI was performed during clinical management of 80 patients with World Health Organization central nervous system grade 3 or 4 gliomas or brain metastases of 6 tissue origins for which the prior brain MRI results were ambiguous. The diagnostic performance with 18F-FET PET/MRI was dually evaluated within routine clinical service and for retrospective parametric evaluation. Various 18F-FET perfusion PET/MRI parameters were assessed, and patients were monitored for at least 6 mo to confirm the diagnosis using pathology, imaging, and clinical progress. Results: Hybrid 18F-FET perfusion PET/MRI had high overall accuracy (86%), sensitivity (86%), and specificity (87%) for difficult diagnostic cases for which conventional MRI accuracy was poor (66%). 18F-FET tumor-to-brain ratio static metrics were highly reliable for distinguishing POD from TRC (area under the curve, 0.90). Dynamic tumor-to-brain intercept was more accurate (85%) than SUV slope (73%) or time to peak (73%). Concordant PET/MRI findings were 89% accurate. When PET and MRI conflicted, 18F-FET PET was correct in 12 of 15 cases (80%), whereas MRI was correct in 3 of 15 cases (20%). Clinical management changed after 88% (36/41) of POD diagnoses, whereas management was maintained after 87% (34/39) of TRC diagnoses. Conclusion: Hybrid 18F-FET PET/MRI positively impacted the routine clinical care of challenging malignant brain tumor cases at a U.S. institution. The results add to a growing body of literature that 18F-FET PET complements MRI, even rescuing MRI when it fails.

Advances in PET imaging of cancer

Molecular imaging has experienced enormous advancements in the areas of imaging technology, imaging probe and contrast development, and data quality, as well as machine learning-based data analysis. Positron emission tomography (PET) and its combination with computed tomography (CT) or magnetic resonance imaging (MRI) as a multimodality PET-CT or PET-MRI system offer a wealth of molecular, functional and morphological data with a single patient scan. Despite the recent technical advances and the availability of dozens of disease-specific contrast and imaging probes, only a few parameters, such as tumour size or the mean tracer uptake, are used for the evaluation of images in clinical practice. Multiparametric in vivo imaging data not only are highly quantitative but also can provide invaluable information about pathophysiology, receptor expression, metabolism, or morphological and functional features of tumours, such as pH, oxygenation or tissue density, as well as pharmacodynamic properties of drugs, to measure drug response with a contrast agent. It can further quantitatively map and spatially resolve the intertumoural and intratumoural heterogeneity, providing insights into tumour vulnerabilities for target-specific therapeutic interventions. Failure to exploit and integrate the full potential of such powerful imaging data may lead to a lost opportunity in which patients do not receive the best possible care. With the desire to implement personalized medicine in the cancer clinic, the full comprehensive diagnostic power of multiplexed imaging should be utilized.

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

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

Early and late contrast enhancing lesions after photon radiotherapy for IDH mutated grade 2 diffuse glioma

OBJECTIVE

The interpretation of new enhancing lesions after radiotherapy for diffuse glioma remains a clinical challenge. We sought to characterize and classify new contrast enhancing lesions in a historical multicenter cohort of patients with IDH mutated grade 2 diffuse glioma treated with photon therapy.

METHODS

We reviewed all follow-up MRI's of all patients treated with radiotherapy for histologically confirmed, IDH mutated diffuse grade 2 glioma between 1-1-2007 and 31-12-2018 in two tertiary referral centers. Disease progression (PD) was defined in accordance with the RANO criteria for progressive disease in low grade glioma. Pseudoprogression (psPD) was defined as any transient contrast-enhancing lesion between the end of radiotherapy and PD, or any new contrast-enhancing lesion that remained stable over a period of 12 months in patients who did not exhibit PD.

RESULTS

A total of 860 MRI's of 106 patients were reviewed. psPD was identified in 24 patients (23%) on 76 MRI's. The cumulative incidence of psPD was 13% at 1 year, 22% at 5 years, and 28% at 10 years. The mean of the observed maximal volume of psPD was 2.4cc. The median Dmin in psPD lesions was 50.1 Gy. The presence of an 1p/19q codeletion was associated with an increased risk of psPD (subhazard ratio 2.34, p=0.048). psPD was asymptomatic in 83% of patients.

CONCLUSION

The cumulative incidence of psPD in grade 2 diffuse glioma increases over time. Consensus regarding event definition and statistical analysis is needed for comparisons between series investigating psPD.

Amino Acid PET in Neurooncology

For decades, several amino acid PET tracers have been used to optimize diagnostics in patients with brain tumors. In clinical routine, the most important clinical indications for amino acid PET in brain tumor patients are differentiation of neoplasm from nonneoplastic etiologies, delineation of tumor extent for further diagnostic and treatment planning (i.e., diagnostic biopsy, resection, or radiotherapy), differentiation of treatment-related changes such as pseudoprogression or radiation necrosis after radiation or chemoradiation from tumor progression at follow-up, and assessment of response to anticancer therapy, including prediction of patient outcome. This continuing education article addresses the diagnostic value of amino acid PET for patients with either glioblastoma or metastatic brain cancer.

Differentiating high-grade glioma progression from treatment-related changes with dynamic [18F]FDOPA PET: a multicentric study

OBJECTIVES

Diagnostic accuracy of amino-acid PET for distinguishing progression from treatment-related changes (TRC) is currently based on single-center non-homogeneous glioma populations. Our study assesses the diagnostic value of static and dynamic [¹⁸F]FDOPA PET acquisitions to differentiate between high-grade glioma (HGG) recurrence and TRC in a large cohort sourced from two independent nuclear medicine centers.

METHODS

We retrospectively identified 106 patients with suspected glioma recurrences (WHO GIII, n = 38; GIV, n = 68; IDH-mutant, n = 35, IDH-wildtype, n = 71). Patients underwent dynamic [¹⁸F]FDOPA PET/CT (n = 83) or PET/MRI (n = 23), and static tumor-to-background ratios (TBRs), metabolic tumor volumes and dynamic parameters (time to peak and slope) were determined. The final diagnosis was either defined by histopathology or a clinical-radiological follow-up at 6 months. Optimal [¹⁸F]FDOPA PET parameter cut-offs were obtained by receiver operating characteristic analysis. Predictive factors and clinical parameters were assessed using univariate and multivariate Cox regression survival analyses.

RESULTS

Surgery or the clinical-radiological 6-month follow-up identified 71 progressions and 35 treatment-related changes. TBR_mean, with a threshold of 1.8, best-differentiated glioma recurrence/progression from post-treatment changes in the whole population (sensitivity 82%, specificity 71%, p < 0.0001) whereas curve slope was only significantly different in IDH-mutant HGGs (n = 25). In survival analyses, MTV was a clinical independent predictor of progression-free and overall survival on the multivariate analysis (p ≤ 0.01). A curve slope > -0.12/h was an independent predictor for longer PFS in IDH-mutant HGGs CONCLUSION: Our multicentric study confirms the high accuracy of [¹⁸F]FDOPA PET to differentiate recurrent malignant gliomas from TRC and emphasizes the diagnostic and prognostic value of dynamic acquisitions for IDH-mutant HGGs.

KEY POINTS

• The diagnostic accuracy of dynamic amino-acid PET, for distinguishing progression from treatment-related changes, is currently based on single-center non-homogeneous glioma populations. • This multicentric study confirms the high accuracy of static [¹⁸F]FDOPA PET images for differentiating progression from treatment-related changes in a homogeneous population of high-grade gliomas and highlights the diagnostic and prognostic value of dynamic acquisitions for IDH-mutant high-grade gliomas. • Dynamic acquisitions should be performed in IDH-mutant glioma patients to provide valuable information for the differential diagnosis of recurrence and treatment-related changes.

Diagnostic value of PET with different radiotracers and MRI for recurrent glioma: a Bayesian network meta-analysis

OBJECTIVE

The purpose of this study was to evaluate the diagnostic accuracy of 6 different imaging modalities for differentiating glioma recurrence from postradiotherapy changes by performing a network meta-analysis (NMA) using direct comparison studies with 2 or more imaging techniques.

DATA SOURCES

PubMed, Scopus, EMBASE, the Web of Science and the Cochrane Library were searched from inception to August 2021. The Confidence In Network Meta-Analysis (CINeMA) tool was used to evaluate the quality of the included studies with the criterion for study inclusion being direct comparison using 2 or more imaging modalities.

DATA EXTRACTION AND SYNTHESIS

The consistency was evaluated by examining the agreement between direct and indirect effects. NMA was performed and the surface under the the cumulative ranking curve (SUCRA) values was obtained to calculate the probability of each imaging modality being the most effective diagnostic method. The CINeMA tool was used to evaluate the quality of the included studies.

MAIN OUTCOMES AND MEASURES

Direct comparison, inconsistency test, NMA and SUCRA values.

RESULTS

A total of 8853 potentially relevant articles were retrieved and 15 articles met the inclusion criteria. 18F-FET showed the highest SUCRA values for sensitivity, specificity, positive predictive value and accuracy, followed by 18F-FDOPA. The quality of the included evidence is classified as moderate.

CONCLUSION AND RELEVANCE

This review indicates that 18F-FET and 18F-FDOPA may have greater diagnostic value for glioma recurrence relative to other imaging modalities (Grading of Recommendations, Assessment, Development and Evaluations B).

PROSPERO REGISTRATION NUMBER

CRD42021293075.

The Role of PET Imaging in the Differential Diagnosis between Radiation Necrosis and Recurrent Disease in Irradiated Adult-Type Diffuse Gliomas: A Systematic Review

Adult-type diffuse gliomas are treated with a multimodality treatment approach that includes radiotherapy both in the primary setting, and in the case of progressive or recurrent disease. Radiation necrosis represents a major complication of radiotherapy. Recurrent disease and treatment-related changes are often indistinguishable using conventional imaging methods. The present systematic review aims at assessing the diagnostic role of PET imaging using different radiopharmaceuticals in differentiating radiation necrosis and disease relapse in irradiated adult-type diffuse gliomas. We conducted a comprehensive literature search using the PubMed/MEDLINE and EMBASE databases for original research studies of interest. In total, 436 articles were assessed for eligibility. Ten original papers, published between 2014 and 2022, were selected. Four articles focused on [¹⁸F]FDG, seven on amino acid tracers ([¹⁸F]FET n = 3 and [¹¹C]MET n = 4), one on [¹¹C]CHO, and one on [⁶⁸Ga]Ga-PSMA. Visual assessment, semi-quantitative methods, and radiomics were applied for image analysis. Furthermore, 2/10 papers were comparative studies investigating different radiopharmaceuticals. The present review, the first one on the topic in light of the new 2021 CNS WHO classification, highlighted the usefulness of PET imaging in distinguishing radiation necrosis and tumour recurrence, but revealed high heterogeneity among studies.

18F-FET-PET imaging in high-grade gliomas and brain metastases: a systematic review and meta-analysis

PURPOSE

To provide a summary of the diagnostic performance of ¹⁸F-FET-PET in the management of patients with high-grade brain gliomas or metastases from extracranial primary malignancies.

METHODS

MEDLINE, EMBASE, and Cochrane Database of Systematic Reviews databases were searched for studies that reported on diagnostic test parameters in radiotherapy planning, response assessment, and tumour recurrence/treatment-related changes differentiation. Radiomic studies were excluded. Quality assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool and the GRADE approach. A bivariate, random-effects model was used to produce summary estimates of sensitivity and specificity.

RESULTS

Twenty-six studies with a total of 1206 patients/lesions were included in the analysis. For radiotherapy planning of glioma, the pooled proportion of patients from 3 studies with ¹⁸F-FET uptake extending beyond the 20 mm margin from the gadolinium enhancement on standard MRI was 39% (95% CI, 10-73%). In 3 studies, ¹⁸F-FET-PET was also shown to be predictive of early responders to treatment, whereas MRI failed to show any prognostic value. For the differentiation of glioma recurrence from treatment-related changes, the pooled sensitivity and specificity of TBR_max 1.9-2.3 from 6 studies were 91% (95% CI, 74-97%) and 84% (95% CI, 69-93%), respectively. The respective values for brain metastases from 4 studies were 82% (95% CI, 74-88%) and 82% (95% CI, 74-88%) using TBR_max 2.15-3.11.

CONCLUSION

While ¹⁸F-FET shows promise as a complementary modality to standard-of-care MRI for the management of primary and metastatic brain malignancies, further validation with standardized image interpretation methods in well-designed prospective studies are warranted.

Challenges and opportunities for advanced neuroimaging of glioblastoma

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

Clinical applications and prospects of PET imaging in patients with IDH-mutant gliomas

PET imaging using radiolabeled amino acids in addition to MRI has become a valuable diagnostic tool in the clinical management of patients with brain tumors. This review provides a comprehensive overview of PET studies in glioma patients with a mutation in the isocitrate dehydrogenase gene (IDH). A considerable fraction of these tumors typically show no contrast enhancement on MRI, especially when classified as grade 2 according to the World Health Organization classification of Central Nervous System tumors. Major diagnostic challenges in this situation are differential diagnosis, target definition for diagnostic biopsies, delineation of glioma extent for treatment planning, differentiation of treatment-related changes from tumor progression, and the evaluation of response to alkylating agents. The main focus of this review is the role of amino acid PET in this setting. Furthermore, in light of clinical trials using IDH inhibitors targeting the mutated IDH enzyme for treating patients with IDH-mutant gliomas, we also aim to give an outlook on PET probes specifically targeting the IDH mutation, which appear potentially helpful for response assessment.

Multiparametric Longitudinal Profiling of RCAS-tva-Induced PDGFB-Driven Experimental Glioma

Glioblastomas are incurable primary brain tumors harboring a heterogeneous landscape of genetic and metabolic alterations. Longitudinal imaging by MRI and [18F]FET-PET measurements enable us to visualize the features of evolving tumors in a dynamic manner. Yet, close-meshed longitudinal imaging time points for characterizing temporal and spatial metabolic alterations during tumor evolution in patients is not feasible because patients usually present with already established tumors. The replication-competent avian sarcoma-leukosis virus (RCAS)/tumor virus receptor-A (tva) system is a powerful preclinical glioma model offering a high grade of spatial and temporal control of somatic gene delivery in vivo. Consequently, here, we aimed at using MRI and [18F]FET-PET to identify typical neuroimaging characteristics of the platelet-derived growth factor B (PDGFB)-driven glioma model using the RCAS-tva system. Our study showed that this preclinical glioma model displays MRI and [18F]FET-PET features that highly resemble the corresponding established human disease, emphasizing the high translational relevance of this experimental model. Furthermore, our investigations unravel exponential growth dynamics and a model-specific tumor microenvironment, as assessed by histology and immunochemistry. Taken together, our study provides further insights into this preclinical model and advocates for the imaging-stratified design of preclinical therapeutic interventions.

Distinguishing Tumor Recurrence From Radiation Necrosis in Treated Glioblastoma Using Multiparametric MRI

PURPOSE

The purpose of this study was to evaluate the diagnostic performance of single-parameter, unimodal and bimodal magnetic resonance imaging (MRI) in differentiating tumor recurrence (TR) from radiation necrosis (RN) in patients with glioblastoma (GBM) after treatment using diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), dynamic susceptibility contrast enhancement-perfusion weighted imaging (DSC-PWI), and proton magnetic resonance spectroscopy (1H-MRS).

MATERIALS AND METHODS

Patients with histologically proven GBM who underwent surgical intervention followed by chemoradiotherapy and developed a new, progressively enhanced lesion on follow-up MRI were included in our study. Subsequently, DWI, DTI, DSC-PWI, and 1H-MRS were performed. Then, these patients underwent a second surgical operation or follow-up MRI to prove TR or RN. MRI metrics include apparent diffusion coefficient (ADC) and relative ADC (rADC) values derived from DWI; fractional anisotropy (FA), axial diffusion coefficient (DA) and radial diffusion coefficient (DR) values derived from DTI; and relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) derived from DSC-PWI. Spectral metabolites such as choline (Cho), creatine (Cr), N-acetylaspartate (NAA), lactate (Lac), and lipids (Lip) were derived from MRS, and the ratios of these metabolites were calculated, including Cho/NAA, Cho/Cr, NAA/Cr, Lac/Cr, and Lip/Cr. These indices were compared between the TR group and RN group, and the receiver operating characteristic (ROC) curve was used to evaluate the performance in distinguishing TR from RN by using single-parameter, unimodal and bimodal MRI.

RESULTS

There were significant differences between the TR and RN groups in terms of ADC (p = 0.001), rADC (p < 0.001), FA (p = 0.001), DA (p = 0.003), DR (p = 0.003), rCBV (p < 0.001), rCBF (p < 0.001), Cho/NAA (p < 0.001), Lac/Cr (p < 0.001) and Lip/Cr (p < 0.001). ROC analysis suggested that rCBV, MRS, and DSC + MRS were the optimal single-parameter, unimodal, and bimodal MRI classifiers for distinguishing TR from RN, with AUC values of 0.909, 0.940, and 0.994, respectively.

CONCLUSION

The combination of parameters based on multiparametric MRI in the region of enhanced lesions is a valuable noninvasive tool for discriminating TR from RN.

DEGRO practical guideline for central nervous system radiation necrosis part 1: classification and a multistep approach for diagnosis

PURPOSE

The Working Group for Neuro-Oncology of the German Society for Radiation Oncology in cooperation with members of the Neuro-Oncology Working Group of the German Cancer Society aimed to define a practical guideline for the diagnosis and treatment of radiation-induced necrosis (RN) of the central nervous system (CNS).

METHODS

Panel members of the DEGRO working group invited experts, participated in a series of conferences, supplemented their clinical experience, performed a literature review, and formulated recommendations for medical treatment of RN including bevacizumab in clinical routine.

CONCLUSION

Diagnosis and treatment of RN requires multidisciplinary structures of care and defined processes. Diagnosis has to be made on an interdisciplinary level with the joint knowledge of a neuroradiologist, radiation oncologist, neurosurgeon, neuropathologist, and neuro-oncologist. A multistep approach as an opportunity to review as many characteristics as possible to improve diagnostic confidence is recommended. Additional information about radiotherapy (RT) techniques is crucial for the diagnosis of RN. Misdiagnosis of untreated and progressive RN can lead to severe neurological deficits. In this practice guideline, we propose a detailed nomenclature of treatment-related changes and a multistep approach for their diagnosis.

Diagnostic yield of simultaneous dynamic contrast-enhanced magnetic resonance perfusion measurements and [18F]FET PET in patients with suspected recurrent anaplastic astrocytoma and glioblastoma

Purpose

Both amino acid positron emission tomography (PET) and magnetic resonance imaging (MRI) blood volume (BV) measurements are used in suspected recurrent high-grade gliomas. We compared the separate and combined diagnostic yield of simultaneously acquired dynamic contrast-enhanced (DCE) perfusion MRI and O-(2-[¹⁸F]-fluoroethyl)-L-tyrosine ([¹⁸F]FET) PET in patients with anaplastic astrocytoma and glioblastoma following standard therapy.

Methods

A total of 76 lesions in 60 hybrid [¹⁸F]FET PET/MRI scans with DCE MRI from patients with suspected recurrence of anaplastic astrocytoma and glioblastoma were included retrospectively. BV was measured from DCE MRI employing a 2-compartment exchange model (2CXM). Diagnostic performances of maximal tumour-to-background [¹⁸F]FET uptake (TBR_max), maximal BV (BV_max) and normalised BV_max (nBV_max) were determined by ROC analysis using 6-month histopathological (n = 28) or clinical/radiographical follow-up (n = 48) as reference. Sensitivity and specificity at optimal cut-offs were determined separately for enhancing and non-enhancing lesions.

Results

In progressive lesions, all BV and [¹⁸F]FET metrics were higher than in non-progressive lesions. ROC analyses showed higher overall ROC AUCs for TBR_max than both BV_max and nBV_max in both lesion-wise (all lesions, p = 0.04) and in patient-wise analysis (p < 0.01). Combining TBR_max with BV metrics did not increase ROC AUC. Lesion-wise positive fraction/sensitivity/specificity at optimal cut-offs were 55%/91%/84% for TBR_max, 45%/77%/84% for BV_max and 59%/84%/72% for nBV_max. Combining TBR_max and best-performing BV cut-offs yielded lesion-wise sensitivity/specificity of 75/97%. The fraction of progressive lesions was 11% in concordant negative lesions, 33% in lesions only BV positive, 64% in lesions only [¹⁸F]FET positive and 97% in concordant positive lesions.

Conclusion

The overall diagnostic accuracy of DCE BV imaging is good, but lower than that of [¹⁸F]FET PET. Adding DCE BV imaging did not improve the overall diagnostic accuracy of [¹⁸F]FET PET, but may improve specificity and allow better lesion-wise risk stratification than [¹⁸F]FET PET alone.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-022-05917-3.

Two Decades of Brain Tumour Imaging with O-(2-[18F]fluoroethyl)-L-tyrosine PET: The Forschungszentrum Jülich Experience

Simple Summary

PET using radiolabelled amino acids has become an essential tool for diagnosing brain tumours in addition to MRI. O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET) is one of the most successful tracers in the field. We analysed our database of 6534 FET PET examinations regarding the diagnostic needs and preferences of the referring physicians for FET PET in the clinical decision-making process. The demand for FET PET increased considerably in the last decade, especially for differentiating tumour progress from treatment-related changes in gliomas. Accordingly, referring physicians rated the diagnostics of recurrent glioma and recurrent brain metastases as the most relevant indication for FET PET. The analysis and survey results confirm the high relevance of FET PET in the clinical diagnosis of brain tumours and support the need for approval for routine use.

Abstract

O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET) is a widely used amino acid tracer for positron emission tomography (PET) imaging of brain tumours. This retrospective study and survey aimed to analyse our extensive database regarding the development of FET PET investigations, indications, and the referring physicians’ rating concerning the role of FET PET in the clinical decision-making process. Between 2006 and 2019, we performed 6534 FET PET scans on 3928 different patients against a backdrop of growing demand for FET PET. In 2019, indications for the use of FET PET were as follows: suspected recurrent glioma (46%), unclear brain lesions (20%), treatment monitoring (19%), and suspected recurrent brain metastasis (13%). The referring physicians were neurosurgeons (60%), neurologists (19%), radiation oncologists (11%), general oncologists (3%), and other physicians (7%). Most patients travelled 50 to 75 km, but 9% travelled more than 200 km. The role of FET PET in decision-making in clinical practice was evaluated by a questionnaire consisting of 30 questions, which was filled out by 23 referring physicians with long experience in FET PET. Fifty to seventy per cent rated FET PET as being important for different aspects of the assessment of newly diagnosed gliomas, including differential diagnosis, delineation of tumour extent for biopsy guidance, and treatment planning such as surgery or radiotherapy, 95% for the diagnosis of recurrent glioma, and 68% for the diagnosis of recurrent brain metastases. Approximately 50% of the referring physicians rated FET PET as necessary for treatment monitoring in patients with glioma or brain metastases. All referring physicians stated that the availability of FET PET is essential and that it should be approved for routine use. Although the present analysis is limited by the fact that only physicians who frequently referred patients for FET PET participated in the survey, the results confirm the high relevance of FET PET in the clinical diagnosis of brain tumours and support the need for its approval for routine use.

Conventional and Advanced Imaging Techniques in Post-treatment Glioma Imaging

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

Glioblastoma Recurrence Versus Radiotherapy Injury: Combined Model of Diffusion Kurtosis Imaging and 11C-MET Using PET/MRI May Increase Accuracy of Differentiation

PURPOSE

To evaluate the diagnostic potential of decision-tree model of diffusion kurtosis imaging (DKI) and 11C-methionine (11C-MET) PET, for the differentiation of radiotherapy (RT) injury from glioblastoma recurrence.

METHODS

Eighty-six glioblastoma cases with suspected lesions after RT were retrospectively enrolled. Based on histopathology or follow-up, 48 patients were diagnosed with local glioblastoma recurrence, and 38 patients had RT injury between April 2014 and December 2019. All the patients underwent PET/MRI examinations. Multiple parameters were derived based on the ratio of tumor to normal control (TNR), including SUVmax and SUVmean, mean value of kurtosis and diffusivity (MK, MD) from DKI, and histogram parameters. The diagnostic models were established by decision trees. Receiver operating characteristic analysis was used for evaluating the diagnostic accuracy of each independent parameter and all the diagnostic models.

RESULTS

The intercluster correlations of DKI, PET, and texture parameters were relatively weak, whereas the intracluster correlations were strong. Compared with models of DKI alone (sensitivity =1.00, specificity = 0.70, area under the curve [AUC] = 0.85) and PET alone (sensitivity = 0.83, specificity = 0.90, AUC = 0.89), the combined model demonstrated the best diagnostic accuracy (sensitivity = 1.00, specificity = 0.90, AUC = 0.95).

CONCLUSIONS

Diffusion kurtosis imaging, 11C-MET PET, and histogram parameters provide complementary information about tissue. The decision-tree model combined with these parameters has the potential to further increase diagnostic accuracy for the discrimination between RT injury and glioblastoma recurrence over the standard Response Assessment in Neuro-Oncology criteria. 11C-MET PET/MRI may thus contribute to the management of glioblastoma patients with suspected lesions after RT.

Congress of Neurological Surgeons systematic review and evidence-based guidelines update on the role of imaging in the management of progressive glioblastoma in adults

TARGET POPULATION

These recommendations apply to adults with glioblastoma who have been previously treated with first-line radiation or chemoradiotherapy and who are suspected of experiencing tumor progression.

QUESTION

In patients with previously treated glioblastoma, is standard contrast-enhanced magnetic resonance imaging including diffusion weighted imaging useful for diagnosing tumor progression and differentiating progression from treatment-related changes?

LEVEL II

Magnetic resonance imaging with and without gadolinium enhancement including diffusion weighted imaging is recommended as the imaging surveillance method to detect the progression of previously diagnosed glioblastoma.

QUESTION

In patients with previously treated glioblastoma, does magnetic resonance spectroscopy add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement?

LEVEL II

Magnetic resonance spectroscopy is recommended as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma.

QUESTION

In patients with previously treated glioblastoma, does magnetic resonance perfusion add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement?

LEVEL III

Magnetic resonance perfusion is suggested as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma.

QUESTION

In patients with previously treated glioblastoma, does the addition of single-photon emission computed tomography (SPECT) provide additional useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement?

LEVEL III

Single-photon emission computed tomography imaging is suggested as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma.

QUESTION

In patients with previously treated glioblastoma, does 18F-fluorodeoxyglucose positron emission tomography add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement?

LEVEL III

The routine use of 18F-fluorodeoxyglucose positron emission tomography to identify progression of glioblastoma is not recommended.

QUESTION

In patients with previously treated glioblastoma, does positron emission tomography with amino acid agents add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement?

LEVEL III

It is suggested that amino acid positron emission tomography be considered to assist in the differentiation of progressive glioblastoma from treatment related changes.

The Utility of Conventional Amino Acid PET Radiotracers in the Evaluation of Glioma Recurrence also in Comparison with MRI

AIM

In this comprehensive review we present an update on the most relevant studies evaluating the utility of amino acid PET radiotracers for the evaluation of glioma recurrence as compared to magnetic resonance imaging (MRI).

METHODS

A literature search extended until June 2020 on the PubMed/MEDLINE literature database was conducted using the terms "high-grade glioma", "glioblastoma", "brain tumors", "positron emission tomography", "PET", "amino acid PET", "[11C]methyl-l-methionine", "[18F]fluoroethyl-tyrosine", "[18F]fluoro-l-dihydroxy-phenylalanine", "MET", "FET", "DOPA", "magnetic resonance imaging", "MRI", "advanced MRI", "magnetic resonance spectroscopy", "perfusion-weighted imaging", "diffusion-weighted imaging", "MRS", "PWI", "DWI", "hybrid PET/MR", "glioma recurrence", "pseudoprogression", "PSP", "treatment-related change", and "radiation necrosis" alone and in combination. Only original articles edited in English and about humans with at least 10 patients were included.

RESULTS

Forty-four articles were finally selected. Conventional amino acid PET tracers were demonstrated to be reliable diagnostic techniques in differentiating tumor recurrence thanks to their high uptake from tumor tissue and low background in normal grey matter, giving additional and early information to standard modalities. Among them, MET-PET seems to present the highest diagnostic value but its use is limited to on-site cyclotron facilities. [18F]labelled amino acids, such as FDOPA and FET, were developed to provide a more suitable PET tracer for routine clinical applications, and demonstrated similar diagnostic performance. When compared to the gold standard MRI, amino acid PET provides complementary and comparable information to standard modalities and seems to represent an essential tool in the differentiation between tumor recurrence and other entities such as pseudoprogression, radiation necrosis, and pseudoresponse.

CONCLUSIONS

Despite the introduction of new advanced imaging techniques, the diagnosis of glioma recurrence remains challenging. In this scenario, the growing knowledge about imaging techniques and analysis, such as the combined PET/MRI and the application of artificial intelligence (AI) and machine learning (ML), could represent promising tools to face this difficult and debated clinical issue.

The diagnostic accuracy of O-(2-18F-fluoroethyl)-L-tyrosine parameters for the differentiation of brain tumour progression from treatment-related changes

BACKGROUND

18F-fluoro-ethyl-tyrosine (18F-FET) is recommended to distinguish brain tumours post-therapeutic true progression (including recurrent and metastatic brain tumours) and treatment-related change (TRC). However, many parameters of 18F-FET can be used for this differential diagnosis. Our purpose was to investigate the diagnostic accuracy of various 18F-FET parameters to differentiate true progression from TRC.

METHODS

We performed a literature search using the following databases: the PubMed, Embase and Web of Science databases up to 29 November 2020. We included studies that reported the diagnostic test results of 18F-FET to distinguish true progression from TRC. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to evaluate the quality of the included studies. The diagnostic accuracy of various parameters was pooled using a random-effects model.

RESULTS

We included 17 eligible studies (nine parameters). For static parameters of 18F-FET, the maximum and mean tumour-to-brain ratios (TBRmax and TBRmean) showed similar pooled sensitivities of 82% [95% confidence interval (CI), 80-85%) and 82% (95% CI, 78-85%), respectively. Among the three kinetic parameters (slope, time to peak and kinetic pattern), the kinetic pattern presented the optimal diagnostic value with a pooled sensitivity of 81% (95% CI, 75-86%). When combining the static and kinetic parameters, the diagnostic performance of 18F-FET was significantly improved, with a pooled sensitivity of 90% (95% CI, 84-94%) in the combination of TBR and kinetic patterns.

CONCLUSIONS

18F-FET static parameters alone showed a comparably high sensitivity in the differentiation between brain tumour true progression and TRC. Combining static and kinetic parameters provided improved diagnostic performance.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics

Objective

To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments.

Methods

The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging).

Results

The biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application.

Conclusion

Advanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Static FET PET radiomics for the differentiation of treatment-related changes from glioma progression

PURPOSE

To investigate the potential of radiomics applied to static clinical PET data using the tracer O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET) to differentiate treatment-related changes (TRC) from tumor progression (TP) in patients with gliomas.

PATIENTS AND METHODS

One hundred fifty-one (151) patients with histologically confirmed gliomas and post-therapeutic progressive MRI findings according to the response assessment in neuro-oncology criteria underwent a dynamic amino acid PET scan using the tracer O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET). Thereof, 124 patients were investigated on a stand-alone PET scanner (data used for model development and validation), and 27 patients on a hybrid PET/MRI scanner (data used for model testing). Mean and maximum tumor to brain ratios (TBR_mean, TBR_max) were calculated using the PET data from 20 to 40 min after tracer injection. Logistic regression models were evaluated for the FET PET parameters TBR_mean, TBR_max, and for radiomics features of the tumor areas as well as combinations thereof to differentiate between TP and TRC. The best performing models in the validation dataset were finally applied to the test dataset. The diagnostic performance was assessed by receiver operating characteristic analysis.

RESULTS

Thirty-seven patients (25%) were diagnosed with TRC, and 114 (75%) with TP. The logistic regression model comprising the conventional FET PET parameters TBR_mean and TBR_max resulted in an AUC of 0.78 in both the validation (sensitivity, 64%; specificity, 80%) and the test dataset (sensitivity, 64%; specificity, 80%). The model combining the conventional FET PET parameters and two radiomics features yielded the best diagnostic performance in the validation dataset (AUC, 0.92; sensitivity, 91%; specificity, 80%) and demonstrated its generalizability in the independent test dataset (AUC, 0.85; sensitivity, 81%; specificity, 70%).

CONCLUSION

The developed radiomics classifier allows the differentiation between TRC and TP in pretreated gliomas based on routinely acquired static FET PET scans with a high diagnostic accuracy.

Relevance of Dynamic 18F-DOPA PET Radiomics for Differentiation of High-Grade Glioma Progression from Treatment-Related Changes

This study evaluates the relevance of ¹⁸F-DOPA PET static and dynamic radiomics for differentiation of high-grade glioma (HGG) progression from treatment-related changes (TRC) by comparing diagnostic performances to the current PET imaging standard of care. Eighty-five patients with histologically confirmed HGG and investigated by dynamic ¹⁸F-FDOPA PET in two institutions were retrospectively selected. ElasticNet logistic regression, Random Forest and XGBoost machine models were trained with different sets of features-radiomics extracted from static tumor-to-background-ratio (TBR) parametric images, radiomics extracted from time-to-peak (TTP) parametric images, as well as combination of both-in order to discriminate glioma progression from TRC at 6 months from the PET scan. Diagnostic performances of the models were compared to a logistic regression model with TBR_mean ± clinical features used as reference. Training was performed on data from the first center, while external validation was performed on data from the second center. Best radiomics models showed only slightly better performances than the reference model (respective AUCs of 0.834 vs. 0.792, p < 0.001). Our current results show similar findings at the multicentric level using different machine learning models and report a marginal additional value for TBR static and TTP dynamic radiomics over the classical analysis based on TBR values.

Diagnostic accuracy of diffusion-weighted imaging in differentiating glioma recurrence from posttreatment-related changes: a meta-analysis

BACKGROUND

Magnetic resonance imaging (MRI) is the most commonly used imaging method to evaluate glioma recurrence. However, conventional MRI has difficulty distinguishing glioma accurately. This study aimed to explore the value of diffusion weighted imaging (DWI) in evaluating glioma recurrence and post-treatment-related changes.

RESEARCH DESIGN AND METHODS

PubMed, Cochrane Library, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Database and China Science and Technology Journal Database were extensively searched in accordance with inclusion criteria and exclusion criteria to obtain appropriate included studies. The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Combined sensitivity and specificity and the area under the summary receiver operating characteristic curve (SROC) with the 95% confidence interval (CI) were calculated.

RESULTS

Seventeen high-quality studies were included. The combined sensitivity was 0.82 (95% CI: 0.76-0.87), the specificity was 0.83 (95% CI: 0.76-0.89), the positive likelihood ratio was 4.9 (95% CI: 3.2-7.5), the negative likelihood ratio was 0.21 (95% CI: 0.15-0.30), the diagnostic odds ratio was 23 (95%: CI 11-48), and the area under the SROC was 0.90 (95% CI: 0.87-0.92).

CONCLUSIONS

This meta-analysis suggests that DWI has high sensitivity, specificity and accuracy in differentiating glioma recurrence.

Clinical Applications of PET/MR Imaging

PET/MR imaging is in routine clinical use and is at least as effective as PET/CT for oncologic and neurologic studies with advantages with certain PET radiopharmaceuticals and applications. In addition, whole body PET/MR imaging substantially reduces radiation dosages compared with PET/CT which is particularly relevant to pediatric and young adult population. For cancer imaging, assessment of hepatic, pelvic, and soft-tissue malignancies may benefit from PET/MR imaging. For neurologic imaging, volumetric brain MR imaging can detect regional volume loss relevant to cognitive impairment and epilepsy. In addition, the single-bed position acquisition enables dynamic brain PET imaging without extending the total study length which has the potential to enhance the diagnostic information from PET.

Impact of 18F-FET PET/MR on clinical management of brain tumor patients

Multiparametric PET/MRI with the amino-acid analog O-(2-¹⁸F-fluoroethyl)-l-tyrosine (¹⁸F-FET) enables the simultaneous assessment of molecular, morphologic, and functional brain tumor characteristics. Although it is considered the most accurate noninvasive approach in brain tumors, its relevance for patient management is still under debate. Here, we report the diagnostic performance of ¹⁸F-FET PET/MRI and its impact on clinical management in a retrospective patient cohort. Methods: We retrospectively analyzed brain tumor patients who underwent ¹⁸F-FET PET/MRI between 2017 and 2018. ¹⁸F-FET PET/MRI examinations were indicated clinically because of equivocal standard imaging results or the clinical course. Histologic confirmation or clinical and standard imaging follow-up served as the reference standard. We evaluated ¹⁸F-FET PET/MRI accuracy in identifying malignancy in untreated suspected lesions (category, new diagnosis) and true progression during adjuvant treatment (category, detection of progression) in a clinical setting. Using multiple regression, we also estimated the contribution of single modalities to produce an optimal PET/MRI outcome. We assessed the recommended and applied therapies before and after ¹⁸F-FET PET/MRI and noted whether the treatment changed on the basis of the ¹⁸F-FET PET/MRI outcome. Results: We included 189 patients in the study. ¹⁸F-FET PET/MRI allowed the identification of malignancy at new diagnosis with an accuracy of 85% and identified true progression with an accuracy of 93%. Contrast enhancement, ¹⁸F-FET PET uptake, and tracer kinetics were the major contributors to an optimal PET/MRI outcome. In the previously equivocal patients, ¹⁸F-FET PET/MRI changed the clinical management in 33% of the untreated lesions and 53% of the cases of tumor progression. Conclusion: Our results suggest that ¹⁸F-FET PET/MRI helps clarify equivocal conditions and profoundly supports the clinical management of brain tumor patients. The optimal modality setting for ¹⁸F-FET PET/MRI and the clinical value of a simultaneous examination need further exploration. At a new diagnosis, multiparametric ¹⁸F-FET PET/MRI might help prevent unnecessary invasive procedures by ruling out malignancy; however, adding static ¹⁸F-FET PET to an already existing MRI examination seems to be of equal value. At detection of progression, multiparametric ¹⁸F-FET PET/MRI may increase therapy effectiveness by distinguishing between tumor progression and therapy-related imaging alterations.

Value of PET imaging for radiation therapy

This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.

Value of PET imaging for radiation therapy

This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.