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.

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 (TBRmean, TBRmax) were calculated using the PET data from 20 to 40 min after tracer injection. Logistic regression models were evaluated for the FET PET parameters TBRmean, TBRmax, 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 TBRmean and TBRmax 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.

Radiomics in neuro-oncology: Basics, workflow, and applications.

Over the last years, the amount, variety, and complexity of neuroimaging data acquired in patients with brain tumors for routine clinical purposes and the resulting number of imaging parameters have substantially increased. Consequently, a timely and cost-effective evaluation of imaging data is hardly feasible without the support of methods from the field of artificial intelligence (AI). AI can facilitate and shorten various time-consuming steps in the image processing workflow, e.g., tumor segmentation, thereby optimizing productivity. Besides, the automated and computer-based analysis of imaging data may help to increase data comparability as it is independent of the experience level of the evaluating clinician. Importantly, AI offers the potential to extract new features from the routinely acquired neuroimages of brain tumor patients. In combination with patient data such as survival, molecular markers, or genomics, mathematical models can be generated that allow, for example, the prediction of treatment response or prognosis, as well as the noninvasive assessment of molecular markers. The subdiscipline of AI dealing with the computation, identification, and extraction of image features, as well as the generation of prognostic or predictive mathematical models, is termed radiomics. This review article summarizes the basics, the current workflow, and methods used in radiomics with a focus on feature-based radiomics in neuro-oncology and provides selected examples of its clinical application.

Sequential implementation of DSC-MR perfusion and dynamic [18F]FET PET allows efficient differentiation of glioma progression from treatment-related changes.

PURPOSE: Perfusion-weighted MRI (PWI) and O-(2-[18F]fluoroethyl-)-l-tyrosine ([18F]FET) PET are both applied to discriminate tumor progression (TP) from treatment-related changes (TRC) in patients with suspected recurrent glioma. While the combination of both methods has been reported to improve the diagnostic accuracy, the performance of a sequential implementation has not been further investigated. Therefore, we retrospectively analyzed the diagnostic value of consecutive PWI and [18F]FET PET. METHODS: We evaluated 104 patients with WHO grade II-IV glioma and suspected TP on conventional MRI using PWI and dynamic [18F]FET PET. Leakage corrected maximum relative cerebral blood volumes (rCBVmax) were obtained from dynamic susceptibility contrast PWI. Furthermore, we calculated static (i.e., maximum tumor to brain ratios; TBRmax) and dynamic [18F]FET PET parameters (i.e., Slope). Definitive diagnoses were based on histopathology (n = 42) or clinico-radiological follow-up (n = 62). The diagnostic performance of PWI and [18F]FET PET parameters to differentiate TP from TRC was evaluated by analyzing receiver operating characteristic and area under the curve (AUC). RESULTS: Across all patients, the differentiation of TP from TRC using rCBVmax or [18F]FET PET parameters was moderate (AUC = 0.69-0.75; p < 0.01). A rCBVmax cutoff > 2.85 had a positive predictive value for TP of 100%, enabling a correct TP diagnosis in 44 patients. In the remaining 60 patients, combined static and dynamic [18F]FET PET parameters (TBRmax, Slope) correctly discriminated TP and TRC in a significant 78% of patients, increasing the overall accuracy to 87%. A subgroup analysis of isocitrate dehydrogenase (IDH) mutant tumors indicated a superior performance of PWI to [18F]FET PET (AUC = 0.8/< 0.62, p < 0.01/≥ 0.3). CONCLUSION: While marked hyperperfusion on PWI indicated TP, [18F]FET PET proved beneficial to discriminate TP from TRC when PWI remained inconclusive. Thus, our results highlight the clinical value of sequential use of PWI and [18F]FET PET, allowing an economical use of diagnostic methods. The impact of an IDH mutation needs further investigation.

Putaminal y-Aminobutyric Acid Modulates Motor Response to Dopaminergic Therapy in Parkinson's Disease.

BACKGROUND: Motor response to dopaminergic therapy is a characteristic of patients with Parkinson's disease (PD). Whether nondopaminergic neurotransmitters contribute to treatment response is uncertain. OBJECTIVES: The aim of this study is to determine whether putaminal y-aminobutyric acid (GABA) levels are associated with dopaminergic motor response. METHODS: We assessed putaminal GABA levels in 19 PD patients and 13 healthy controls (HCs) utilizing ultra-high field proton magnetic resonance spectroscopy. Motor performance was evaluated using the Movement Disorder Society-Unified Parkinson's Disease Rating Scale, Part III, in the ON and OFF states. Statistical analysis comprised group comparisons, correlation analysis, and multiple linear regression. RESULTS: In PD, GABA levels were significantly higher compared to HCs (1.50 ± 0.26 mM vs. 1.26 ± 0.31 mM, P = 0.022). Furthermore, GABA levels were independent predictors of absolute and relative dopaminergic treatment response. CONCLUSIONS: Our findings indicate that elevated putaminal GABA levels are associated with worse dopaminergic response in PD, emphasizing the essential role of nondopaminergic neurotransmitters in motor response. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

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 (TBRmax/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, TBRmax, TBRmean, 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.

Comparison of 18F-FET PET and perfusion-weighted MRI for glioma grading: a hybrid PET/MR study.

PURPOSE: Both perfusion-weighted MR imaging (PWI) and O-(2-18F-fluoroethyl)-L-tyrosine PET (18F-FET) provide grading information in cerebral gliomas. The aim of this study was to compare the diagnostic value of 18F-FET PET and PWI for tumor grading in a series of patients with newly diagnosed, untreated gliomas using an integrated PET/MR scanner. METHODS: Seventy-two patients with untreated gliomas [22 low-grade gliomas (LGG), and 50 high-grade gliomas (HGG)] were investigated with 18F-FET PET and PWI using a hybrid PET/MR scanner. After visual inspection of PET and PWI maps (rCBV, rCBF, MTT), volumes of interest (VOIs) with a diameter of 16 mm were centered upon the maximum of abnormality in the tumor area in each modality and the contralateral unaffected hemisphere. Mean and maximum tumor-to-brain ratios (TBRmean, TBRmax) were calculated. In addition, Time-to-Peak (TTP) and slopes of time-activity curves were calculated for 18F-FET PET. Diagnostic accuracies of 18F-FET PET and PWI for differentiating low-grade glioma (LGG) from high-grade glioma (HGG) were evaluated by receiver operating characteristic analyses (area under the curve; AUC). RESULTS: The diagnostic accuracy of 18F-FET PET and PWI to discriminate LGG from HGG was similar with highest AUC values for TBRmean and TBRmax of 18F-FET PET uptake (0.80, 0.83) and for TBRmean and TBRmax of rCBV (0.80, 0.81). In case of increased signal in the tumor area with both methods (n = 32), local hot-spots were incongruent in 25 patients (78%) with a mean distance of 10.6 ± 9.5 mm. Dynamic FET PET and combination of different parameters did not further improve diagnostic accuracy. CONCLUSIONS: Both 18F-FET PET and PWI discriminate LGG from HGG with similar diagnostic performance. Regional abnormalities in the tumor area are usually not congruent indicating that tumor grading by 18F-FET PET and PWI is based on different pathophysiological phenomena.

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 TBRmean alone to 85 % when combined with the textural parameter Coarseness or Short-zone emphasis. The accuracy of TBRmax 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 TBRmax. 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.

Volumetric assessment of recurrent or progressive gliomas: comparison between F-DOPA PET and perfusion-weighted MRI.

PURPOSE: To compare the diagnostic information obtained with 6-[(18)F]-fluoro-L-3,4-dihydroxyphenylalanine (F-DOPA) PET and relative cerebral blood volume (rCBV) maps in recurrent or progressive glioma. METHODS: All patients with recurrent or progressive glioma referred for F-DOPA imaging at our institution between May 2010 and May 2014 were retrospectively included, provided that macroscopic disease was visible on conventional MRI images and that rCBV maps were available for comparison. The final analysis included 50 paired studies (44 patients). After image registration, automatic tumour segmentation of both sets of images was performed using the average signal in a large reference VOI including grey and white matter multiplied by 1.6. Tumour volumes identified by both modalities were compared and their spatial congruence calculated. The distances between F-DOPA uptake and rCBV hot spots, tumour-to-brain ratios (TBRs) and normalized histograms were also computed. RESULTS: On visual inspection, 49 of the 50 F-DOPA and 45 of the 50 rCBV studies were classified as positive. The tumour volume delineated using F-DOPA (F-DOPAvol 1.6) greatly exceeded that of rCBV maps (rCBVvol 1.6). The median F-DOPAvol 1.6 and rCBVvol 1.6 were 11.44 ml (range 0 - 220.95 ml) and 1.04 ml (range 0 - 26.30 ml), respectively (p < 0.00001). Overall, the median overlapping volume was 0.27 ml, resulting in a spatial congruence of 1.38 % (range 0 - 39.22 %). The mean hot spot distance was 27.17 mm (±16.92 mm). F-DOPA uptake TBR was significantly higher than rCBV TBR (1.76 ± 0.60 vs. 1.15 ± 0.52, respectively; p < 0.0001). The histogram analysis showed that F-DOPA provided better separation of tumour from background. In 6 of the 50 studies (12 %), however, physiological uptake in the striatum interfered with tumour delineation. CONCLUSION: The information provided by F-DOPA PET and rCBV maps are substantially different. Image interpretation is easier and a larger tumour extent is identified on F-DOPA PET images than on rCBV maps. The clinical impact of such differences needs to be explored in future studies.

Structural connectome-based predictive modeling of cognitive deficits in treated glioma patients.

Background: In glioma patients, tumor growth and subsequent treatments are associated with various types of brain lesions. We hypothesized that cognitive functioning in these patients critically depends on the maintained structural connectivity of multiple brain networks. Methods: The study included 121 glioma patients (median age, 52 years; median Eastern Cooperative Oncology Group performance score 1; CNS-WHO Grade 3 or 4) after multimodal therapy. Cognitive performance was assessed by 10 tests in 5 cognitive domains at a median of 14 months after treatment initiation. Hybrid amino acid PET/MRI using the tracer O-(2-[18F]fluoroethyl)-L-tyrosine, a network-based cortical parcellation, and advanced tractography were used to generate whole-brain fiber count-weighted connectivity matrices. The matrices were applied to a cross-validated machine-learning model to identify predictive fiber connections (edges), critical cortical regions (nodes), and the networks underlying cognitive performance. Results: Compared to healthy controls (n = 121), patients' cognitive scores were significantly lower in 9 cognitive tests. The models predicted the scores of 7/10 tests (median correlation coefficient, 0.47; range, 0.39-0.57) from 0.6% to 5.4% of the matrix entries; 84% of the predictive edges were between nodes of different networks. Critically involved cortical regions (≥10 adjacent edges) included predominantly left-sided nodes of the visual, somatomotor, dorsal/ventral attention, and default mode networks. Highly critical nodes (≥15 edges) included the default mode network's left temporal and bilateral posterior cingulate cortex. Conclusions: These results suggest that the cognitive performance of pretreated glioma patients is strongly related to structural connectivity between multiple brain networks and depends on the integrity of known network hubs also involved in other neurological disorders.

Glutamate Signaling in Patients With Parkinson Disease With REM Sleep Behavior Disorder.

BACKGROUND AND OBJECTIVES: Clinical heterogeneity of patients with Parkinson disease (PD) is well recognized. PD with REM sleep behavior disorder (RBD) is a more malignant phenotype with faster motor progression and higher nonmotor symptom burden. However, the neural mechanisms underlying this clinical divergence concerning imbalances in neurotransmitter systems remain elusive. METHODS: Combining magnetic resonance (MR) spectroscopy and [11C]ABP688 PET on a PET/MR hybrid system, we simultaneously investigated two different mechanisms of glutamate signaling in patients with PD. Patients were grouped according to their RBD status in overnight video-polysomnography and compared with age-matched and sex-matched healthy control (HC) participants. Total volumes of distribution (VT) of [11C]ABP688 were estimated with metabolite-corrected plasma concentrations during steady-state conditions between 45 and 60 minutes of the scan following a bolus-infusion protocol. Glutamate, glutamine, and glutathione levels were investigated with single-voxel stimulated echo acquisition mode MR spectroscopy of the left basal ganglia. RESULTS: We measured globally elevated VT of [11C]ABP688 in 16 patients with PD and RBD compared with 17 patients without RBD and 15 HC participants (F(2,45) = 5.579, p = 0.007). Conversely, glutamatergic metabolites did not differ between groups and did not correlate with the regional VT of [11C]ABP688. VT of [11C]ABP688 correlated with the amount of REM sleep without atonia (F(1,42) = 5.600, p = 0.023) and with dopaminergic treatment response in patients with PD (F(1,30) = 5.823, p = 0.022). DISCUSSION: Our results suggest that patients with PD and RBD exhibit altered glutamatergic signaling indicated by higher VT of [11C]ABP688 despite unaffected glutamate levels. The imbalance of glutamate receptors and MR spectroscopy glutamate metabolite levels indicates a novel mechanism contributing to the heterogeneity of PD and warrants further investigation of drugs targeting mGluR5.

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.

Diagnostic Accuracy of MR Spectroscopic Imaging and 18F-FET PET for Identifying Glioma: A Biopsy-Controlled Hybrid PET/MRI Study.

Contrast-enhanced MRI is the method of choice for brain tumor diagnostics, despite its low specificity for tumor tissue. This study compared the contribution of MR spectroscopic imaging (MRSI) and amino acid PET to improve the detection of tumor tissue. Methods: In 30 untreated patients with suspected glioma, O-(2-[18F]fluoroethyl)-l-tyrosine (18F-FET) PET; 3-T MRSI with a short echo time; and fluid-attenuated inversion recovery, T2-weighted, and contrast-enhanced T1-weighted MRI were performed for stereotactic biopsy planning. Serial samples were taken along the needle trajectory, and their masks were projected to the preoperative imaging data. Each sample was individually evaluated neuropathologically. 18F-FET uptake and the MRSI signals choline (Cho), N-acetyl-aspartate (NAA), creatine, myoinositol, and derived ratios were evaluated for each sample and classified using logistic regression. The diagnostic accuracy was evaluated by receiver operating characteristic analysis. Results: On the basis of the neuropathologic evaluation of tissue from 88 stereotactic biopsies, supplemented with 18F-FET PET and MRSI metrics from 20 areas on the healthy-appearing contralateral hemisphere to balance the glioma/nonglioma groups, 18F-FET PET identified glioma with the highest accuracy (area under the receiver operating characteristic curve, 0.89; 95% CI, 0.81-0.93; threshold, 1.4 × background uptake). Among the MR spectroscopic metabolites, Cho/NAA normalized to normal brain tissue showed the highest diagnostic accuracy (area under the receiver operating characteristic curve, 0.81; 95% CI, 0.71-0.88; threshold, 2.2). The combination of 18F-FET PET and normalized Cho/NAA did not improve the diagnostic performance. Conclusion: MRI-based delineation of gliomas should preferably be supplemented by 18F-FET PET.

Alterations in white matter fiber density associated with structural MRI and metabolic PET lesions following multimodal therapy in glioma patients.

Background: In glioma patients, multimodality therapy and recurrent tumor can lead to structural brain tissue damage characterized by pathologic findings in MR and PET imaging. However, little is known about the impact of different types of damage on the fiber architecture of the affected white matter. Patients and methods: This study included 121 pretreated patients (median age, 52 years; ECOG performance score, 0 in 48%, 1-2 in 51%) with histomolecularly characterized glioma (WHO grade IV glioblastoma, n=81; WHO grade III anaplastic astrocytoma, n=28; WHO grade III anaplastic oligodendroglioma, n=12), who had a resection, radiotherapy, alkylating chemotherapy, or combinations thereof. After a median follow-up time of 14 months (range, 1-214 months), anatomic MR and O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET images were acquired on a 3T hybrid PET/MR scanner. Post-therapeutic findings comprised resection cavities, regions with contrast enhancement or increased FET uptake and T2/FLAIR hyperintensities. Local fiber density was determined from high angular-resolution diffusion-weighted imaging and advanced tractography methods. A cohort of 121 healthy subjects selected from the 1000BRAINS study matched for age, gender and education served as a control group. Results: Lesion types differed in both affected tissue volumes and relative fiber densities compared to control values (resection cavities: median volume 20.9 mL, fiber density 16% of controls; contrast-enhanced lesions: 7.9 mL, 43%; FET uptake areas: 30.3 mL, 49%; T2/FLAIR hyperintensities: 53.4 mL, 57%, p<0.001). In T2/FLAIR-hyperintense lesions caused by peritumoral edema due to recurrent glioma (n=27), relative fiber density was as low as in lesions associated with radiation-induced gliosis (n=13, 48% vs. 53%, p=0.17). In regions with pathologically increased FET uptake, local fiber density was inversely related (p=0.005) to the extent of uptake. Total fiber loss associated with contrast-enhanced lesions (p=0.006) and T2/FLAIR hyperintense lesions (p=0.013) had a significant impact on overall ECOG score. Conclusions: These results suggest that apart from resection cavities, reduction in local fiber density is greatest in contrast-enhancing recurrent tumors, but total fiber loss induced by edema or gliosis has an equal detrimental effect on the patients' performance status due to the larger volume affected.

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

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.

Effect of Zolpidem in the Aftermath of Traumatic Brain Injury: An MEG Study.

In the past two decades, many studies have shown the paradoxical efficacy of zolpidem, a hypnotic used to induce sleep, in transiently alleviating various disorders of consciousness such as traumatic brain injury (TBI), dystonia, and Parkinson's disease. The mechanism of action of this effect of zolpidem is of great research interest. In this case study, we use magnetoencephalography (MEG) to investigate a fully conscious, ex-coma patient who suffered from neurological difficulties for a few years due to traumatic brain injury. For a few years after injury, the patient was under medication with zolpidem that drastically improved his symptoms. MEG recordings taken before and after zolpidem showed a reduction in power in the theta-alpha (4-12 Hz) and lower beta (15-20 Hz) frequency bands. An increase in power after zolpidem intake was found in the higher beta/lower gamma (20-43 Hz) frequency band. Source level functional connectivity measured using weighted-phase lag index showed changes after zolpidem intake. Stronger connectivity between left frontal and temporal brain regions was observed. We report that zolpidem induces a change in MEG resting power and functional connectivity in the patient. MEG is an informative and sensitive tool to detect changes in brain activity for TBI.

18F-FET PET Imaging in Differentiating Glioma Progression from Treatment-Related Changes: A Single-Center Experience.

In glioma patients, differentiation between tumor progression (TP) and treatment-related changes (TRCs) remains challenging. Difficulties in classifying imaging alterations may result in a delay or an unnecessary discontinuation of treatment. PET using O-(2-18F-fluoroethyl)-l-tyrosine (18F-FET) has been shown to be a useful tool for detecting TP and TRCs. Methods: We retrospectively evaluated 127 consecutive patients with World Health Organization grade II-IV glioma who underwent 18F-FET PET imaging to distinguish between TP and TRCs. 18F-FET PET findings were verified by neuropathology (40 patients) or clinicoradiologic follow-up (87 patients). Maximum tumor-to-brain ratios (TBRmax) of 18F-FET uptake and the slope of the time-activity curves (20-50 min after injection) were determined. The diagnostic accuracy of 18F-FET PET parameters was evaluated by receiver-operating-characteristic analysis and χ2 testing. The prognostic value of 18F-FET PET was estimated using the Kaplan-Meier method. Results: TP was diagnosed in 94 patients (74%) and TRCs in 33 (26%). For differentiating TP from TRCs, receiver-operating-characteristic analysis yielded an optimal 18F-FET TBRmax cutoff of 1.95 (sensitivity, 70%; specificity, 71%; accuracy, 70%; area under the curve, 0.75 ± 0.05). The highest accuracy was achieved by a combination of TBRmax and slope (sensitivity, 86%; specificity, 67%; accuracy, 81%). However, accuracy was poorer when tumors harbored isocitrate dehydrogenase (IDH) mutations (91% in IDH-wild-type tumors, 67% in IDH-mutant tumors, P < 0.001). 18F-FET PET results correlated with overall survival (P < 0.001). Conclusion: In our neurooncology department, the diagnostic performance of 18F-FET PET was convincing but slightly inferior to that of previous reports.

Flare Phenomenon in O-(2-18F-Fluoroethyl)-l-Tyrosine PET After Resection of Gliomas.

PET using O-(2-18F-fluoroethyl)-l-tyrosine (18F-FET) is useful to detect residual tumor tissue after glioma resection. Recent animal experiments detected reactive changes in 18F-FET uptake at the rim of the resection cavity within the first 2 wk after resection of gliomas. In the present study, we evaluated pre- and postoperative 18F-FET PET scans of glioma patients with particular emphasis on the identification of reactive changes after surgery. Methods: Forty-three patients with cerebral gliomas (9 low-grade, 34 high-grade; 9 primary tumors, 34 recurrent tumors) who had preoperative (time before surgery: median, 23 d; range, 6-44 d) and postoperative 18F-FET PET (time after surgery: median, 14 d; range, 5-28 d) were included. PET scans (20-40 min after injection) were evaluated visually for complete or incomplete resection and compared with MRI. Changes in 18F-FET uptake were evaluated by tumor-to-brain ratios in residual tumor and by maximum lesion-to-brain ratios near the resection cavity. Results: Visual analysis of 18F-FET PET scans revealed complete resection in 16 of 43 patients and incomplete resection in the remaining patients. PET results were concordant with MRI in 69% of the patients. The maximum lesion-to-brain ratio for 18F-FET uptake near the resection cavity was significantly higher than preoperative values (1.59 ± 0.36 vs. 1.14 ± 0.17; n = 43; P < 0.001). In 11 patients (26%), a flare phenomenon was observed, with a considerable increase in 18F-FET uptake compared with preoperative values in either the residual tumor (n = 5) or areas remote from the tumor on the preoperative PET scan (n = 6) (2.92 ± 1.24 vs. 1.62 ± 0.75; P < 0.001). Further follow-up in 5 patients showed decreasing 18F-FET uptake in the flare areas in 4 patients and progress in 1 patient. Conclusion: Our study confirmed that 18F-FET PET provides valuable information for assessing the success of glioma resection. Postoperative reactive changes at the rim of the resection cavity appear to be mild. However, in 23% of the patients, a postoperative flare phenomenon was observed that warrants further investigation.

Comparison of O-(2-18F-Fluoroethyl)-L-Tyrosine Positron Emission Tomography and Perfusion-Weighted Magnetic Resonance Imaging in the Diagnosis of Patients with Progressive and Recurrent Glioma: A Hybrid Positron Emission Tomography/Magnetic Resonance Study.

OBJECTIVE: To compare the diagnostic performance of O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET) positron emission tomography (PET) and perfusion-weighted magnetic resonance imaging (PWI) for the diagnosis of progressive or recurrent glioma. METHODS: Thirty-two pretreated gliomas (25 progressive or recurrent tumors, 7 treatment-related changes) were investigated with 18F-FET PET and PWI via a hybrid PET/magnetic resonance scanner. Volumes of interest with a diameter of 16 mm were centered on the maximum of abnormality in the tumor area in PET and PWI maps (relative cerebral blood volume, relative cerebral blood flow, mean transit time) and the contralateral unaffected hemisphere. Mean and maximum tumor-to-brain ratios as well as dynamic data for 18F-FET uptake were calculated. Diagnostic accuracies were evaluated by receiver operating characteristic analyses, calculating the area under the curve. RESULTS: 18F-FET PET showed a significant greater sensitivity to detect abnormalities in pretreated gliomas than PWI (76% vs. 52%, P = 0.03). The maximum tumor-to-brain ratio of 18F-FET PET was the only parameter that discriminated treatment-related changes from progressive or recurrent gliomas (area under the curve, 0.78; P = 0.03, best cut-off 2.61; sensitivity 80%, specificity 86%, accuracy 81%). Among patients with signal abnormality in both modalities, 75% revealed spatially incongruent local hot spots. CONCLUSIONS: This pilot study suggests that 18F-FET PET is superior to PWI to diagnose progressive or recurrent glioma.

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.