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.

The impact of brain lesions on health-related quality of life in patients with WHO CNS grade 3 or 4 glioma: a lesion-function and resting-state fMRI analysis.

PURPOSE: In glioma patients, tumor development and multimodality therapy are associated with changes in health-related quality of life (HRQoL). It is largely unknown how different types and locations of tumor- and treatment-related brain lesions, as well as their relationship to white matter tracts and functional brain networks, affect HRQoL. METHODS: In 121 patients with pretreated gliomas of WHO CNS grades 3 or 4, structural MRI, O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET, resting-state functional MRI (rs-fMRI) and self-reported HRQoL questionnaires (EORTC QLQ-C30/BN20) were obtained. Resection cavities, T1-enhancing lesions, T2/FLAIR hyperintensities, and lesions with pathologically increased FET uptake were delineated. Effects of tumor lateralization, involvement of white matter tracts or resting-state network nodes by different types of lesions and within-network rs-fMRI connectivity were analyzed in terms of their interaction with HRQoL scores. RESULTS: Right hemisphere gliomas were associated with significantly less favorable outcomes in physical, role, emotional and social functioning, compared with left-sided tumors. Most functional HRQoL scores correlated significantly with right-sided white-matter tracts involvement by T2/FLAIR hyperintensities and with loss of within-network functional connectivity of right-sided nodes. Tumors of the left hemisphere caused significantly more communication deficits. CONCLUSION: In pretreated high-grade gliomas, right hemisphere lesions are associated with reduced HRQoL scores in most functional domains except communication ability, compared to tumors of the left hemisphere. These relationships are mainly observed for T2/FLAIR lesions involving structural and functional networks in the right hemisphere. The data suggest that sparing the right hemisphere from treatment-related tissue damage may improve HRQoL in glioma patients.

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.

Dynamic susceptibility contrast parametric imaging using accelerated dual-contrast echo planar imaging with keyhole.

BACKGROUND: Echo planar imaging (EPI) is one of the methods of choice in dynamic susceptibility contrast MRI (DSC-MRI) because it provides a sufficient temporal resolution. However, the relatively long readout duration of EPI often imposes limitations on increased spatial coverage or the use of multiple contrasts. PURPOSE: To develop a DSC-MRI method using EPIK (EPI with keyhole) to provide dual-contrast (TE1 and TE2 ) information with a higher spatial coverage than EPI. To compare results from the community-standard EPI method and the proposed EPIK method. STUDY TYPE: Prospective. SUBJECTS: One healthy subject and 17 brain tumor patients. FIELD STRENGTH/SEQUENCE: 3 T/accelerated EPI and dual-contrast EPIK sequences. ASSESSMENT: After an initial evaluation using healthy in vivo images, the use of the proposed method for DSC-MRI was verified with brain tumor patients. The parametric images (eg, CBF and CBV) and arterial input function (AIF), obtained from both the EPI and EPIK, were compared. STATISTICAL TESTS: The ratio of AIF peak height of the proposed method to that of EPI was computed. The ratio computation was also performed for the time-to-peak (TTP) in the AIF curves. From the obtained CBF and CBV maps, the tumor-to-brain (TBR) ratio was also calculated for each imaging method and the results were compared. RESULTS: For the same temporal resolution (1.5 sec), EPIK yielded dual-contrast (TEs of 13/33 msec) with an increased spatial coverage (24 slices) and less geometric distortions than EPI; EPI provided single contrast (TE of 32 msec) with 20 slices. The obtained parametric values (eg, AIF peak, TTP, and TBR) had similar characteristics between EPI and the proposed method. DATA CONCLUSION: The dual-contrast data produced by EPIK in DSC-MRI allowed T1 -corrected parametric images without the need of second contrast injection and an enhanced estimation of the AIF. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:628-640.

Prostate-specific membrane antigen radioligand therapy of prostate cancer.

Defining an optimal therapeutic approach in metastatic castration-resistance prostate cancer (mCRPC) patients in advanced stages is still challenging in routine clinical practice. Prostate-specific membrane antigen (PSMA) targeted radionuclide therapy with ß- or α-emitters such as 177-Lutethium (177Lu) or 225-Actinium (225A) has been a main focus at multiple academic research centers in the last few years. This review article provides an overview of PSMA characteristics, clinical performance, safety and toxicity of PSMA targeted ß- or α-radiation therapy.

Imaging of amino acid transport in brain tumours: Positron emission tomography with O-(2-[18F]fluoroethyl)-L-tyrosine (FET).

The assessment of cerebral gliomas using magnetic resonance imaging (MRI) provides excellent structural images but cannot solve all diagnostic problems satisfactorily. The differentiation of tumour tissue from non-neoplastic changes may be difficult especially in the post-treatment phase. In recent years, positron emission tomography (PET) using radiolabelled amino acids has gained considerable interest as an additional tool to improve the diagnosis of cerebral gliomas and brain metastases. A key step for this advancement was the development of the F-18 labelled amino acid O-(2-[18F]fluoroethyl)-L-tyrosine (FET) which has spread rapidly in the last decade and replaced carbon-11 labelled amino acid tracers such as 11C-methyl-L-methionine (MET) in many centres in Europe. FET can be produced with high efficiency and distributed in a satellite concept like 2-[18F]fluoro-2-deoxy-D-glucose (FDG). Furthermore, FET exhibits favourable properties such as high in vivo stability, high tumour to background contrast and tissue specific tracer kinetics, which provides additional information for tumour grading or differential diagnosis. The Response Assessment in Neuro-Oncology (RANO) working group - an international effort to develop new standardized response criteria for clinical trials in brain tumours - has recently recommended the additional use of amino acid PET imaging for brain tumour management. FET PET can provide important diagnostic information in crucial situations such as the definition of biopsy site, the delineation of cerebral gliomas for therapy planning, sensitive monitoring of treatment response and an improved differentiation of tumour recurrence from treatment-related changes. In this article the basic information, methodological aspects and the actual status of clinical application of FET PET are reviewed.

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.

Influence of blood-brain barrier permeability on O-(2-18F-fluoroethyl)-L-tyrosine uptake in rat gliomas.

PURPOSE: O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET) is an established tracer for the diagnosis of brain tumors with PET. This study investigates the influence of blood-brain barrier (BBB) permeability on 18F-FET uptake in two rat glioma models and one human xenograft model. METHODS: F98 glioma, 9L gliosarcoma or human U87 glioblastoma cells were implanted into the striatum of 56 Fischer or RNU rats. Thereafter, animals were divided into a control group and a group receiving injections of the glucocorticoid dexamethasone (Dex). After 12-13 days of tumor growth animals received injection of Evans blue dye (EBD) to visualize BBB disturbance and underwent 18F-FET PET followed by autoradiography. Time activity curves, standardized uptake values (SUV) and Tumor-to-brain ratios (TBR) of 18F-FET uptake [18-61 min post injection (p.i.)] were evaluated using a volume-of-Interest (VOI) analysis. BBB disturbance was quantitatively evaluated by EBD fluorescence. The membrane gaps of blood vessel endothelial tight junctions were measured using electron microscopy to visualize ultrastructural BBB alterations in one untreated and one Dex treated F98 glioma. Data were analyzed by two-way ANOVAs. RESULTS: In Dex treated animals EBD extravasation was significantly reduced in 9L (P < 0.001) and U87 (P = 0.008) models and showed a trend in F98 models (P = 0.053). In contrast, no significant differences of 18F-FET uptake were observed between Dex treated animals and control group except a decrease of the TBR in the 9L tumor model in PET (P < 0.01). Ultrastructural evaluation of tumor blood vessel endothelia revealed significant reduction of the cleft diameter between endothelial cells after Dex treatment in F98 model (P = 0.010). CONCLUSION: Despite a considerable reduction of BBB permeability in rat gliomas after Dex treatment, no relevant changes of 18F-FET uptake were noted in this experimental study. Thus, 18F-FET uptake in gliomas appears to be widely independent of the permeability of the BBB.

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.

Reproducibility of O-(2-(18)F-fluoroethyl)-L-tyrosine uptake kinetics in brain tumors and influence of corticoid therapy: an experimental study in rat gliomas.

PURPOSE: Positron emission tomography (PET) using O-(2-(18)F-fluoroethyl)-L-tyrosine ((18)F-FET) is a well-established method for the diagnostics of brain tumors. This study investigates reproducibility of (18)F-FET uptake kinetics in rat gliomas and the influence of the frequently used dexamethasone (Dex) therapy. METHODS: F98 glioma or 9L gliosarcoma cells were implanted into the striatum of 31 Fischer rats. After 10-11 days of tumor growth, the animals underwent dynamic PET after injection of (18)F-FET (baseline). Thereafter, animals were divided into a control group and a group receiving Dex injections, and all animals were reinvestigated 2 days later. Tumor-to-brain ratios (TBR) of (18)F-FET uptake (18-61 min p.i.) and the slope of the time-activity-curves (TAC) (18-61 min p.i.) were evaluated using a Volume-of-Interest (VOI) analysis. Data were analyzed by two-way repeated measures ANOVA and reproducibility by the intraclass correlation coefficient (ICC). RESULTS: The slope of the tumor TACs showed high reproducibility with an ICC of 0.93. A systematic increase of the TBR in the repeated scans was noted (3.7 ± 2.8 %; p < 0.01), and appeared to be related to tumor growth as indicated by a significant correlation of TBR and tumor volume (r = 0.77; p < 0.0001). After correction for tumor growth TBR showed high longitudinal stability with an ICC of 0.84. Dex treatment induced a significant decrease of the TBR (-8.2 ± 6.1 %; p < 0.03), but did not influence the slope of the tumor TAC. CONCLUSION: TBR of (18)F-FET uptake and tracer kinetics in brain tumors showed high longitudinal stability. Dex therapy may induce a minor decrease of the TBR; this needs further investigation.

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.

Uptake and tracer kinetics of O-(2-(18)F-fluoroethyl)-L-tyrosine in meningiomas: preliminary results.

PURPOSE: O-(2-[(18)F]Fluoroethyl)-L-tyrosine ((18)F-FET) is a well-established PET tracer for the imaging of cerebral gliomas, but little is known about (18)F-FET uptake in meningiomas. The aim of this study was to explore (18)F-FET kinetics and tumour-to-background contrast in meningiomas of various histologies. METHODS: A group of 24 patients with suspected cerebral meningioma on MRI/CT had an additional dynamic (18)F-FET PET scan prior to surgery. Time-activity curves (TAC) of (18)F-FET uptake in the tumours and tumour-to-brain ratios (TBR) for early (3 - 14 min after injection) and late (18)F-FET uptake (20 - 40 min after injection) were analysed and compared with histological subtypes and WHO grade. (18)F-FET uptake in critical structures in the skull base was also evaluated in terms of tumour-to-tissue (T/Tis) ratio. RESULTS: TBR of (18)F-FET uptake in meningiomas was significantly higher in the early phase than in the late phase (3.5 ± 0.8 vs. 2.2 ± 0.3; P < 0.001). The difference in TBR between low-grade meningiomas (WHO grade I, 18 patients) and high-grade meningiomas (WHO grade II or III, 6 patients) was significant in the late phase of (18)F-FET uptake (2.1 ± 0.2 vs. 2.5 ± 0.2, P = 0.003) while there was no significant difference in the early phase. ROC analysis showed that TBR of (18)F-FET uptake in the late phase had significant power to differentiate low-grade from high-grade meningiomas (AUC 0.87 ± 0.18, sensitivity 83 %, specificity 83 %, optimal cut-off 2.3; P < 0.01). Evaluation of TAC yielded three different curve patterns of (18)F-FET PET uptake. Combination of TBR (cut-off value 2.3) and TAC pattern slightly improved the differentiation of high-grade from low-grade meningiomas (accuracy 92 %; P = 0.001). Analysis of background radioactivity in the skull base indicated that (18)F-FET uptake may be helpful in distinguishing meningioma tissue in the late phase. T/Tis ratios were >1.2 in all patients for the periorbita, sphenoidal sinus, pituitary gland, tentorium, bone and brain, in more than 90 % of patients for the mucosa and dura, but in only 63 % of patients for the cavernous sinus. CONCLUSION: (18)F-FET PET may provide additional information for noninvasive grading of meningiomas and possibly for the discrimination of tumour in critical areas of the skull base. A further evaluation of (18)F-FET PET in meningiomas appears to be justified.

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

OBJECTIVE: We aimed to evaluate the diagnostic potential of dual-time-point imaging with positron emission tomography (PET) using O-(2-[(18)F]fluoroethyl)-L-tyrosine ((18)F-FET) for non-invasive grading of cerebral gliomas compared with a dynamic approach. METHODS: Thirty-six patients with histologically confirmed cerebral gliomas (21 primary, 15 recurrent; 24 high-grade, 12 low-grade) underwent dynamic PET from 0 to 50 min post-injection (p.i.) of (18)F-FET, and additionally from 70 to 90 min p.i. Mean tumour-to-brain ratios (TBRmean) of (18)F-FET uptake were determined in early (20-40 min p.i.) and late (70-90 min p.i.) examinations. Time-activity curves (TAC) of the tumours from 0 to 50 min after injection were assigned to different patterns. The diagnostic accuracy of changes of (18)F-FET uptake between early and late examinations for tumour grading was compared to that of curve pattern analysis from 0 to 50 min p.i. of (18)F-FET. RESULTS: The diagnostic accuracy of changes of the TBRmean of (18)F-FET PET uptake between early and late examinations for the identification of HGG was 81% (sensitivity 83%; specificity 75%; cutoff - 8%; p < 0.001), and 83% for curve pattern analysis (sensitivity 88%; specificity 75%; p < 0.001). CONCLUSION: Dual-time-point imaging of (18)F-FET uptake in gliomas achieves diagnostic accuracy for tumour grading that is similar to the more time-consuming dynamic data acquisition protocol. KEY POINTS: • Dual-time-point imaging is equivalent to dynamic FET PET for grading of gliomas. • Dual-time-point imaging is less time consuming than dynamic FET PET. • Costs can be reduced due to higher patient throughput. • Reduced imaging time increases patient comfort and sedation might be avoided. • Quicker image interpretation is possible, as no curve evaluation is necessary.

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.

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.

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.