Register or Submit a manuscript.
Quick Link
OBM Neurobiology

(ISSN 2573-4407)

OBM Neurobiology is an international peer-reviewed Open Access journal published quarterly online by LIDSEN Publishing Inc. By design, the scope of OBM Neurobiology is broad, so as to reflect the multidisciplinary nature of the field of Neurobiology that interfaces biology with the fundamental and clinical neurosciences. As such, OBM Neurobiology embraces rigorous multidisciplinary investigations into the form and function of neurons and glia that make up the nervous system, either individually or in ensemble, in health or disease. OBM Neurobiology welcomes original contributions that employ a combination of molecular, cellular, systems and behavioral approaches to report novel neuroanatomical, neuropharmacological, neurophysiological and neurobehavioral findings related to the following aspects of the nervous system: Signal Transduction and Neurotransmission; Neural Circuits and Systems Neurobiology; Nervous System Development and Aging; Neurobiology of Nervous System Diseases (e.g., Developmental Brain Disorders; Neurodegenerative Disorders).

OBM Neurobiology publishes a variety of article types (Original Research, Review, Communication, Opinion, Comment, Conference Report, Technical Note, Book Review, etc.). Although the OBM Neurobiology Editorial Board encourages authors to be succinct, there is no restriction on the length of the papers. Authors should present their results in as much detail as possible, as reviewers are encouraged to emphasize scientific rigor and reproducibility.

Publication Speed (median values for papers published in 2023): Submission to First Decision: 7.5 weeks; Submission to Acceptance: 15.9 weeks; Acceptance to Publication: 7 days (1-2 days of FREE language polishing included)

Current Issue: 2024  Archive: 2023 2022 2021 2020 2019 2018 2017
Open Access Review

Contribution of PET Imaging to Clinical Management of Gliomas

Wolf-Dieter Heiss *

  1. Max Planck Institute for Metabolism Research, Gleueler Str. 50, D-50931, Cologne, Germany

*   Correspondence: Wolf-Dieter Heiss

Received: July 2, 2018 | Accepted: September 5, 2018 | Published: September 20, 2018

OBM Neurobiology 2018, Volume 2, Issue 3, doi:10.21926/obm.neurobiol.1803011

Academic Editors: Antonio Meola

Special Issue: Tumors of the Central Nervous System

Recommended citation: Heiss WD. Contribution of PET Imaging to Clinical Management of Gliomas. OBM Neurobiology 2018; 2(3): 011; doi:10.21926/obm.neurobiol.1803011.

© 2018 by the authors. This is an open access article distributed under the conditions of the Creative Commons by Attribution License, which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is correctly cited.

Abstract

Gliomas originating from glial cells comprise about 30% of all primary central nervous system tumors and 80% of malignant brain tumors. Gliomas differ in their biological activity and are categorized according to grades, from benign to malignant with high recurrence rates. For diagnosis, location and extent of the tumor is assessed by CT and MRI, but for grading, additional parameters are necessary: contrast enhanced CT and MRI reveal damage of the blood–brain barrier, perfusion-weighted MRI shows regional blood supply, and MR spectroscopy permits insight into regional metabolism. Positron emission tomography (PET) of glucose metabolism as well as amino acid and nucleoside uptake can assess tumor grade and invasive growth, indicate effects on function of tissues outside of the tumor, demonstrate treatment efficacy, detect recurrences, and yield prognostic information.

Coregistration of PET and MRI combines high-resolution morphological information with biological information. This imaging technology is optimized in hybrid MRI/PET by which morphologic, functional, metabolic, and molecular information is assessed simultaneously in the human brain.

Keywords

Gliomas; tumor recurrence; morphologic imaging; functional imaging; molecular imaging; PET

1. Introduction

Gliomas are the most frequently occurring primary tumors affecting the central nervous system (accounting for 29%), with an incidence of 20.5 per 100,000 people each year. Within this group, 54% are malignant gliomas with an incidence of 6.6 per 100,000 [1]. Survival rates are dependent on the grade of gliomas: 35.7% at 1 year and 4%–7% at 5 years for glioblastoma, 60%–80% at 1 year and 26%–46% at 5 years for astrocytomas and oligodendrogliomas of WHO grade III, and 94% at 1 year and 67% at 5 years for astrocytomas and oligodendrogliomas of WHO grade II [2]. Patients with malignant tumors have an average survival of 15–20 months despite surgical resection followed by radiotherapy and chemotherapy [3]. Imaging plays an integral and decisive role in the grading of gliomas, therapeutic management, and in the development of new treatment strategies. Furthermore, multimodal and molecular imaging may have an especially significant role in detecting and defining new targets for research [4,5,6].

Morphological imaging by CT and especially MRI detects the location of brain tumors and is improved by contrast enhancement, due to damage of the blood–brain barrier. MR spectroscopy may provide additional information on the tissue, including the presence or level of malignancy. Information detected by MRI is limited since brain tumor tissue may extend into tissue outside the areas affected by a blood–brain barrier disruption. After radiation therapy, a blood–brain barrier disruption may persist in non-tumorous tissue. MR spectroscopy is unreliable in certain areas, specifically close to the skull or the ventricles. Nuclear medicine procedures can detect physiological and metabolic changes in the involved brain tissue [7,8]]. Notably, positron emission tomography (PET) can quantify tumor metabolism, proliferation rate, and invasiveness and demonstrate the effects on functional networks as well as monitor changes after therapy [9,10,11,12].

In this review, which is an update of a previously published paper [13], clinically relevant results studying glucose metabolism, amino acid uptake, and cell proliferation with PET tracers are summarized. Other tracers specifically applied for research topics [4,14] are not discussed.

Energy for the brain is nearly exclusively supplied by glucose. For the measurement of the cerebral metabolic rate of glucose, 18F-labeled deoxy-d-glucose (FDG) is used, which becomes phosphorylated to FDG-phosphate and accumulates in proportion to local metabolism. Regional quantitative metabolic rates of glucose (rCMRGlc) are determined from the tissue activity measured by PET and the arterial input function [15].

Amino acid uptake in gliomas is increased due to altered overexpressed L-type amino acid carriers [16,17]. This tracer indicates the different metabolic activities in the tumor cell. Amino acid uptake in gliomas is higher than in white matter, and also often higher than in the normal cortex. The most frequently used amino acid for tumor brain imaging with PET is (methyl-11C)-L-methionine (MET) [18,19], but this tracer suffers from a short half-life of 11C. Amino acids labeled with 18F-fluorine as O-(2-[18F] fluoroethyl)-L-tyrosine (FET) and 3, 4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (FDOPA) showed comparable results to MET. However, since FET is not further metabolized it can only reflect transport in tissue. FDOPA is a substrate for the enzyme aromatic amino acid decarboxylase in dopaminergic neurons, which is responsible for FDOPA uptake by the basal ganglia and might therefore interfere with tumor delineation. On the other hand, MET is incorporated into proteins, used for methylation, and is needed for DNA translation.

As nucleosides are involved in cellular proliferation, they can indicate histologic grade 3'-deoxy-3'-[18F] fluorothymidine (FLT) accumulation correlates with activity of thymidine kinase-1, which is expressed during the DNA synthesis phase [20]; this makes it a suitable tracer of tumor proliferation [21]. Accumulation of FLT depends on blood-brain barrier (BBB) permeability, and high FLT uptake is found in tumors with impaired BBB; therefore, FLT is not useful in low grade gliomas with intact BBB [22,23,24].

PET studies during functional activation show the effect of tumors on brain tissue outside the tumor and on eloquent areas. Blood flow tracers such as 15O-water are frequently used for this purpose, but functional changes can be also recorded by FDG. Accurate anatomic localization can be achieved by coregistration and fusion with MRI [25]. However, perfusion MRI is the method used most in the clinical setting for demonstration of functional activation.

2. Diagnosis, Grading and Prognosis

The World Health Organization (WHO) classification of gliomas distinguishes four grades of gliomas: I and II are benign; grade III is anaplastic; and grade IV, glioblastoma multiforme, is the most malignant with the worst prognosis [26]. The WHO classification of gliomas has been updated recently [27], combining molecular parameters such as the IDH mutation and 1p/19q co-deletion with histology, which defines five subgroups. However, since nearly all imaging studies were done on the basis of the previous classification, the prior classification was used in this review for the description of imaging data. Gliomas are frequently heterogeneous [28] and therefore, histologic grading may not be representative for further prognosis/development. Anatomic imaging is still the first step in diagnosis, but it does not yield all the information on tumor pathology essential for individualized treatment. PET can supplement conventional CT and MRI information on tumor grading, necrosis, proliferative activity, and vasculature.

3. Glucose Metabolism

The first PET study in oncology [29] already showed increased glucose consumption in brain tumors and the effect of radiation necrosis, especially in malignant gliomas. FDG uptake levels in low-grade tumors is the same as in white matter, and uptake in high-grade tumors can be in the range of that of normal gray matter. Regions with low and high uptake can be near each other in a single tumor. This variability must be taken into account when tumors are graded. Usually, uptake ratios of tumor to white matter greater than 1.5 or of tumor to gray matter greater than 0.6 are used for distinction of benign tumors (grades I and II) from malignant tumors (grades III and IV) (Figure 1) [30]. Additionally, delayed PET after injection may help to distinguish tumors from normal gray matter [31].

 

Figure 1 Typical patterns of glucose (FDG) uptake in gliomas of different grades: Astrocytoma WHO grade 2 shows low uptake in relation to gray matter and can hardly be differentiated (a), in malignant gliomas (grade 3 (b) and grade 4 / glioblastoma (c)) glucose uptake is significantly increased and above the level of gray matter; in the glioblastome (c) a central necrosis (reduced FDG uptake) is visible.

In a primary glioma, FDG uptake correlates with histologic tumor grade [32], cell density [33], and survival [34]. Additionally, metabolism in normal brain tissue is impaired and the reduction is related to prognosis [35]. FDG-PET is therefore of value in patient management [36]. Necrotic compartments in glioblastoma often cause heterogeneous FDG uptake. In pilocytic astrocytoma with metabolically active fenestrated endothelial cells, uptake can be rather high, but prognosis is good. The similarity of FDG uptake in tumors to that in the cortex and the partial-volume averaging by PET limit the detection of small gliomas. This limitation can be overcome by coregistration with MRI. Coregistered MRI/FDG-PET can help in the selection of the most metabolically active tumor part for stereotactic biopsy [37]. Other malignant tumors in the brain, especially medulloblastomas, often show high FDG uptake [38,39]. It should be considered that the Response Assessment in Neuro-Oncology (RANO) guidelines emphasize superiority of amino acid PET over FDG–PET [40]. Therefore, the use of FDG for brain tumor imaging has been widely abandoned in PET centers with access to radiolabeled amino acids.

4. Amino Acid Uptake

Uptake of MET in gliomas is 1.2 to 6.0 times above that in normal tissue and correlates to cell proliferation, Ki-67 expression, nuclear antigen expression, microvessel density, and angiogenesis [41]. MET-PET has a sensitivity of 76% and a specificity of 87% for the diagnosis of brain tumors [42]. Due to the low uptake in normal brain tissue and the accumulation despite the unimpaired blood–brain barrier, amino acid tracers are especially suited for detection of low-grade tumors (Figure 2). Even tumors not visible on FDG-PET can be detected with MET [43]. Amino acid uptake was correlated to histological tumor grade in high- and low-grade gliomas [44]. Additionally, the invasion of malignant cells into the surrounding brain could reliably be distinguished by MET-PET [45], demonstrating the importance of integrating this technique into radiation therapy planning [46]. In some gliomas, MET-PET is superior to contrast-enhanced MRI [47]. MET-PET can help determine prognosis in gliomas and is superior than FDG-PET and MRI in predicting survival in low-grade gliomas [48]. Recent reviews have summarized the value of MET-PET for imaging of gliomas [4,49,50,51].

 

Figure 2 (11C)-MET-PET in low and high grade gliomas: uptake of (11C)-MET is increased in relationship to grade in astrocytoma and glioblastoma as well as in oligodendrocytoma.

MET uptake differs with tumor type: in oligodendrogliomas, uptake tends to be higher than in astrocytomas of the same histological grade, although they are less aggressive [52]. In oligodendrogliomas, 11C-choline PET may be useful in evaluating the potential malignancy, but MET-PET is superior in detecting “hot lesions” [53]. MET uptake is increased in other malignant intracranial tumors, but also in benign neoplasias, such as meningiomas (for review see [38]).

The disadvantage of MET is the short half-life of 11C (20 min). Therefore, 18F-labeled aromatic amino acid analogs O-(2-[18F] fluoroethyl)-L-tyrosine (FET) and [18F]-fluoro-dihydroxy-phenylalanine (FDOPA)) with similar brain uptake as MET were introduced for tumor imaging [18,19,54,55,56]. Uptake of FET is related to grade and prognosis [57,58]; specifically, the volume of increased FET uptake correlated to survival of patients with glioblastoma [59]. Despite significant differences between high- and low-grade gliomas, sensitivity and specificity for detection were 87% and 68%, respectively [60]. As with MET, coregistration with MRI [61] and combination with MRS [62] improves diagnostic accuracy: high FET accumulation was related to neuronal cell loss indicated by MRS [63]. The early phase of FET uptake appears to be most informative for grading [64,65] and prognosis [66]; tracer accumulation is slow in low-grade gliomas, for which late scans provide the best contrast [67]. The FET uptake kinetic analysis independently predicted overall and progression-free survival [68]. Dynamic FET studies with inclusion of early and late scans therefore improved differentiation and grading performance [69,70,71,72]. Kinetic analysis of dynamic FET uptake parameters is of special prognostic value in diffuse low-grade gliomas [51].

FDOPA was more sensitive and specific than FDG for differentiating high- and low-grade tumors, and uptake was related to proliferation [73]. FDOPA studies have demonstrated association with tumor grade [74], progression-free survival [75], and overall survival in recurrent tumors [76,77]. High uptake (an SUV of more than 1.75) was a predictor of progression in low-grade gliomas [78]. A direct comparison of FDOPA and FET in high-grade gliomas revealed no significant difference in patterns, but uptake ratios were 10-15% higher for FET than for FDOPA [79].

5. Nucleoside Uptake

Imaging of nucleoside uptake adds another dimension to the assessment of the biological activity of tumors, specifically in regards to cellular proliferation (Figure 3)[80]. The tracer FLT achieves high tumor to normal tissue ratios of grade III and IV gliomas [81], which was not observed in grade II gliomas. FLT uptake was correlated to Ki-67 expression [82]. For preoperative tumor grading, FLT -PET was superior to MRI and MRS for differentiation between grades III and IV [83]. FLT-PET was superior to MET-PET in tumor grading and assessment of proliferation in some gliomas; notably, the combination with MET-PET added significant information [84]. A direct comparison in primary and recurrent low-grade gliomas showed low FLT uptake (SUV = 1.8) but high uptake of FDOPA (SUV = 5.75) and FDG (SUV = 8.5), and tumor to normal tissue ratios of 2.3 ± 0.5 for FDOPA, 1.8 ± 0.9 for FLT, and 1.0 ± 0.6 for FDG, confirming the value of FDOPA for evaluation of low grade gliomas [85]. In high-grade gliomas, FLT-PET predicted overall survival of patients [86].

 

Figure 3 Comparison of Gd-Ti-MRI, FDG-, MET- and FLT-PET in glioblastoma: disruption of blood brain barrier and peritumorous edema visible on MRI, increase of glucose turnover in tumor and reduction in surrounding tissue, increased MET-uptake in tumor core, infiltration detected by FLT-PET.

6. Effects on Surrounding and Remote Brain Areas

The rim of reduced metabolism in normal tissue around malignant tumors might be partly due to edema and infiltrating tumor tissues [87]. Additionally, function of the non-tumorous brain is affected: cortical centers are displaced and functional activations are reduced or occur at atypical locations, even in contralateral areas which indicate reorganization of functional networks; the knowledge of these altered networks is important for planning tailored surgery. In the motoric network, activation of secondary motor areas and of the motor cortex ipsilateral to the paretic limbs has been observed [88]. Functional MRI is the most important procedure to determine functional anatomy in patients with gliomas [6].

In patients with brain tumors in the dominant hemisphere, a considerable reorganization of the language-related network is observed [89], dependent on the speed of the development of the brain lesion: a verb generation paradigm analysis showed increased activation area beyond the primary language regions to the left frontal medial gyrus, the orbital inferior frontal gyrus, the anterior insula, and the left cerebellum (Figure 4), as well as the contralateral functional network. Successful resection of a left frontotemporal tumor improved aphasia and restored left hemisphere dominance, suggesting a reversible disinhibition by removal of the primary functional damage. The hierarchy of the functional network for recovery in an individual patient as shown in these examples should be taken into account in tailored surgery.

 

Figure 4 Activation of H215O PET by verb generation coregistered to MRI. Primary speech centers are affected by the tumor, temporal Wernicke center and frontal Broca center are shifted and language activation pattern is shifted to the right hemisphere.

7. Monitoring Treatment Effects

PET studies can follow the efficiency of therapy in brain tumors [90]. Via FDG-PET, reduction of the tumor is visible after only a few weeks of radiation and chemotherapy [91], and recurrence is indicated by progressive hypermetabolic regions [92]. The early assessment of therapy efficacy by PET can help to optimize therapy of gliomas: FDG accumulation was measured before and after 14 days of temozolomide chemotherapy and tumor response after 8 weeks was analyzed [91]. Pre-treatment FDG uptake was higher in responders than non-responders, and responders showed a greater than 25% reduction of metabolic rate in tumor regions after 8 weeks [91]. FDG-PET also predicted response to temozolomide (TMZ) versus TMZ plus radiotherapy (RT) in recurrent malignant glioma [93]. Changes in tumor glucose metabolism were observed also with everolimus or rapamycin in combination with RT and TMZ [93,94]. However, hypermetabolism is sometimes mimicked by the infiltration of macrophages, especially after radiotherapy. This disadvantage makes FDG-PET not the optimal method for the evaluation of treatment [95].

Amino acid and nucleoside tracers do not possess this disadvantage and several studies indicated that patients can benefit from treatment studies based on MET- or FET-PET [96,97,98,99,100]. Differentiation of recurrent tumors and necrosis is detected by MET-PET with high sensitivity and specificity (∼75%), and progression was detected early (Figure. 5) [101,102,103,104]. In many patients, information supplied by MET-PET affected further treatment management [105].

The changes observed by amino acid PET [106,107,108,109] indicate deactivation of amino acid transport as an early sign of response to chemotherapy. FET-PET was more efficient (sensitivity 80%, specificity close to 100%) [110] than MRI in showing effects of multimodal treatment [111,112] Early changes of FET uptake of > 10% after postoperative radiochemotherapy predicted a significantly longer disease-free and overall survival in patients with glioblastomas [113]. Similar results were obtained with FET- and FDOPA-PET [114,115]. FET-PET was also useful to assess pseudoprogression in glioblastomas [116] and could also demonstrate treatment effects in recurrent tumors [115,117,118,119,120,121].

 

Figure 5 Decrease of 11C-Methionin uptake in PET demonstrated response to chemotherapy with favorable prognosis.

FLT-PET was successful in the prediction of the prognosis of responders and non-responders to a combination therapy and also in predicting survival. An SUV decrease of more than 25% or less than 25% distinguished responders and non-responders, respectively [122]. Additionally, the responders survived 3 times as long as non-responders. Notably, the kinetics of FLT uptake are closely related to prognosis, early efficacy of treatment, and outcome [123,124,125,126], and can serve as early surrogate markers of longtime survival.

These results indicate that coregistration of various PET and MRI modalities are useful for evaluating new treatments, e.g. targeting proliferating cells[127], angiogenesis [114], or applying gene therapy vectors [128].

FET-PET was also useful to assess pseudoprogression in glioblastomas [116] and could also elucidate treatment effects in recurrent tumors [115,117,118,119,120]. Antiangiogenic treatment with bevacizumab causes a rapid decrease in T1 contrast-enhancing tumor parts, which suggests radiographic response rates are related to pseudonormalization of abnormal blood-brain barrier permeability [129]; the distinction between anti-vascular and true antitumor effects by MRI criteria is difficult, therefore, the RANO criteria were developed [130]. On the other hand, transiently-increased permeability of the vasculature may be a consequence from irradiation and can be enhanced by temozolomide [131]. Pseudoprogression as well as pseudoresponses after therapy can be differentiated from actual tumor response by FET-PET [70,132].

With FLT-PET, a distinction between responders and non-responders to a combination therapy was possible: FLT-PET at 2 and 6 weeks predicted survival better than MRI [122]. FLT uptake investigated at different time points in the course of treatment was able to differentiate between responders and non- responders by a SUV decrease of more than 25% or less than 25%, respectively, and the responders survived 3 times as long as non-responders [122]. As shown by several groups [123,124,125,126], the kinetics of FLT uptake are closely related to prognosis, early efficacy of treatment, and outcome. These therapeutic effects may be related to neovascularization by bevacizumab and/or permeability changes by chemotherapy [123,133] and can serve as early surrogate markers of longtime survival [11]. Similar results were obtained with FDOPA-PET [134].

Multimodal imaging, including various PET and MRI modalities, will have a great impact on the development of new therapeutic strategies, such as targeting proliferating cells [127], angiogenesis [114], or applying gene therapy vectors [128].

8. Residual Tumors, Recurrences and Necrosis

The capacity of PET to identify tumor compartments that differ in activity is especially important for the detection of residual or recurrent tumors after resection, and for differentiation between treatment-induced changes (such as necrosis) and active proliferating tissue. After tumor resection, normal postsurgical changes do not show increased FDG uptake. Therefore, a hypermetabolic activity after surgery is highly suspect of residual tumor, and FDG-PET can be performed within a few days after surgery [92]. While normalization of glucose metabolism in the surrounding area of the resected tumor might be related to edema  and increased intracranial pressure, a newly detected hypermetabolism weeks after therapy indicates a recurrent tumor and progression from low-grade to high-grade glioma [37,92,135,136]. One of the most important applications of PET tracers after treatment of gliomas is the differentiation between radiation-induced changes, like necrosis, or recurrent or residual tumors after radiation therapy [29,137]. Generally, the question, “Tumor or necrosis?” is an oversimplification as in most cases both tumor and necrotic tissue can be found next to each other in patients or may even overlap [138]. Sensitivity of FDG-PET was 75% at a specificity of 81% for the detection of recurrent tumor versus radiation necrosis [17,139]. However, there is a specific overlap in FDG-uptake in recurrent tumor and radiation necrosis [138] (review in [140]). Stereotactic biopsy based on FDG-PET improves the detection of tumor tissue when compared to anatomical imaging alone [37]. A disadvantage of FDG-PET is that accumulation of FDG may occur from macrophages that potentially infiltrate the sites having received radiation therapy [91,141]. Therefore, radiation necrosis may be indistinguishable from a recurrent tumor.

Necrosis and gliosis after therapy show a reduction of amino acid uptake in contrast to uptake in recurrent or residual tumor growth. Therefore, MET-PET successfully differentiates between recurrent tumor growth and radiation necrosis with the detection of a recurrent tumor at a high sensitivity and high specificity (Figure 6). Again, MET-PET is more sensitive than FDG-PET for differentiation between recurrent tumor and radiation necrosis (Figure 7) [102,104,142] and provided high accuracy [143], despite its limitations in tumor grading [144], and is especially effective in combination with MRI [145,146]. Even in brain lesions that did not show increased uptake in FDG-PET, a sensitivity between 89% (tumors) and 92% (gliomas) with a specificity of 100% was obtained [43] (for detailed review see [147]). A recent systematic review and meta-analysis [148] demonstrated that FET-PET has good sensitivity (82%) and average specificity (76%) for diagnosis of brain tumors; it allows discrimination between infection and tumoral lesions and also between tumor recurrence and radionecrosis [149]. MET-PET and FET-PET differentiated tumor tissue and treatment-related changes with a sensitivity of 91% and a specificity of 100%. In adequately equipped centers, amino acid PET is the method of choice for differentiation between necrosis and progressive disease [40]. Fusion of FDOPA-PET with MRI provides precise anatomic localization of tracer uptake [150], and FDOPA-PET better identifies large tumor volumes than perfusion-weighted MRI [151]. FDOPA-PET is also superior to FDG-PET in detection of recurrences [152] and is able to differentiate glioma recurrence from treatment-related changes.

FLT-PET had a moderately better overall accuracy for diagnosing glioma recurrence than FDG-PET [153,154]. The FLT influx rate differentiated recurrence from radionecrosis, but the SUV did not [155]. For monitoring treatment effects and the differentiation between necrosis and recurrence, multimodal imaging is most effective [12].

 

Figure 6 Differentiation between recurrent tumor and radiation necrosis by FDG-PET.

Figure 7 Uptake of glucose (FDG) and methionin (MET) in the course of a patient with glioblastoma: After tumor resection and radiation therapy the uptake of FDG and METis initially reduced; MET-PET indicates the recurrency long before it can be proven by FDG-PET.

9. The Future: Hybrid PET/MRI Systems

Coregistration of PET and MRI data requires positioning the patient in different scanners, often under different conditions and at different times. Hybrid PET/MRI systems combine high-resolution MRI (including spectroscopy, functional MRI, diffusion- and perfusion-weighted imaging) with the molecular, biochemical, and functional imaging properties of PET. In contrast to PET/CT data acquisition, a hybrid PET/MRI system analyzes simultaneously due to PET detectors [156] in the MRI gantry. After the feasibility of simultaneous PET/MRI recording was shown [157], dedicated brain PET/MRI scanners tested some promising applications [158]. In the first clinical studies, the hybrid system demonstrated simultaneous high-resolution structural, functional, and molecular imaging in tumor patients [159].

BesideIn addition to the time-saving benefits and patient management advantages, hybrid MRI/PET improves the presurgical diagnosis of patients with focal epilepsy, where small lesions, hypoplasias, or heterotopies can be delineated [160,161]. As previously stated, hybrid MRI/PET has great advantages in the differential diagnosis of brain tumors, grading of gliomas, assessment of progression, and the distinction between necrosis and recurrence of tumors [162,163,164,165,166]. Additionally, it is an important tool for the selection of sites for biopsies and in the evaluation of treatment effects [160,167,168,169,170,171,172,173,174,175,176]. Adding diffusion tensor imaging/fiber tracking, fMRI, PWI, MRS, and activation-PET to multimodal imaging can enhance the assessment of a tumor on the functional networks in the brain [177,178,179,180,181] and show anaerobic changes as well as the effect on efferent and connecting fiber tracts and on task-related activation patterns.

Author Contributions

The author has completed all the work.

Funding

Supported by the WDH Foundation within the Max Planck Society.

Competing Interests

The author has declared that no competing interests exist.

References

  1. Dolecek TA, Propp JM, Stroup NE, Kruchko C. CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2005–2009. Neuro Oncol. 2012; 14: v1-v49. [CrossRef]
  2. Yang P, Wang Y, Peng X, You G, Zhang W, Yan W, et al. Management and survival rates in patients with glioma in China (2004–2010): a retrospective study from a single-institution. J Neuro Oncol. 2013; 113: 259-266. [CrossRef]
  3. Weller M, Van Den Bent M, Tonn JC, Stupp R, Preusser M, Cohen-Jonathan-Moyal E, et al. European Association for Neuro-Oncology (EANO) guideline on the diagnosis and treatment of adult astrocytic and oligodendroglial gliomas. Lancet Oncol. 2017; 18: e315-e329. [CrossRef]
  4. Herholz K. Brain tumors: an update on clinical PET research in gliomas. Semin Nucl Med. 2017; 47: 5-17. [CrossRef]
  5. Galldiks N. Neuroimaging in patients with high-grade gliomas. Q J Nucl Med Mol Imaging. 2018. [CrossRef]
  6. Volz L, Kocher M, Lohmann P, Shah N, Fink G, Galldiks N. Functional magnetic resonance imaging in glioma patients: from clinical applications to future perspectives. Q J Nucl Med Mol Imaging. 2018. [CrossRef]
  7. Schillaci O, Filippi L, Manni C, Santoni R. Single-photon emission computed tomography/computed tomography in brain tumors. Semin Nucl Med. 2007; 37: 34-47. [CrossRef]
  8. Spence AM, Mankoff DA, Muzi M. Positron emission tomography imaging of brain tumors. Neuroimaging Clin. 2003; 13: 717-739. [CrossRef]
  9. Heiss W-D, Raab P, Lanfermann H. Multimodality assessment of brain tumors and tumor recurrence.J Nucl Med. 2011; 52: 1585. [CrossRef]
  10. Herholz K, Langen K-J, Schiepers C, Mountz JM. Brain tumors. Semin Nucl Med. 2012; 42: 356-370. [CrossRef]
  11. Albert NL, Weller M, Suchorska B, Galldiks N, Soffietti R, Kim MM, et al. Response Assessment in Neuro-Oncology working group and European Association for Neuro-Oncology recommendations for the clinical use of PET imaging in gliomas. Neuro Oncol. 2016; 18: 1199-1208. [CrossRef]
  12. Assimakopoulos A, Polyzoidis K, Sioka C. Positron emission tomography imaging in gliomas. Neuroimmunol Neuroinflammation. 2014; 1; 107-114. [CrossRef]
  13. Heiss WD. Positron emission tomography imaging in gliomas: applications in clinical diagnosis, for assessment of prognosis and of treatment effects, and for detection of recurrences. Eur J Neurol. 2017; 24: e1255-e1270. [CrossRef]
  14. Verger A, Langen K-J. PET Imaging in Glioblastoma: Use in Clinical Practice. Glioblastoma [Internet]: Codon Publications. 2017.
  15. Reivich M, Kuhl D, Wolf A, Greenberg J, Phelps Ma, Ido T, et al. The [18F] fluorodeoxyglucose method for the measurement of local cerebral glucose utilization in man. Circ Res. 1979; 44: 127-137. [CrossRef]
  16. Bergström M, Lundqvist H, Ericson K, Lilja A, Johnström P, Långström B, et al. Comparison of the accumulation kinetics of L-(methyl-11C)-methionine and D-(methyl-11C)-methionine in brain tumors studied with positron emission tomography. Acta Radiol. 1987; 28: 225-229.
  17. Miyagawa T, Oku T, Uehara H, Desai R, Beattie B, Tjuvajev J, et al. “Facilitated” amino acid transport is upregulated in brain tumors. J Cerebr Blood F Met. 1998; 18: 500-509. [CrossRef]
  18. Becherer A, Karanikas G, Szabó M, Zettinig G, Asenbaum S, Marosi C, et al. Brain tumour imaging with PET: a comparison between [18 F] fluorodopa and [11 C] methionine. Eur J Nucl Med Mol I. 2003; 30: 1561-1567. [CrossRef]
  19. Weber WA, Wester H-J, Grosu AL, Herz M, Dzewas B, Feldmann H-J, et al. O-(2-[18 F] fluoroethyl)-L-tyrosine and L-[methyl-11 C] methionine uptake in brain tumours: initial results of a comparative study. Eur J Nucl Med. 2000; 27: 542-549. [CrossRef]
  20. Rasey JS, Grierson JR, Wiens LW, Kolb PD, Schwartz JL. Validation of FLT uptake as a measure of thymidine kinase-1 activity in A549 carcinoma cells. The J Nucl Med. 2002; 43: 1210.
  21. Shields AF, Grierson JR, Dohmen BM, Machulla H-J, Stayanoff JC, Lawhorn-Crews JM, et al. Imaging proliferation in vivo with [F-18] FLT and positron emission tomography. Nat Med. 1998; 4: 1334. [CrossRef]
  22. Muzi M, Spence AM, O'Sullivan F, Mankoff DA, Wells JM, Grierson JR, et al. Kinetic analysis of 3'-deoxy-3'-18F-fluorothymidine in patients with gliomas. J Nucl Med. 2006; 47: 1612-1621.
  23. Herholz K. Brain Tumors: An Update on Clinical PET Research in Gliomas. Semin Nucl Med. 2017; 47: 5-17. [CrossRef]
  24. Shields AF, Grierson JR, Dohmen BM, Machulla HJ, Stayanoff JC, Lawhorncrews JM, et al. Imaging proliferation in vivo with [F-18]FLT and positron emission tomography. Nat Med. 1998; 4: 1334. [CrossRef]
  25. Pietrzyk U, Herholz K, Heiss W. Three-dimensional alignment of functional and morphological tomograms. J Cmput Assist Tomo. 1990; 14: 51-59.
  26. Louis DN, Ohgaki H, Wiestler OD, Cavenee WK, Burger PC, Jouvet A, et al. The 2007 WHO classification of tumours of the central nervous system. Acta neuropathol. 2007; 114: 97-109. [CrossRef]
  27. Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, et al. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. Acta Neuropathol. 2016; 131: 803-820. [CrossRef]
  28. Paulus W, Peiffer J. Intratumoral histologic heterogeneity of gliomas. A quantitative study. Cancer. 1989; 64: 442-447. [CrossRef]
  29. Patronas N, Di Chiro G, Brooks R, DeLaPaz R, Kornblith P, Smith B, et al. Work in progress:[18F] fluorodeoxyglucose and positron emission tomography in the evaluation of radiation necrosis of the brain. Radiology. 1982; 144: 885-889. [CrossRef]
  30. Delbeke D, Meyerowitz C, Lapidus RL, Maciunas RJ, Jennings MT, Moots PL, et al. Optimal cutoff levels of F-18 fluorodeoxyglucose uptake in the differentiation of low-grade from high-grade brain tumors with PET. Radiology. 1995; 195: 47-52. [CrossRef]
  31. Spence AM, Muzi M, Mankoff DA, O'Sullivan SF. ^ sup 18^ F-FDG PET of Gliomas at Delayed Intervals: Improved Distinction Between Tumor and Normal Gray Matter. J Nucl Med. 2004; 45: 1653.
  32. Di Chiro G, DeLaPaz RL, Brooks RA, Sokoloff L, Kornblith PL, Smith BH, et al. Glucose utilization of cerebral gliomas measured by [18F] fluorodeoxyglucose and positron emission tomography. Neurology. 1982; 32: 1323. [CrossRef]
  33. Herholz K, Pietrzyk U, Voges J, Schröder R, Halber M, Treuer H, et al. Correlation of glucose consumption and tumor cell density in astrocytomas: a stereotactic PET study. J neurosurg. 1993; 79: 853-858. [CrossRef]
  34. Patronas NJ, Chiro GD, Kufta C, Bairamian D, Kornblith PL, Simon R, et al. Prediction of survival in glioma patients by means of positron emission tomography. J Neurosurg. 1985; 62: 816-822. [CrossRef]
  35. Hölzer T, Herholz K, Jeske J, Heiss W-D. FDG-PET as a prognostic indicator in radiochemotherapy of glioblastoma. J Cmput Assist Tomo. 1993; 17: 681-687. [CrossRef]
  36. Wray R, Solnes L, Mena E, Meoded A, Subramaniam RM. 18F-Flourodeoxy-glucose PET/computed tomography in brain tumors: value to patient management and survival outcomes. PET Clinics. 2015; 10: 423-430. [CrossRef]
  37. Levivier M, Goldman S, Pirotte B, Brucher J-M, Balériaux D, Luxen A, et al. Diagnostic yield of stereotactic brain biopsy guided by positron emission tomography with [18F] fluorodeoxyglucose. J Neurosurg. 1995; 82: 445-452. [CrossRef]
  38. Herholz K, Herscovitch P, Heiss W-D, Heiss W-D. NeuroPET: Positron Emission Tomography in Neuroscience and Clinical Neurology; 11 Tables: Springer Science & Business Media; 2004. [CrossRef]
  39. Ullrich RT, Kracht LW, Jacobs AH. Neuroimaging in patients with gliomas. Semin Neurol. 2008; 28: 484-494. [CrossRef]
  40. Albert NL, Weller M, Suchorska B, Galldiks N, Soffietti R, Kim MM, et al. Response Assessment in Neuro-Oncology working group and European Association for Neuro-Oncology recommendations for the clinical use of PET imaging in gliomas. Neuro Oncol. 2016; 18: 1199-1208. [CrossRef]
  41. Kracht LW, Friese M, Herholz K, Schroeder R, Bauer B, Jacobs A, et al. Methyl-[11 C]-l-methionine uptake as measured by positron emission tomography correlates to microvessel density in patients with glioma. Eur J Nucl Med Mol I. 2003; 30: 868-873. [CrossRef]
  42. Herholz K, Hölzer T, Bauer B, Schröder R, Voges J, Ernestus R, et al. 11C-methionine PET for differential diagnosis of low-grade gliomas. Neurology. 1998; 50: 1316-1322. [CrossRef]
  43. Chung J-K, Kim Y, Kim S-k, Lee Y, Paek S, Yeo J, et al. Usefulness of 11 C-methionine PET in the evaluation of brain lesions that are hypo-or isometabolic on 18 F-FDG PET. Eur J Nucl Med Mol I. 2002; 29: 176-182. [CrossRef]
  44. Kuwert T, Morgenroth C, Woesler B, Matheja P, Palkovic S, Vollet B, et al. Uptake of iodine-123-α-methyl tyrosine by gliomas and non-neoplastic brain lesions. Eur J Nucl Med. 1996; 23: 1345-1353. [CrossRef]
  45. Bergström M, Collins VP, Ehrin E, Ericson K, Eriksson L, Greitz T, et al. Discrepancies in brain tumor extent as shown by computed tomography and positron emission tomography using [68Ga] EDTA,[11C] glucose, and [11C] methionine. J Cmput Assist Tomo. 1983; 7: 1062-1066. [CrossRef]
  46. Nuutinen J, Sonninen P, Lehikoinen P, Sutinen E, Valavaara R, Eronen E, et al. Radiotherapy treatment planning and long-term follow-up with [11C] methionine PET in patients with low-grade astrocytoma. International J Radiat Oncol Biol Phys. 2000; 48: 43-52. [CrossRef]
  47. Mineura K, Sasajima T, Kowada M, Uesaka Y, Shishido F. Innovative approach in the diagnosis of gliomatosis cerebri using carbon-11-L-methionine positron emission tomography. J Nucl Med: official publication, Soc Nucl Med. 1991; 32: 726-728.
  48. Singhal T, Narayanan TK, Jacobs MP, Bal C, Mantil JC. 11C-methionine PET for grading and prognostication in gliomas: a comparison study with 18F-FDG PET and contrast enhancement on MRI. J Nucl Med. 2012; 53: 1709. [CrossRef]
  49. Glaudemans AW, Enting RH, Heesters MA, Dierckx RA, van Rheenen RW, Walenkamp AM, et al. Value of 11 C-methionine PET in imaging brain tumours and metastases. Eur J Nucl Med Mol I. 2013; 40: 615-635. [CrossRef]
  50. Suchorska B, Albert N, Bauer E, Tonn J, Galldiks N. The role of amino acid PET in the light of the new WHO classification 2016 for brain tumors. Q J Nucl Med Mol Imaging. 2018. [CrossRef]
  51. Näslund O, Smits A, Förander P, Laesser M, Bartek J, Gempt J, et al. Amino acid tracers in PET imaging of diffuse low-grade gliomas: a systematic review of preoperative applications. Acta Neurochir. 2018;1-10. [CrossRef]
  52. Derlon J-M, Petit-Taboué M-C, Chapon F, Beaudouin V, Noël M-H, Creveuil C, et al. The in vivo metabolic pattern of low-grade brain gliomas: a positron emission tomographic study using 18F-fluorodeoxyglucose and 11C-L-methylmethionine. Neurosurgery. 1997; 40: 276-287. [CrossRef]
  53. Kato T, Shinoda J, Oka N, Miwa K, Nakayama N, Yano H, et al. Analysis of 11C-methionine uptake in low-grade gliomas and correlation with proliferative activity. Am J Neuroradiol. 2008; 29: 1867-1871. [CrossRef]
  54. Galldiks N, Langen K-J, Pope WB. From the clinician's point of view-What is the status quo of positron emission tomography in patients with brain tumors? Neuro Oncol. 2015; 17: 1434-1444. [CrossRef]
  55. Villani V, Carapella CM, Chiaravalloti A, Terrenato I, Piludu F, Vidiri A, et al. The Role of PET [18F]FDOPA in Evaluating Low-grade Glioma. Anticancer Res. 2015; 35: 5117-5122.
  56. Dadone-Montaudie B, Ambrosetti D, Dufour M, Darcourt J, Almairac F, Coyne J, et al. [18F] FDOPA standardized uptake values of brain tumors are not exclusively dependent on LAT1 expression. 2017; 12: e0184625.
  57. Gempt J, Bette S, Ryang Y-M, Buchmann N, Peschke P, Pyka T, et al. 18F-fluoro-ethyl-tyrosine positron emission tomography for grading and estimation of prognosis in patients with intracranial gliomas. Eur J Radiol. 2015; 84: 955-962. [CrossRef]
  58. Sweeney R, Polat B, Samnick S, Reiners C, Flentje M, Verburg FA. O-(2-[18 F] fluoroethyl)-l-tyrosine uptake is an independent prognostic determinant in patients with glioma referred for radiation therapy. Ann Nucl Med. 2014; 28: 154-162. [CrossRef]
  59. Suchorska B, Jansen NL, Linn J, Kretzschmar H, Janssen H, Eigenbrod S, et al. Biological tumor volume in 18FET-PET before radiochemotherapy correlates with survival in GBM. Neurology. 2015; 84: 710-719. [CrossRef]
  60. Hutterer M, Nowosielski M, Putzer D, Jansen NL, Seiz M, Schocke M, et al. [18F]-fluoro-ethyl-L-tyrosine PET: a valuable diagnostic tool in neuro-oncology, but not all that glitters is glioma. Neuro Oncol. 2013; 15:341-351. [CrossRef]
  61. Pauleit D, Floeth F, Hamacher K, Riemenschneider MJ, Reifenberger G, Müller H-W, et al. O-(2-[18F] fluoroethyl)-L-tyrosine PET combined with MRI improves the diagnostic assessment of cerebral gliomas. Brain. 2005; 128: 678-687. [CrossRef]
  62. Floeth FW, Pauleit D, Wittsack H-J, Langen KJ, Reifenberger G, Hamacher K, et al. Multimodal metabolic imaging of cerebral gliomas: positron emission tomography with [18F] fluoroethyl-L-tyrosine and magnetic resonance spectroscopy. J Neurosurg. 2005; 102: 318-327. [CrossRef]
  63. Stadlbauer A, Prante O, Nimsky C, Salomonowitz E, Buchfelder M, Kuwert T, et al. Metabolic imaging of cerebral gliomas: spatial correlation of changes in O-(2-18F-fluoroethyl)-L-tyrosine PET and proton magnetic resonance spectroscopic imaging. J Nucl Med. 2008; 49: 721-729. [CrossRef]
  64. Albert NL, Winkelmann I, Suchorska B, Wenter V, Schmid-Tannwald C, Mille E, et al. Early static 18F-FET-PET scans have a higher accuracy for glioma grading than the standard 20–40 min scans. Eur J Nucl Med Mol I. 2016; 43: 1105-1114. [CrossRef]
  65. Calcagni ML, Galli G, Giordano A, Taralli S, Anile C, Niesen A, et al. Dynamic O-(2-[18F] fluoroethyl)-L-tyrosine (F-18 FET) PET for glioma grading: assessment of individual probability of malignancy. Clin Nucl Med. 2011; 36: 841-847. [CrossRef]
  66. Pyka T, Gempt J, Ringel F, Hüttinger S, van Marwick S, Nekolla S, et al. Prediction of glioma recurrence using dynamic 18F-fluoroethyltyrosine PET. Am J Neuroradiol. 2014; 35: 1924-1929. [CrossRef]
  67. Lohmann P, Herzog H, Kops ER, Stoffels G, Judov N, Filss C, et al. Dual-time-point O-(2-[18F] fluoroethyl)-L-tyrosine PET for grading of cerebral gliomas. Eur Radiol. 2015; 25: 3017-3024. [CrossRef]
  68. Niyazi M, Jansen N, Ganswindt U, Schwarz SB, Geisler J, Schnell O, et al. Re-irradiation in recurrent malignant glioma: prognostic value of [18 F] FET–PET. J Neuro-oncol. 2012; 110: 389-395. [CrossRef]
  69. Jansen NL, Suchorska B, Wenter V, Eigenbrod S, Schmid-Tannwald C, Zwergal A, et al. Dynamic 18F-FET PET in newly diagnosed astrocytic low-grade glioma identifies high-risk patients. J Nucl Med. 2014; jnumed. 113.122333.
  70. Galldiks N, Stoffels G, Filss C, Rapp M, Blau T, Tscherpel C, et al. The use of dynamic O-(2-18F-fluoroethyl)-l-tyrosine PET in the diagnosis of patients with progressive and recurrent glioma. Neuro-oncol 2015; 17: 1293-1300. [CrossRef]
  71. Thon N, Kunz M, Lemke L, Jansen NL, Eigenbrod S, Kreth S, et al. Dynamic 18 F‐FET PET in suspected WHO grade II gliomas defines distinct biological subgroups with different clinical courses. IntJ Cancer. 2015; 136: 2132-2145. [CrossRef]
  72. Bashir A, Brennum J, Broholm H, Law I. The diagnostic accuracy of detecting malignant transformation of low-grade glioma using O-(2-[18F] fluoroethyl)-l-tyrosine positron emission tomography: a retrospective study. J Neurosurg. 2018: 1-14. [CrossRef]
  73. Fueger BJ, Czernin J, Cloughesy T, Silverman DH, Geist CL, Walter MA, et al. Correlation of 6-18F-fluoro-L-dopa PET uptake with proliferation and tumor grade in newly diagnosed and recurrent gliomas. J Nucl Med. 2010; 51: 1532. [CrossRef]
  74. Janvier L, Olivier P, Blonski M, Morel O, Vignaud J-M, Karcher G, et al. Correlation of SUV-derived indices with tumoral aggressiveness of gliomas in static 18F-FDOPA PET: use in clinical practice. Clin Nucl Med. 2015; 40: e429-e435. [CrossRef]
  75. Herrmann K, Czernin J, Cloughesy T, Lai A, Pomykala KL, Benz MR, et al. Comparison of visual and semiquantitative analysis of 18F-FDOPA-PET/CT for recurrence detection in glioblastoma patients. Neuro-oncol. 2013; 16: 603-609. [CrossRef]
  76. Karunanithi S, Sharma P, Kumar A, Gupta DK, Khangembam BC, Ballal S, et al. Can 18F-FDOPA PET/CT predict survival in patients with suspected recurrent glioma? A prospective study. Eur J Radiol. 2014; 83: 219-225. [CrossRef]
  77. Patel CB, Fazzari E, Chakhoyan A, Yao J, Raymond C, Nguyen H, et al. 18 F-FDOPA PET and MRI characteristics correlate with degree of malignancy and predict survival in treatment-naïve gliomas: a cross-sectional study. J Neuro Oncol. 2018: 1-11.
  78. Villani V, Carapella CM, Chiaravalloti A, Terrenato I, Piludu F, Vidiri A, et al. The role of PET [18F] FDOPA in evaluating low-grade glioma. Anticancer Res. 2015; 35: 5117-5122.
  79. Lapa C, Linsenmann T, Monoranu CM, Samnick S, Buck AK, Bluemel C, et al. Comparison of the amino acid tracers 18F-FET and 18F-DOPA in high-grade glioma patients. J Nucl Med. 2014; 55: 1611-1616. [CrossRef]
  80. Nikaki A, Angelidis G, Efthimiadou R, Tsougos I, Valotassiou V, Fountas K, et al. 18 F-fluorothymidine PET imaging in gliomas: an update. Ann Nucl Med. 2017; 31: 495-505. [CrossRef]
  81. Ullrich R, Backes H, Li H, Kracht L, Miletic H, Kesper K, et al. Glioma proliferation as assessed by 3 ‘-fluoro-3’-deoxy-L-thymidine positron emission tomography in patients with newly diagnosed high-grade glioma. Clin Cancer Res. 2008; 14: 2049-2055. [CrossRef]
  82. Chen W, Cloughesy T, Kamdar N, Satyamurthy N, Bergsneider M, Liau L, et al. Imaging proliferation in brain tumors with 18F-FLT PET: comparison with 18F-FDG. J Nucl Med. 2005; 46: 945-952.
  83. Collet S, Valable S, Constans J, Lechapt-Zalcman E, Roussel S, Delcroix N, et al. [18F]-fluoro-l-thymidine PET and advanced MRI for preoperative grading of gliomas. NeuroImage: Clinical. 2015 ;8: 448-454. [CrossRef]
  84. Hatakeyama T, Kawai N, Nishiyama Y, Yamamoto Y, Sasakawa Y, Ichikawa T, et al. 11 C-methionine (MET) and 18 F-fluorothymidine (FLT) PET in patients with newly diagnosed glioma. Eur J Nucl Med Mol I. 2008; 35: 2009-2017. [CrossRef]
  85. Tripathi M, Sharma R, D'souza M, Jaimini A, Panwar P, Varshney R, et al. Comparative evaluation of F-18 FDOPA, F-18 FDG, and F-18 FLT-PET/CT for metabolic imaging of low grade gliomas. Clin Nucl Med. 2009; 34: 878-883. [CrossRef]
  86. Idema A, Hoffmann AL, Boogaarts HD, Troost E, Wesseling P, Heerschap A, et al. 30-Deoxy-30-18F-fluorothymidine PET-derived proliferative volume predicts overall survival in high-grade glioma patients. J Nucl Med. 2012; 53: 1904-1910. [CrossRef]
  87. DeLaPaz R, Patronas NJ, Brooks RA, Smith BH, Kornblith PL, Milam H, et al. Positron emission tomographic study of suppression of gray-matter glucose utilization by brain tumors. Am J Neuroradiol. 1983; 4: 826-829.
  88. Wunderlich G, Knorr U, Herzog H, Kiwit JC, Freund H-J, Seitz RJ. Precentral glioma location determines the displacement of cortical hand representation. Neurosurgery. 1998; 42: 18-27. [CrossRef]
  89. Thiel A, Herholz K, Koyuncu A, Ghaemi M, Kracht LW, Habedank B, et al. Plasticity of language networks in patients with brain tumors: A PET activation study. AnnNeurol. 2001; 50: 620-629. [CrossRef]
  90. Keunen O, Taxt T, Grüner R, Lund-Johansen M, Tonn J-C, Pavlin T, et al. Multimodal imaging of gliomas in the context of evolving cellular and molecular therapies. Adv Drug Deliver Rev. 2014; 76: 98-115. [CrossRef]
  91. Brock C, Young H, O'Reilly S, Matthews J, Osman S, Evans H, et al. Early evaluation of tumour metabolic response using [18 F] fluorodeoxyglucose and positron emission tomography: a pilot study following the phase II chemotherapy schedule for temozolomide in recurrent high-grade gliomas. British J Cancer. 2000; 82: 608. [CrossRef]
  92. Glantz MJ, Hoffman JM, Coleman RE, Friedman AH, Hanson MW, Burger PC, et al. Identification of early recurrence of primary central nervous system tumors by [18F] fluorodeoxyglucose positron emission tomography. Ann Neurol. 1991; 29: 347-355. [CrossRef]
  93. Charnley N, West CM, Barnett CM, Brock C, Bydder GM, Glaser M, et al. Early change in glucose metabolic rate measured using FDG-PET in patients with high-grade glioma predicts response to temozolomide but not temozolomide plus radiotherapy. Int J Radiat Oncol Biol Phys. 2006; 66: 331-338. [CrossRef]
  94. Sarkaria JN, Galanis E, Wu W, Peller PJ, Giannini C, Brown PD, et al. North Central Cancer Treatment Group Phase I trial N057K of everolimus (RAD001) and temozolomide in combination with radiation therapy in patients with newly diagnosed glioblastoma multiforme. Int J Radiat Oncol Biol Phys. 2011; 81: 468-475. [CrossRef]
  95. Ricci PE, Karis JP, Heiserman JE, Fram EK, Bice AN, Drayer BP. Differentiating recurrent tumor from radiation necrosis: time for re-evaluation of positron emission tomography? Am J Neuroradiol. 1998; 19: 407-413.
  96. Tanaka Y, Nariai T, Momose T, Aoyagi M, Maehara T, Tomori T, et al. Glioma surgery using a multimodal navigation system with integrated metabolic images. J Neurosurg. 2009; 110: 163-172. [CrossRef]
  97. Grosu A-L, Weber WA, Riedel E, Jeremic B, Nieder C, Franz M, et al. L-(methyl-11C) methionine positron emission tomography for target delineation in resected high-grade gliomas before radiotherapy.Int J Radiat Oncol Biol Phys. 2005; 63: 64-74. [CrossRef]
  98. Weber DC, Zilli T, Buchegger F, Casanova N, Haller G, Rouzaud M, et al. [(18) F] Fluoroethyltyrosine-positron emission tomography-guided radiotherapy for high-grade glioma. Radiat Oncol. 2008; 3: 44. [CrossRef]
  99. Vees H, Senthamizhchelvan S, Miralbell R, Weber DC, Ratib O, Zaidi H. Assessment of various strategies for 18 F-FET PET-guided delineation of target volumes in high-grade glioma patients. Eur J Nucl Med Mol I. 2009; 36: 182-193. [CrossRef]
  100. Nariai T, Tanaka Y, Wakimoto H, Aoyagi M, Tamaki M, Ishiwata K, et al. Usefulness of l-[methyl-11C] methionine—positron emission tomography as a biological monitoring tool in the treatment of glioma. J Neurosurg. 2005; 103: 498-507. [CrossRef]
  101. Thiel A, Pietrzyk U, Sturm V, Herholz K, Hövels M, Schröder R. Enhanced accuracy in differential diagnosis of radiation necrosis by positron emission tomography-magnetic resonance imaging coregistration: technical case report. Neurosurgery. 2000; 46: 232-234. [CrossRef]
  102. Tsuyuguchi N, Takami T, Sunada I, Iwai Y, Yamanaka K, Tanaka K, et al. Methionine positron emission tomography for differentiation of recurrent brain tumor and radiation necrosis after stereotactic radiosurgery—In malignant glioma—. Ann Nucl Med. 2004; 18: 291-296. [CrossRef]
  103. Terakawa Y, Tsuyuguchi N, Iwai Y, Yamanaka K, Higashiyama S, Takami T, et al. Diagnostic accuracy of 11C-methionine PET for differentiation of recurrent brain tumors from radiation necrosis after radiotherapy. J Nucl Med. 2008. [CrossRef]
  104. Van Laere K, Ceyssens S, Van Calenbergh F, de Groot T, Menten J, Flamen P, et al. Direct comparison of 18 F-FDG and 11 C-methionine PET in suspected recurrence of glioma: sensitivity, inter-observer variability and prognostic value. Eur J Nucl Med Mol I. 2005; 32: 39-51. [CrossRef]
  105. Yamane T, Sakamoto S, Senda M. Clinical impact of 11 C-methionine PET on expected management of patients with brain neoplasm. Eur J Nucl Med Mol I. 2010; 37: 685-690. [CrossRef]
  106. Galldiks N, Kracht LW, Burghaus L, Thomas A, Jacobs AH, Heiss WD, et al. Use of 11 C-methionine PET to monitor the effects of temozolomide chemotherapy in malignant gliomas. Eur J Nucl Med Mol I. 2006; 33: 516-524. [CrossRef]
  107. Wyss M, Hofer S, Bruehlmeier M, Hefti M, Uhlmann C, Bärtschi E, et al. Early metabolic responses in temozolomide treated low-grade glioma patients. J Neuro Oncol. 2009; 95: 87-93. [CrossRef]
  108. Galldiks N, Kracht LW, Burghaus L, Ullrich RT, Backes H, Brunn A, et al. Patient-tailored, imaging-guided, long-term temozolomide chemotherapy in patients with glioblastoma. Mol Imaging. 2010; 9: 7 290.2010. 00002.
  109. Ono T, Sasajima T, Doi Y, Oka S, Ono M, Kanagawa M, et al. Amino acid PET tracers are reliable markers of treatment responses to single-agent or combination therapies including temozolomide, interferon-β, and/or bevacizumab for glioblastoma. Nucl Med Biol. 2015; 42: 598-607. [CrossRef]
  110. Mehrkens J, Pöpperl G, Rachinger W, Herms J, Seelos K, Tatsch K, et al. The positive predictive value of O-(2-[18 F] fluoroethyl)-L-tyrosine (FET) PET in the diagnosis of a glioma recurrence after multimodal treatment. J Neuro Oncol. 2008; 88: 27-35. [CrossRef]
  111. Rachinger W, Goetz C, Pöpperl G, Gildehaus FJ, Kreth FW, Holtmannspötter M, et al. Positron emission tomography with O-(2-[18F]fluoroethyl)-l-tyrosine versus magnetic resonance imaging in the diagnosis of recurrent gliomas. Neurosurgery. 2005; 57: 505-511. [CrossRef]
  112. Galldiks N, Langen KJ, Holy R, Pinkawa M, Stoffels G, Nolte KW, et al. Assessment of Treatment Response in Patients with Glioblastoma Using O-(2-18F-Fluoroethyl)-l-Tyrosine PET in Comparison to MRI. J Nucl Med. 2012; 53: 1048-1057. [CrossRef]
  113. Piroth MD, Pinkawa M, Holy R, Klotz J, Nussen S, Stoffels G, et al. Prognostic Value of Early [F]Fluoroethyltyrosine Positron Emission Tomography After Radiochemotherapy in Glioblastoma Multiforme. Int J Radiat Oncol Biol Phys. 2011; 80: 176-184. [CrossRef]
  114. Galldiks N, Rapp M, Stoffels G, Fink GR, Shah NJ, Coenen HH, et al. Response assessment of bevacizumab in patients with recurrent malignant glioma using [18F]Fluoroethyl-L-tyrosine PET in comparison to MRI. Eur J Nucl Med Mol I. 2013; 40: 22-33. [CrossRef]
  115. Schwarzenberg J, Czernin J, Cloughesy TF, Ellingson BM, Pope WB, Grogan T, et al. Treatment response evaluation using 18F-FDOPA PET in patients with recurrent malignant glioma on bevacizumab therapy. Clin Cancer Res. 2014; 20: 3550-3559. [CrossRef]
  116. Galldiks N, Dunkl V, Stoffels G, Hutterer M, Rapp M, Sabel M, et al. Diagnosis of pseudoprogression in patients with glioblastoma using O-(2-[18F]fluoroethyl)-L-tyrosine PET. Eur J Nucl Med Mol Imaging. 2015; 42: 685-695. [CrossRef]
  117. Heinzel A, Müller D, Langen KJ, Blaum M, Verburg FA, Mottaghy FM, et al. The Use of O-(2-18F-Fluoroethyl)-l-Tyrosine PET for Treatment Management of Bevacizumab and Irinotecan in Patients with Recurrent High-Grade Glioma: A Cost-Effectiveness Analysis. J Nucl Med. 2013; 54: 1217-1222. [CrossRef]
  118. Jansen NL, Suchorska B, Schwarz SB, Eigenbrod S, Lutz J, Graute V, et al. [18F]fluoroethyltyrosine-positron emission tomography-based therapy monitoring after stereotactic iodine-125 brachytherapy in patients with recurrent high-grade glioma. Mol Imaging. 2013; 12: 137-147. [CrossRef]
  119. Niyazi M, Jansen NL, Rottler M, Ganswindt U, Belka C. Recurrence pattern analysis after re-irradiation with bevacizumab in recurrent malignant glioma patients. Radiat Oncol. 2014; 9: 299. [CrossRef]
  120. Franceschi E, Bartolotti M, Brandes AA. Bevacizumab in recurrent glioblastoma: open issues. Future Oncol. 2015; 11: 2655-2665. [CrossRef]
  121. Galldiks N, Kocher M, Langen KJ. Pseudoprogression after glioma therapy: an update. Expert Rev Neurother. 2017; 17. [CrossRef]
  122. Chen W, Delaloye S, Silverman DH, Geist C, Czernin J, Sayre J, et al. Predicting treatment response of malignant gliomas to bevacizumab and irinotecan by imaging proliferation with [18F] fluorothymidine positron emission tomography: a pilot study. J Clinl Oncol. 2007; 25: 4714-4721. [CrossRef]
  123. Wardak M, Schiepers C, Dahlbom M, Cloughesy T, Chen W, Satyamurthy N, et al. Discriminant analysis of ¹⁸F-fluorothymidine kinetic parameters to predict survival in patients with recurrent high-grade glioma. Clin Cancer Res. 2011; 17: 6553-6562. [CrossRef]
  124. Corroyer-Dulmont, Aurelien, Jacobs, Andreas H. Detection of glioblastoma response to temozolomide combined with;bevacizumab based on mu MRI and mu PET imaging reveals;[F-18]-fluoro-L-thymidine as an early and robust predictive marker for;treatment efficacy. Neuro Oncol. 2013; 15: 41-56. [CrossRef]
  125. Schwarzenberg J, Czernin J, Cloughesy TF, Ellingson BM, Pope WB, Geist C, et al. 3'-deoxy-3'-18F-fluorothymidine PET and MRI for early survival predictions in patients with recurrent malignant glioma treated with bevacizumab. J Nucl Med. 2012; 53: 29-36. [CrossRef]
  126. Wardak M, Schiepers C, Cloughesy TF, Dahlbom M, Phelps ME, Huang SC. 18 F-FLT    and 18 F-FDOPA PET kinetics in recurrent brain tumors. Eur J Nucl Med & Molecular Imaging. 2014; 41: 1199-1209. [CrossRef]
  127. Schnell O, Krebs B, Carlsen J, Miederer I, Goetz C, Goldbrunner RH, et al. Imaging of integrin αvβ3 expression in patients with malignant glioma by [18F] Galacto-RGD positron emission tomography. Neuro-Oncol. 2009; 11: 861. [CrossRef]
  128. Jacobs A, Voges J, Reszka R, Lercher M, Gossmann A, Kracht L, et al. Positron-emission tomography of vector-mediated gene expression in gene therapy for gliomas. Lancet. 2001; 358: 727-729. [CrossRef]
  129. Vredenburgh JJ, Desjardins A, Nd HJ, Marcello J, Reardon DA, Quinn JA, et al. Bevacizumab plus irinotecan in recurrent glioblastoma multiforme. J Clin Oncol. 2007; 25: 4722-4729. [CrossRef]
  130. Wen PY, Macdonald DR, Reardon DA, Cloughesy TF, Sorensen AG, Galanis E, et al. Updated Response Assessment Criteria for High-Grade Gliomas: Response Assessment in Neuro-Oncology Working Group. J Clin Oncol. 2010; 28: 1963. [CrossRef]
  131. Taal W, Brandsma D, de Bruin HG, Bromberg JE, Swaak-Kragten AT, Smitt PA, et al. Incidence of early pseudo-progression in a cohort of malignant glioma patients treated with chemoirradiation with temozolomide. Cancer. 2008; 113: 405-410. [CrossRef]
  132. Hutterer M, Nowosielski M, Putzer D, Waitz D, Tinkhauser G, Kostron H, et al. O-(2-18F-fluoroethyl)-L-tyrosine PET predicts failure of antiangiogenic treatment in patients with recurrent high-grade glioma. J Nucl Med. 2011; 52: 856-864. [CrossRef]
  133. Schiepers C, Dahlbom M, Chen W, Cloughesy T, Czernin J, Phelps ME, et al. Kinetics of 3'-deoxy-3'-18F-fluorothymidine during treatment monitoring of recurrent high-grade glioma. J Nucl Med. 2010; 51: 720-727. [CrossRef]
  134. Schwarzenberg J, Czernin J, Cloughesy TF, Ellingson BM, Pope WB, Grogan T, et al. Treatment response evaluation using 18F-FDOPA PET in patients with recurrent malignant glioma on bevacizumab therapy. Clin Cancer Res. 2014; 20: 3550-3559. [CrossRef]
  135. De Witte O, Levivier M, Violon P, Salmon I, Damhaut P, Wikler D, Jr., et al. Prognostic value positron emission tomography with [18F]fluoro-2-deoxy-D-glucose in the low-grade glioma. Neurosurgery. 1996; 39: 470-476.
  136. Langleben DD, Segall GM. PET in differentiation of recurrent brain tumor from radiation injury. J Nucl Med. 2000; 41: 1861-1867.
  137. Di Chiro G, Oldfield E, Wright DC, De Michele D, Katz DA, Patronas NJ, et al. Cerebral necrosis after radiotherapy and/or intraarterial chemotherapy for brain tumors: PET and neuropathologic studies. AJR Am J Roentgenol. 1988; 150: 189-197. [CrossRef]
  138. Levivier M, Becerra A, De WO, Brotchi J, Goldman S. Radiation necrosis or recurrence. J Neurosurg. 1996; 84: 148.
  139. Chao ST, Suh JH, Raja S, Lee SY, Barnett G. The sensitivity and specificity of FDG PET in distinguishing recurrent brain tumor from radionecrosis in patients treated with stereotactic radiosurgery. Int J Cancer. 2001; 96: 191-197. [CrossRef]
  140. Herholz K, Langen KJ, Schiepers C, Mountz JM. Brain tumors. Semin Nucl Med. 2012; 42: 356-370. [CrossRef]
  141. Reinhardt MJ, Kubota K, Yamada S, Iwata R, Yaegashi H. Assessment of cancer recurrence in residual tumors after fractionated radiotherapy: a comparison of fluorodeoxyglucose, L-methionine and thymidine. J Nucl Med. 1997; 38: 280-287.
  142. Takenaka S, Asano Y, Shinoda J, Nomura Y, Yonezawa S, Miwa K, et al. Comparison of (11)C-methionine, (11)C-choline, and (18)F-fluorodeoxyglucose-PET for distinguishing glioma recurrence from radiation necrosis. Neurologia medico-chirurgica. 2014; 54: 280-289. [CrossRef]
  143. Minamimoto R, Saginoya T, Kondo C, Tomura N, Ito K, Matsuo Y, et al. Differentiation of Brain Tumor Recurrence from Post-Radiotherapy Necrosis with 11C-Methionine PET: Visual Assessment versus Quantitative Assessment. PloS one. 2015; 10: e0132515. [CrossRef]
  144. Ceyssens S, Van Laere K, de Groot T, Goffin J, Bormans G, Mortelmans L. [11C]methionine PET, histopathology, and survival in primary brain tumors and recurrence. AJNR Am J Neuroradiol. 2006; 27: 1432-1437.
  145. Pöpperl G, Götz C, Rachinger W, Gildehaus FJ, Tonn JC, Tatsch K. Value of O-(2-[18F]fluoroethyl)- L-tyrosine PET for the diagnosis of recurrent glioma. Eur J Nucl Med & Mol Imaging. 2004; 31: 1464-1470. [CrossRef]
  146. Laukamp KR, Lindemann F, Weckesser M, Hesselmann V, Ligges S, Wolfer J, et al. Multimodal Imaging of Patients With Gliomas Confirms (11)C-MET PET as a Complementary Marker to MRI for Noninvasive Tumor Grading and Intraindividual Follow-Up After Therapy. Mol Imaging. 2017; 16: 1536012116687651. [CrossRef]
  147. Chen W. Clinical Applications of PET in Brain Tumors. J Nucl Med. 2007; 48: 1468. [CrossRef]
  148. Dunet V, Rossier C, Buck A, Stupp R, Prior JO. Performance of 18F-fluoro-ethyl-tyrosine (18F-FET) PET for the differential diagnosis of primary brain tumor: a systematic review and Metaanalysis. J Nucl Med. 2012; 53: 207-214. [CrossRef]
  149. Pyka T, Hiob D, Preibisch C, Gempt J, Wiestler B, Schlegel J, et al. Diagnosis of glioma recurrence using multiparametric dynamic 18F-fluoroethyl-tyrosine PET-MRI. Eur J Radiol. 2018; 103: 32-37. [CrossRef]
  150. Ledezma CJ, Chen W, Sai V, Freitas B, Cloughesy T, Czernin J, et al. 18F-FDOPA PET/MRI fusion in patients with primary/recurrent gliomas: initial experience. Eur J Radiol. 2009; 71: 242-248. [CrossRef]
  151. Cicone F, Filss CP, Minniti G, Rossi-Espagnet C, Papa A, Scaringi C, et al. Volumetric assessment of recurrent or progressive gliomas: comparison between F-DOPA PET and perfusion-weighted MRI. Eur J Nucl Med Mol Imaging. 2015; 42: 905-915. [CrossRef]
  152. Karunanithi S, Sharma P, Kumar A, Khangembam BC, Bandopadhyaya GP, Kumar R, et al. 18F-FDOPA PET/CT for detection of recurrence in patients with glioma: prospective comparison with 18F-FDG PET/CT. Eur J Nucl Med Mol Imaging. 2013; 40: 1025-1035. [CrossRef]
  153. Li Z, Yu Y, Zhang H, Xu G, Chen L. A meta-analysis comparing 18F-FLT PET with 18F-FDG PET for assessment of brain tumor recurrence. Nucl Med Communicat. 2015; 36: 695-701. [CrossRef]
  154. Zhao F, Cui Y, Li M, Fu Z, Chen Z, Kong L, et al. Prognostic value of 3'-deoxy-3'-18F-fluorothymidine ([(18)F] FLT PET) in patients with recurrent malignant gliomas. Nucl Med Biol. 2014; 41: 710-715. [CrossRef]
  155. Spence AM, Muzi M, Link JM, O'Sullivan F, Eary JF, Hoffman JM, et al. NCI-sponsored trial for the evaluation of safety and preliminary efficacy of 3'-deoxy-3'-[18F]fluorothymidine (FLT) as a marker of proliferation in patients with recurrent gliomas: preliminary efficacy studies. Mol Imaging Biol. 2009; 11: 343-355. [CrossRef]
  156. Judenhofer MS, Wehrl HF, Newport DF, Catana C, Siegel SB, Becker M, et al. Simultaneous PET-MRI: a new approach for functional and morphological imaging. Nat Med. 2008; 14: 459-465. [CrossRef]
  157. Schlemmer HP, Pichler BJ, Schmand M, Burbar Z, Michel C, Ladebeck R, et al. Simultaneous MR/PET imaging of the human brain: feasibility study. Radiology. 2008; 248: 1028-1035. [CrossRef]
  158. Heiss WD. The potential of PET/MR for brain imaging. Eur J Nucl Med Mol Imaging. 2009; 36 Suppl 1: S105-112. [CrossRef]
  159. Boss A, Bisdas S, Kolb A, Hofmann M, Ernemann U, Claussen CD, et al. Hybrid PET/MRI of intracranial masses: initial experiences and comparison to PET/CT. J Nucl Med. 2010; 51: 1198-1205. [CrossRef]
  160. Catana C, Drzezga A, Heiss WD, Rosen BR. PET/MRI for neurologic applications. Journal of Nuclear Medicine Official Publication Society of Nuclear Medicine. 2012; 53: 1916-1925. [CrossRef]
  161. Shin HW, Jewells V, Sheikh A, Zhang J, Zhu H, An H, et al. Initial experience in hybrid PET-MRI for evaluation of refractory focal onset epilepsy. Seizure Eur J Epilepsy. 2015; 31: 1-4. [CrossRef]
  162. Verger A, Filss CP, Lohmann P, Stoffels G, Sabel M, Wittsack HJ, et al. Comparison of O-(2-(18)F-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. World Neurosurg. 2018; 113: e727-e737. [CrossRef]
  163. Fink JR, Muzi M, Peck M, Krohn KA. Multimodality Brain Tumor Imaging: MR Imaging, PET, and PET/MR Imaging. J Nucl Med. 2015; 56: 1554-1561. [CrossRef]
  164. Marner L, Henriksen OM, Lundemann M, Larsen VA, Law I. Clinical PET/MRI in neurooncology: opportunities and challenges from a single-institution perspective. Clin Translational imaging. 2017; 5: 135-149. [CrossRef]
  165. Broski SM, Goenka AH, Kemp BJ, Johnson GB. Clinical PET/MRI: 2018 Update. AJR Am J Roentgenol. 2018; 211: 295-313. [CrossRef]
  166. Chiang GC, Kovanlikaya I, Choi C, Ramakrishna R, Magge R, Shungu DC. Magnetic Resonance Spectroscopy, Positron Emission Tomography and Radiogenomics-Relevance to Glioma. Front Neurol. 2018; 9: 33. [CrossRef]
  167. la Fougere C, Suchorska B, Bartenstein P, Kreth FW, Tonn JC. Molecular imaging of gliomas with PET: opportunities and limitations. Neuro Oncol. 2011; 13: 806-819. [CrossRef]
  168. Preuss M, Werner P, Barthel H, Nestler U, Christiansen H, Hirsch FW, et al. Integrated PET/MRI for planning navigated biopsies in pediatric brain tumors. Child's nervous system. 2014; 30: 1399-1403. [CrossRef]
  169. Burhan AM, Marlatt NM, Palaniyappan L, Anazodo UC, Prato FS. Role of Hybrid Brain Imaging in Neuropsychiatric Disorders. Diagnostics (Basel, Switzerland). 2015; 5: 577-614. [CrossRef]
  170. Bisdas S, La Fougere C, Ernemann U. Hybrid MR-PET in Neuroimaging. Clin Neuroradiol. 2015; 25 Suppl 2: 275-281. [CrossRef]
  171. Werner P, Barthel H, Drzezga A, Sabri O. Current status and future role of brain PET/MRI in clinical and research settings. Eur J Nucl Med Mol Imaging. 2015; 42: 512-526. [CrossRef]
  172. Sacconi B, Raad RA, Lee J, Fine H, Kondziolka D, Golfinos JG, et al. Concurrent functional and metabolic assessment of brain tumors using hybrid PET/MR imaging. J Neurooncol. 2016; 127: 287-293. [CrossRef]
  173. Filss CP, Galldiks N, Stoffels G, Sabel M, Wittsack HJ, Turowski B, et al. Comparison of 18F-FET PET and perfusion-weighted MR imaging: a PET/MR imaging hybrid study in patients with brain tumors. J Nucl Med. 2014; 55: 540-545. [CrossRef]
  174. Jena A, Taneja S. Multiparametric Evaluation in Differentiating Glioma Recurrence from Treatment-Induced Necrosis Using Simultaneous (18)F-FDG-PET/MRI: A Single-Institution Retrospective Study. 2017; 38: 899-907.
  175. Sogani SK, Jena A, Taneja S, Gambhir A, Mishra AK, D'Souza MM, et al. Potential for differentiation of glioma recurrence from radionecrosis using integrated 18F-fluoroethyl-L-tyrosine (FET) positron emission tomography/magnetic resonance imaging: A prospective evaluation. 2017.
  176. Puttick S, Bell C, Dowson N, Rose S, Fay M. PET, MRI, and simultaneous PET/MRI in the development of diagnostic and therapeutic strategies for glioma. Drug Discov Today. 2015; 20: 306-317. [CrossRef]
  177. Neuner I, Kaffanke JB, Langen KJ, Kops ER, Tellmann L, Stoffels G, et al. Multimodal imaging utilising integrated MR-PET for human brain tumour assessment. Eur Radiol. 2012; 22: 2568-2580. [CrossRef]
  178. Ertl-Wagner B, Ingrisch M, Niyazi M, Schnell O, Jansen N, Forster S, et al. [PET-MR in patients with glioblastoma multiforme]. Der Radiologe. 2013; 53: 682-690. [CrossRef]
  179. Jeong JW, Juhasz C, Mittal S, Bosnyak E, Kamson DO, Barger GR, et al. Multi-modal imaging of tumor cellularity and Tryptophan metabolism in human Gliomas. Cancer imaging. 2015;15: 10. [CrossRef]
  180. Morana G, Piccardo A, Puntoni M, Nozza P, Cama A, Raso A, et al. Diagnostic and prognostic value of 18F-DOPA PET and 1H-MR spectroscopy in pediatric supratentorial infiltrative gliomas: a comparative study. Neuro Oncol. 2015; 17: 1637-1647. [CrossRef]
  181. da Silva NA, Lohmann P, Fairney J, Magill AW, Oros Peusquens AM, Choi CH, et al. Hybrid MR-PET of brain tumours using amino acid PET and chemical exchange saturation transfer MRI. Eur J Nucl Med Mol Imaging. 2018; 45: 1031-1040. [CrossRef]
Journal Metrics
2023
CiteScore SJR SNIP
1.00.2320.256
Newsletter
Download PDF Download Full-Text XML Download Citation
0 0
Newsletter  

TOP