Literature DB >> 30699942

Combined Amino Acid Positron Emission Tomography and Advanced Magnetic Resonance Imaging in Glioma Patients.

Philipp Lohmann1, Jan-Michael Werner2, N Jon Shah3,4,5, Gereon R Fink6,7, Karl-Josef Langen8,9, Norbert Galldiks10,11,12.   

Abstract

Imaging techniques such as positron emission tomography (PET) and magnetic resonance imaging (MRI) provide valuable information about brain tumor patients. Particularly amino acid PET, advanced MRI techniques, and combinations thereof are of great interest for the non-invasive assessment of biological characteristics in patients with primary or secondary brain cancer. A methodological innovation that potentially advances research in patients with brain tumors is the increasing availability of hybrid PET/MRI systems, which enables the simultaneous acquisition of both imaging modalities. Furthermore, the advent of ultra-high field MRI scanners operating at magnetic field strengths of 7 T or more will allow further development of metabolic MR imaging at higher resolution. This review focuses on the combination of amino acid PET with MR spectroscopic imaging, perfusion- and diffusion-weighted imaging, as well as chemical exchange saturation transfer in patients with high-grade gliomas, especially glioblastomas.

Entities:  

Keywords:  3,4-dihydroxy-6-[18F]-fluoro-l-phenylalanine (FDOPA); O-(2-[18F]-fluoroethyl)-l-tyrosine (FET); [11C]-methyl-l-methionine (MET); brain tumors; chemical exchange saturation transfer; diffusion-weighted imaging; high-grade glioma; hybrid PET/MRI scanner; magnetic resonance spectroscopy; perfusion-weighted imaging

Year:  2019        PMID: 30699942      PMCID: PMC6406895          DOI: 10.3390/cancers11020153

Source DB:  PubMed          Journal:  Cancers (Basel)        ISSN: 2072-6694            Impact factor:   6.639


1. Introduction

At present, contrast-enhanced magnetic resonance imaging (MRI) is the method of choice for brain tumor diagnostics since MRI provides excellent soft tissue contrast, comparatively high resolution, and is widely available. On the downside, its specificity for neoplastic tissue is low, hampering the evaluation of tumor extent in both enhancing and non-enhancing gliomas as well as the differentiation of tumor progression from non-specific treatment-related changes [1,2,3]. [18F]-2-Fluoro-2-deoxy-D-glucose (FDG) is the most extensively used positron emission tomography (PET) tracer to date and has hence gained exceptional importance in general oncology. In stark contrast, its applicability in brain tumor diagnostics is hindered by high levels of physiological glucose uptake in the cerebral cortex resulting in diminished contrast between tumor and background. On the contrary, the cerebral uptake of radiolabeled amino acids is low while it is typically increased in brain tumors, resulting in an enhanced tumor-to-background contrast [4,5]. Importantly, the uptake of amino acid tracers is independent of the blood-brain barrier integrity, allowing the evaluation of amino acid uptake in non-enhancing gliomas [1,6]. Additionally, amino acid PET has demonstrated its usefulness for the differentiation of tumor progression from treatment-related changes [7,8,9,10,11,12] and for various other indications, e.g., treatment monitoring, prognostication or tumor grading [4,5,6,13,14,15,16,17]. Among amino acid tracers labelled with carbon-11 used for PET imaging in neuro-oncology, [11C]-methyl-L-methionine (MET) is currently best evaluated [18,19]. However, the short half-life of carbon-11 (20 min) limits its use to centers with an on-site cyclotron. To overcome such logistical limitations, amino acid tracers have been labeled with fluorine-18, which has a longer half-life of 110 min [4,6]. For that reason, O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) has replaced MET in many neuro-oncological centers. Subsequently, FET has become the most widely used radiotracer for brain tumor diagnostics, especially in Western Europe. Another fluorine-18 labeled amino acid tracer is 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (FDOPA), originally developed to evaluate the dopamine synthesis in the basal ganglia, which also shows increased uptake in brain tumors [20,21]. Although brain tumors distant to the striatum are depicted with high contrast, the high striatal uptake of FDOPA limits its usefulness for tumor delineation especially near the basal ganglia [22,23]. The Response Assessment in Neuro-Oncology (RANO) working group considers the additional value of amino acid PET for brain tumor diagnostics as highly relevant and recommends its use at every stage of brain tumor management [24]. The combination of MRI and PET, especially if hybrid PET/MR scanners are used, offers great potential for brain tumor diagnostics. This technology is particularly attractive when ultra-high field MRI scanners operating at magnetic field strengths of 7 T or more are widely available, allowing comparative anatomical and metabolic imaging at high resolution. Currently, amino acid PET tracers are the best evaluated and most frequently used PET tracers for brain tumor diagnostics. Therefore, this review focuses on the combination of amino acid PET with MR spectroscopy (MRS), perfusion- and diffusion-weighted imaging (PWI, DWI), and chemical exchange saturation transfer (CEST) in patients with glioblastoma (GBM).

2. Search Strategy

A PubMed search of the published literature with the combination of the search terms “glioblastoma”, “brain tumors”, “high-grade glioma”, “positron emission tomography”, “magnetic resonance imaging”, “magnetic resonance spectroscopy”, “perfusion-weighted imaging”, “diffusion-weighted imaging”, “chemical exchange saturation transfer”, “PET”, “amino acid PET”, “MRI”, “advanced MRI”, “MRS”, “PWI”, “DWI”, “CEST”, and “hybrid PET/MR” before and inclusive of December 2018 was performed. Additional literature was retrieved from the reference lists of all identified articles. Furthermore, articles identified through searches of the authors’ files were included. Only papers in English were considered.

3. Amino Acid PET and MRS

MR spectroscopy (MRS) is a non-invasive method to detect selected water-soluble metabolites in vivo. In magnetic resonance, an externally applied magnetic field experienced by the nucleus is modulated by the distribution of surrounding electrons. Given that every molecule presents with a slightly different distribution of electrons, every nucleus experiences a slightly different magnetic field. Consequently, every molecule has its characteristic magnetic field ‘signature’ that, combined with interactions amongst the nuclei, results in slightly different resonance frequencies leading to differential signals. These signal differences are used in MRS to identify the metabolites of interest. Every nucleus possessing a non-zero spin can be theoretically used for MRS, e.g., protons, carbon-13 and phosphorous-31. However, due to the low abundance of the latter and limited resolution of metabolite profiles in vivo, mainly proton spectra are used in clinical practice. Metabolites that are frequently assessed by MRS are lactate, lipids, alanine, N-acetylaspartate (NAA), glutamine, glutamate, 2-hydroxyglutarate (2-HG), citrate, creatine, choline, and myo-inositol. In gliomas, with increasing grade of malignancy, NAA and creatine are usually decreased, whereas choline, lipids and lactate are increased [25,26,27]. Furthermore, the accumulation of 2-HG caused by gene mutations encoding for the enzyme isocitrate dehydrogenase (IDH) can be detected by 2-HG spectroscopy at 3 T [28]. Although several studies demonstrated the feasibility of 2-HG spectroscopy in a clinical setting [29,30,31,32], 2-HG spectroscopy remains challenging due to a small and complex signal and it is therefore not yet established in clinical routine [33]. Two different MRS methods exist using either data from a single voxel or multiple voxels in a single slice or multiple slices of the investigated organ. Single-voxel spectroscopy is the most widely used method due to simple data acquisition and relatively short scanning time. Moreover, the comparatively high signal-to-noise ratio achieved by single-voxel spectroscopy results in high-quality spectra enabling a quantitative analysis and straightforward interpretation. However, the manually preselected region of interest (ROI) based on information from T2-weighted or contrast-enhanced MRI may represent only a fraction of the tumor, potentially resulting in an incomplete evaluation of tumor biology. Multi-voxel spectroscopy techniques may overcome these limitations by covering a more extended two- or three-dimensional ROI at higher spatial resolution. Especially in heterogenous lesions, this allows detection of subtle intratumoral signal alterations [34]. Another advantage of smaller voxels used in multi-voxel spectroscopy is the reduction of partial volume effects as structures such as cerebrospinal fluid or fat may diminish the quality of spectra and can be excluded from ROI definition. However, because of the difficulty of achieving good enough shimming over a large enough region, multi-voxel spectroscopy can have a lower signal-to-noise ratio, a reduced spectral quality for individual voxels, requires longer scanning times, and is technically more demanding than single-voxel spectroscopy [35]. In a few studies, MRS combined with amino acid PET in glioma patients was used. D´Souza and colleagues [36] evaluated in 29 high-grade glioma patients the diagnostic performance of MET PET and single-voxel MRS at 3 T for the correct diagnosis of tumor recurrence after neurooncological treatment including radiotherapy and chemotherapy. Metrics derived from both MET PET (i.e., tumor/brain ratios) and single-voxel MRS (i.e., choline/creatine ratios) suggested a high diagnostic accuracy of 85–90% for the detection of high-grade glioma recurrence. Floeth and co-workers [37] explored the use of combined FET PET and single-voxel MRS at 1.5 T in 50 patients with newly diagnosed lesions suspicious for gliomas on contrast-enhanced MRI. Based on the neuropathological assessment, gliomas could be identified with an accuracy of 68% using conventional MRI alone. Accuracy could be increased to 97% when conventional MR imaging was used in combination with FET PET and single-voxel MRS. In that study, FET lesion/brain ratios and NAA/choline ratios were identified as significant independent predictors for the identification of glioma tissue. Stadlbauer et al. [38] used two-dimensional multi-voxel spectroscopy at 1.5 T in combination with FET PET to spatially correlate concentrations of choline, creatine, and NAA with FET uptake in 15 glioma patients. The authors found significant correlations between increased FET uptake and parameters derived from MRS. More precisely, increased FET uptake was significantly correlated with the extent of neuronal loss (NAA) and partially with membrane proliferation (choline), indicating that both PET and MRS provide complementary information. Yet, the number of patients included in that study was relatively small and two-dimensional MRS allowed only limited coverage of the tumor, especially in comparison with amino acid PET, which provided three-dimensional information concerning tracer distribution. To overcome these limitations, Mauler and colleagues [39] investigated the spatial correlation between FET PET and three-dimensional MRS covering the whole brain. Forty-one glioma patients were investigated using a 3 T hybrid PET/MR scanner. Importantly, the authors reported that the FET uptake and increased choline/NAA ratios were not consistently spatially congruent (Figure 1). Unfortunately, however, no spatial correlation with neuropathological information obtained via stereotactic biopsy was performed to further explore the differences between amino acid uptake and the metabolites detected by MRS in gliomas.
Figure 1

Simultaneously acquired contrast-enhanced (CE) T1-weighted MRI, FET PET and whole-brain MRS shows elevated choline/N-acetylaspartate (Cho/NAA) ratios in a patient with neuropathologically confirmed glioblastoma. Areas of contrast enhancement, FET uptake and increased Cho/NAA are spatially incongruent. Image courtesy of Joerg Mauler, Institute of Neuroscience and Medicine, Forschungszentrum Juelich, Germany, and Andrew Maudsley, Department of Radiology, University of Miami Medical School, Miami, FL, USA.

4. Amino Acid PET and PWI

PWI is a non-invasive MRI technique to measure blood flow quantitatively. In Neuro-Oncology, the parameters relative cerebral blood volume (rCBV) and cerebral blood flow (rCBF) are frequently assessed. Most commonly, a gadolinium-based contrast agent is used to assess tissue perfusion. After i.v. injection, the passage of the contrast agent leads to i) a local magnetic field distortion (susceptibility effect) in the vicinity of the vessels causing a signal drop in T2- or T2*-weighted MRI, also called dynamic susceptibility contrast (DSC), or ii) a shortening of T1-relaxation time causing a signal increase in T1-weighted MRI, also called dynamic contrast-enhanced (DCE) MRI. While DSC data requires only the first pass of intravascular contrast agent for assessing tissue perfusion, DCE additionally evaluates information about the continuous accumulation of the contrast agent in the extracellular space. Consequently, the acquisition times for DCE are longer than for DSC. Another PWI method called arterial spin labelling (ASL) does not require a contrast agent. Here, endogenous water molecules in blood vessels are magnetically labeled by applying a specific radiofrequency pulse. Passage of these labeled molecules through the tissue of interest leads to a reduction of signal intensity in proportion to the perfusion. However, by dispensing with the administration of a contrast agent, the signal-to-noise ratio of ASL is inherently low, so that repetitive signal averaging is mandatory resulting in prolonged acquisition times. ASL significantly benefits from higher magnetic field strengths. Thus, ultra-high field MRI scanners operating at magnetic field strengths of up to 7 T may boost its clinical utility in the future. Several studies combined PWI and amino acid PET in patients with high-grade gliomas for the delineation of the glioma extent. Filss and colleagues [40] compared DSC PWI and FET PET acquired concurrently using a 3 T hybrid PET/MR scanner in 56 glioma patients (24 patients with GBM). One main finding was that FET PET tumor volumes were significantly larger than tumor volumes delineated by rCBV maps. Furthermore, the spatial congruence of the two methods was poor, and the localization of tumor hotspots identified by PWI and FET PET yielded inconsistent results indicating that the delineation of glioma extent is not appropriately reflected by PWI and hence cannot replace amino acid PET (Figure 2). These findings were confirmed subsequently [41,42]. Besides, similar results were reported by Cicone and co-workers for the comparison of DSC PWI at 1.5 T and FDOPA PET [22].
Figure 2

Simultaneously acquired contrast-enhanced (CE) T1-weighted MRI, FET PET and relative cerebral blood volume (rCBV) obtained from PWI in a patient with neuropathologically confirmed glioblastoma. FET PET identifies metabolically active tumor areas without an increased rCBV. Image courtesy of Christian Filss, Institute of Neuroscience and Medicine, Forschungszentrum Juelich, Juelich, Germany.

Verger et al. [43] investigated the usefulness of FET PET and DSC PWI at 3 T for the grading of gliomas in 72 patients with newly diagnosed glioma. The diagnostic accuracy for glioma grading was comparable for both FET PET and rCBV with an area under the receiver-operating characteristic curve of about 0.80. However, neuropathological diagnoses were not based on the revised WHO classification from 2016 [44], which limits the applicability of the results. The authors also found in 78% of patients a considerable spatial disparity between the local hotspots delineated using the two methods, consistent with previous studies [22,40,41]. Dandois and co-workers [45] compared the diagnostic accuracy of DSC PWI at 1.5 T and amino acid PET using MET for the differentiation of recurrent glioma from radiation necrosis in 28 high-grade glioma patients. The diagnostic performance was comparable between rCBV maps and MET PET for this clinically relevant question. These findings were reinforced by other studies [36,46,47]. However, in the majority of the cases, the diagnosis of either recurrent glioma or radiation necrosis was based on clinical observation and radiological follow-up rather than neuropathology. In stark contrast, Verger and colleagues [48] reported that FET PET seems to be superior to PWI at 3 T to diagnose recurrent glioma. Importantly, and in contrast to the latter studies mentioned above, the definite diagnosis was based on neuropathology in about 80% of the cases. These findings were confirmed by another study [49]. Subsequently, Roodakker et al. [50] compared regional MET PET and PWI at 3 T with local neuropathology in patients with en bloc-resected oligodendrogliomas. They showed that MET uptake correlated with tumor cell density throughout the entire tumor volume in all patients. Interestingly, tumor perfusion (rCBV) did not correlate with MET uptake or with any other histological marker. Morana and colleagues [51] compared FDOPA PET and ASL at 1.5 T for the grading and prediction of tumor progression in 26 pediatric gliomas. Authors reported a better diagnostic performance for FDOPA PET with an area under the receiver-operating characteristic curve of 0.95 compared to 0.88 for rCBF derived from ASL. The reported differences across the studies highlight the need for prospective studies with larger cohorts and neuropathological validation to further evaluate the differences between perfusion MRI and amino acid PET. Furthermore, a more recent meta-analysis regarding PWI in high-grade gliomas by Patel and co-workers [52] revealed a considerable heterogeneity of applied MR sequences, acquisition and post-processing parameters utilized in PWI studies of brain tumors thereby hampering comparability and reproducibility of results.

5. Amino Acid PET and DWI

Diffusion-weighted imaging (DWI) is an MRI technique based on the measurement of Brownian motion of water molecules to generate image contrast. DWI contrast uses two opposing gradient pulses; the first one induces a phase shift in water molecules, leading to a signal reduction. Subsequently, a second opposed gradient pulse is applied, which rephases the water molecules in the region of interest, leading to a recovery of the water signal. If water molecules moved out of the region of interest within the time between the two pulses, the number of water molecules contributing to the water signal is reduced. Therefore, the signal intensity is decreased. By variation of the amplitude, pulse duration, and time between the pulses, the degree of diffusion-weighting, represented by the b-value, can be altered. The apparent diffusion coefficient (ADC) is calculated from different b-values (typical range of b-values, 0–1000 s/mm2), and represents a quantitative measure of diffusivity [53]. In brain tumors, hypointense signals in ADC maps (indicating lower ADC values) are suspicious for neoplastic tissue due to high tumor cellularity leading to a restriction of diffusivity [6]. Several studies addressed the spatial congruency of DWI and amino acid PET in glioma patients with mixed results. Karavaeva and colleagues [54] demonstrated a significant spatial relationship of FDOPA uptake and ADC signal alterations at 1.5 T in patients with recurrent high-grade glioma. Furthermore, a significant spatial correlation of both ADC values and FDOPA uptake with the cellular proliferation rate was reported. However, it remains unclear whether the cellular proliferation rate was associated with tumor progression or treatment-related tissue reactions such as inflammatory processes. On the other hand, several other studies reported contradictory results concerning the spatial congruency of amino acid uptake and ADC abnormalities [55,56,57]. Recently, Popp and co-workers [57] showed that tumor volumes in patients with recurrent glioblastoma delineated using ADC maps acquired at 1.5 T were frequently localized outside of areas with increased FET uptake. Another study by Kinoshita [58] and colleagues reported that MET PET demonstrated a more robust and reliable estimation of cell density in gliomas compared to ADC maps acquired at 3 T. These controversial study results concerning the spatial congruency are most likely related to the fact that amino acid PET and DWI encode different biological properties [57,59] (Figure 3).
Figure 3

Contrast-enhanced (CE) T1-weighted MRI, FET PET and the apparent diffusion coefficient (ADC) map obtained from DWI in a patient with neuropathologically confirmed glioblastoma. In contrast to the ADC map, FET PET shows the metabolically active tumor tissue with high contrast. Furthermore, the ADC map shows slightly increased diffusivity in various subregions, erroneously indicating treatment-related changes.

Pyka and colleagues [49] compared FET PET and DWI at 3 T for the differentiation of tumor progression from treatment-related changes in 47 high-grade glioma patients. The authors reported a superior performance for FET PET compared to ADC (AUC, 0.86 vs. 0.69). The combination of FET PET and ADC with other MRI metrics such as rCBV resulted in an AUC improvement to 0.89. It should be pointed out that DWI has a low spatial resolution and a poor signal-to-noise ratio. Although stronger gradients and higher magnetic field strengths can increase signal-to-noise ratios, susceptibility artifacts would become concurrently more pronounced. Another limitation of DWI is the compromised reproducibility and comparability of ADC values, even when the same MR scanner is used [60]. Moreover, diffusivity can also be altered by ischemia, infection, inflammation, gliosis, necrosis, or vascular proliferation, suggesting non-specificity of DWI changes [6,61,62].

6. Amino Acid PET and CEST

Chemical exchange saturation transfer (CEST) is an MRI technique for the indirect detection of different metabolites using the MR free water signal [63]. CEST contrasts are based on the spontaneous exchange of free water protons and protons bound to metabolites (solute-bound protons). After saturation of solute-bound protons by the application of a radio-frequency pulse with a specific frequency depending on the metabolite of interest, these protons exchange with free water protons and cause a signal reduction of free water. Thus, the CEST signal depends upon the exchange rate between free water and solute-bound protons and the concentration of the metabolite of interest [64,65]. CEST has already been applied for the measurement of glycogen (GlycoCEST) [66], glucose (GlucoCEST) [67], glutamate (GluCEST) [68], amide proton transfer (APT) [69], and intracellular pH [69,70,71]. The signal used to generate CEST contrasts is complex and small. Therefore, CEST imaging may benefit from higher magnetic field strengths (> 3 T) due to an increased signal-to-noise ratio and spectral dispersion. However, complex data processing steps are required to evaluate metabolite concentrations from CEST contrasts [72,73,74,75]. Although several studies evaluated CEST in patients with GBM [75,76,77], only few studies directly compared amino acid PET and CEST in more than 5 patients. Da Silva et al. [78] compared FET PET and APT CEST MRI in 8 high-grade gliomas patients using a 3 T hybrid PET/MR scanner. The authors showed that FET PET and APT CEST are spatially incongruent and reflect different biological information. However, although CEST and amino acid PET were acquired simultaneously, the number of patients was low, and no correlation with local neuropathology was obtained.

7. Conclusions and Outlook

The combination of amino acid PET and advanced MRI methods offers a variety of new vistas for the assessment of brain tumors with the potential to overcome the limitations of conventional MRI. Amino acid PET and advanced MRI methods already provided promising results for the clinical management of patients with GBM. Both the complementary and additive value of these methods as well as their incongruent findings, suggesting differential biological information, warrant further investigation including neuropathological validation. The increasing advent of hybrid PET/MR scanners offers the great potential of comparative studies using both amino acid PET and advanced MRI in a single session. Furthermore, the clinical benefits of simultaneous PET/MR imaging need to be balanced against the relatively high cost of such an approach. Of note, the increasing availability of ultra-high field MRI scanners with magnetic field strengths of 7 T will help to develop novel techniques thereby promoting advanced MRI in neuro-oncology as almost all contrasts benefit from the higher spatial resolution related to the increased signal-to-noise ratio. Amino acid PET is a robust and attractive approach for clinicians for many reasons including easy scan reading. Furthermore, most studies using amino acid PET in neuro-oncology provide comparable results across different scanners, which is also a consequence of national and international efforts concerning the standardization of amino acid PET acquisition and evaluation in brain tumor imaging [24,79]. Recently, joint practice guidelines were developed by the European Association of Nuclear Medicine (EANM), the Society of Nuclear Medicine and Molecular Imaging (SNMMI), the European Association of Neuro-Oncology (EANO), and the working group for Response Assessment in Neuro-Oncology with PET (PET-RANO) [80]. In contrast, the yet missing standardization of advanced MRI methods is—at least in part—likely to account for conflicting data. In a significant number of advanced MRI studies, self-developed or self-optimized MR sequence protocols and acquisition parameters, as well as post-processing tools, were used, thereby impeding comparability and reproducibility of the results. Besides, vendors of MRI and PET scanners should strive for further standardization of imaging protocols and data processing since better comparability and easier reproducibility of the data is likely to boost their clinical value. Finally, further implementation of various advanced MRI methods as well as amino acid PET in clinical routine requires the validation of neuroimaging findings through neuropathology. To conclude, advanced MRI in combination with amino acid PET has the potential to become an essential diagnostic tool for improving the clinical management of patients with high-grade gliomas, as well as in light of emerging high-throughput analysis methods of large-scale data sets such as radiomics and machine learning [16,81,82].
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Authors:  Frank Willi Floeth; Dirk Pauleit; Hans-Jörg Wittsack; Karl Josef Langen; Guido Reifenberger; Kurt Hamacher; Martina Messing-Jünger; Karl Zilles; Friedrich Weber; Walter Stummer; Hans-Jakob Steiger; Gabriele Woebker; Hans-Wilhelm Müller; Heinz Coenen; Michael Sabel
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Review 1.  Application of 7T MRS to High-Grade Gliomas.

Authors:  L McCarthy; G Verma; G Hangel; A Neal; B A Moffat; J P Stockmann; O C Andronesi; P Balchandani; C G Hadjipanayis
Journal:  AJNR Am J Neuroradiol       Date:  2022-05-26       Impact factor: 4.966

2.  Maximizing the use of batch production of 18F-FDOPA for imaging of brain tumors to increase availability of hybrid PET/MR imaging in clinical setting.

Authors:  Mariam Aboian; Ramon Barajas; Julia Shatalov; Vahid Ravanfar; Emma Bahroos; Elizabeth Tong; Jennie W Taylor; N Oberheim Bush; Patricia Sneed; Youngho Seo; Soonmee Cha; Miguel Hernandez-Pampaloni
Journal:  Neurooncol Pract       Date:  2020-10-14

3.  Combined 18F-FET PET and diffusion kurtosis MRI in posttreatment glioblastoma: differentiation of true progression from treatment-related changes.

Authors:  Francesco D'Amore; Farida Grinberg; Jörg Mauler; Norbert Galldiks; Ganna Blazhenets; Ezequiel Farrher; Christian Filss; Gabriele Stoffels; Felix M Mottaghy; Philipp Lohmann; Nadim Jon Shah; Karl-Josef Langen
Journal:  Neurooncol Adv       Date:  2021-03-10

4.  CEST MRI provides amide/amine surrogate biomarkers for treatment-naïve glioma sub-typing.

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5.  Metabolic Tumor Volume Response Assessment Using (11)C-Methionine Positron Emission Tomography Identifies Glioblastoma Tumor Subregions That Predict Progression Better Than Baseline or Anatomic Magnetic Resonance Imaging Alone.

Authors:  Sean Miller; Pin Li; Matthew Schipper; Larry Junck; Morand Piert; Theodore S Lawrence; Christina Tsien; Yue Cao; Michelle M Kim
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Authors:  Norbert Galldiks; Frank Angenstein; Jan-Michael Werner; Elena K Bauer; Robin Gutsche; Gereon R Fink; Karl-Josef Langen; Philipp Lohmann
Journal:  Brain Pathol       Date:  2022-03       Impact factor: 6.508

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Authors:  Jules Tianyu Zhang-Yin; Antoine Girard; Marc Bertaux
Journal:  Cancers (Basel)       Date:  2022-02-10       Impact factor: 6.639

Review 9.  Identifying clinically applicable machine learning algorithms for glioma segmentation: recent advances and discoveries.

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Journal:  Neurooncol Adv       Date:  2022-06-14

10.  Radiomics-Based Machine Learning in Differentiation Between Glioblastoma and Metastatic Brain Tumors.

Authors:  Chaoyue Chen; Xuejin Ou; Jian Wang; Wen Guo; Xuelei Ma
Journal:  Front Oncol       Date:  2019-08-22       Impact factor: 6.244

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