Hybrid PET/MRI in Cerebral Glioma: Comparison
View Latest Version
Please note this is a comparison between Version 2 by Lindsay Dong and Version 1 by Gabriele Stoffels.

Advanced MRI methods and PET using radiolabelled amino acids provide valuable information in addition to conventional MR imaging for brain tumour diagnostics. The advent of hybrid PET/MRI has allowed a convergence of the methods, but up-to-date simultaneous imaging has reached little relevance in clinical neuro-oncology. A key factor for the benefit of PET/MRI in neuro-oncology is a multimodal approach that provides decisive improvements in the diagnostics of brain tumours compared with a single modality. 

  • brain tumour diagnosis
  • cerebral glioma
  • PET
  • radiolabelled amino acids

1. Introduction

Currently, the diagnosis of brain tumours is primarily based on contrast-enhanced MRI. Structural imaging using T1- and T2-weighted sequences provides high-resolution imaging of brain tumours and allows a differential diagnosis in a large fraction of lesions [1]. Differentiating tumour tissue from non-specific tissue changes, however, can be difficult, especially in cases of gliomas with diffusely infiltrating tumour growth, lack of contrast enhancement, and reactive tissue changes after surgery, radiotherapy, alkylating chemotherapy, or other experimental therapy approaches. In this situation, PET using radiolabelled amino acids can provide important additional diagnostic information [2]. The Response Assessment in Neuro-Oncology (RANO) Working Group has recommended the use of amino acid PET, in addition to MRI, in all stages of brain tumour management [3,4,5,6,7,8][3][4][5][6][7][8]. O-(2-[18F]-fluoroethyl)-L-tyrosine (18F-FET) was developed in our institution in the 1990s in order to provide a fluorine-18-labelled amino acid PET tracer with a longer half-life (110 min), which provides logistical advantages compared with shorter-lived carbon-11 labelled amino acids (half-life 20 min) such as [11C]-methyl-L-methionine [9,10,11][9][10][11].

2. PET Tracers for Brain Tumour Imaging

Today, radiolabelled amino acids are the preferred PET tracers in neuro-oncology [1]. Amino acid PET is helpful regarding differential diagnosis, classification and the prognostication of newly diagnosed brain tumours, the delineation of brain tumour extent for treatment planning, the assessment of treatment response and the differentiation of tumour recurrence or progression from treatment-related changes [1]. The most widely used amino acid tracers are [11C]-methyl-L-methionine (MET), 18F-FET and 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (18F-FDOPA), as described in previous publications from the RANO Group [3,4][3][4]. Furthermore, the synthetic amino acid analogue anti-1-amino-3-[18F]fluorocyclobutane-1-carboxylic acid (FACBC or Fluciclovine) has gained clinical interest for brain tumour imaging in recent years [25,26,27][12][13][14]. The uptake of these tracers in brain tumours is primarily dependent on the increased expression and functionality of large neutral amino acid transporters of the L-type (LAT, subtypes LAT1 and LAT2) [1]. In contrast to radiolabelled amino acids, the most widely used PET tracer 2-[18F]-fluorodeoxyglucose (18F-FDG) has a limited use in brain tumours because of the high glucose metabolism in normal brain tissue. The proliferation tracer [18F]-3′-deoxy-3′-fluorothymidine accumulates in cerebral gliomas in relation to the grade of malignancy and prognosis [29[15][16],30], but uptake is usually restricted to contrast-enhancing tumour parts on MRI and the tumour volume is smaller than that observed with amino acid tracers [31][17]. [11C]-choline or [18F]-fluoro-choline are markers of cell membrane phospholipids in brain tumours, but tracer uptake is also restricted to tumour parts with the disruption of the blood–brain barrier (BBB) [32][18]. A correlation of tracer uptake with the grade of malignancy has been reported [33[19][20],34], but the role of choline tracers in the primary diagnosis of brain tumours is limited, as the accumulation is not tumour-specific [35,36,37][21][22][23]. Another important approach for brain tumour imaging is the use of ligands for the mitochondrial translocator protein (TSPO), such as [11C]-PK11195, [18F]-GE-180 and [18F]-DPA-714 [45][24]. TSPO is overexpressed in activated microglia and macrophages, but also in glioma cells [46][25]. PET imaging of gliomas using TSPO ligands depicts tumours with high contrast compared with the normal brain [47][26], but discrimination between tumour mass and brain tissue appears to be critical at the tumour rim, where glia-associated microglia/macrophages may also show high tracer binding [48,49,50][27][28][29]. TSPO ligands accumulate in brain areas with intact BBB, but differences exist in the visualisation of tumour extent compared with amino acid PET [51][30].

3. Advanced MRI Methods in Neuro-Oncology

Advanced MRI methods can provide functional, physiologic and molecular information beyond conventional MRI, which may be helpful in equivocal findings [53][31]. A detailPed description of these methods is beyond the scope of this article, and therefore only a brief overview of the most important methods from this area is given. PWIrfusion-weighted MRI (PWI) either via dynamic susceptibility contrast (DSC) MRI, dynamic contrast-enhanced (DCE) MRI or arterial spin labeling (ASL) MRI provides several surrogate markers of tissue perfusion, such as relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), and other perfusion metrics [1,54,55][1][32][33]. In particular, rCBV mapping is a valuable supplement to conventional MRI in the differentiation of tumour progression or recurrence from treatment-related changes [56][34]. Proton MR spectroscopy (MRS) enables the non-invasive measurement of the signals of selected metabolites in vivo. Important metabolites for the characterisation of brain tumours are the neuronal marker N-acetyl-aspartate (NAA) and choline-containing compounds as cell membrane markers (Cho). MR spectroscopic imaging (MRSI) provides parameter maps, which visualise heterogenous distributions of different metabolites, or ratios thereof, in larger volumes of the brain [57][35]. Diffusion-weighted imaging (DWI) is based upon the random Brownian motion of water molecules within a voxel of tissue, which can be quantified, for example, by the apparent diffusion coefficient (ADC) [58][36]. In brain tumours, the ADC is inversely correlated with cell density, probably due to reduced water mobility from dense cellular packing. Diffusion kurtosis imaging (DKI) is an advanced neuroimaging modality that is an extension of diffusion tensor imaging by estimating the kurtosis (skewed distribution) of water diffusion based on a probability distribution function [59][37].

4. Hybrid PET/MRI in Animal Research

Hybrid PET/MRI has been successfully used in preclinical neuroimaging to correlate changes in neuronal activity using fMRI and changes in receptor expression and neurotransmitter binding [66,67,68,69][38][39][40][41]. Simultaneous PET/MRI imaging is essential for these examinations, as neuronal activations in temporally separate examinations are not comparable and do not permit any reliable conclusions. Moreover, several studies have used combined PET and MRI in animal brain tumour models to explore novel PET tracers and advanced MR methods for brain tumour diagnosis, but the investigations have used mainly sequential PET/MRI [70,71,72,73,74][42][43][44][45][46]. Previous review articles have made suggestions as to the expectation that simultaneous hybrid PET/MRI will be used for the modelling of physiological and biochemical processes, because during the simultaneous acquisition one can be sure the prevailing physiological conditions such as blood flow and perfusion, pertain to both the PET and MRI measurements [75][47]. However, there has been little implementation in experimental brain tumour research to date.

5. Hybrid PET/MRI in Newly Diagnosed Cerebral Gliomas

In brain lesions suspicious for neoplasms, conventional MRI is frequently inconclusive and additional imaging methods can be helpful. This concerns differential diagnosis, the definition of an optimal biopsy site, and the detection of tumour infiltration, especially in tumours without contrast enhancement in MRI. Furthermore, the non-invasive classification of tumours and the assessment of molecular features and prognostication can be valuable if neuropathological assessment is not possible. Pyka et al. investigated the value of combined 18F-FET PET and MRS in a series of 67 patients with newly diagnosed gliomas [77][48]. Static 18F-FET PET allowed the differentiation of low-grade and high-grade gliomas with an area under the curve (AUC) in receiver operating characteristics analysis (ROC) of 0.86 and MRS using the Cho/NAA with an AUC of 0.72. The combination of 18F-FET PET and MRS achieved an AUC of 0.97. Furthermore, the multimodal approach was able to differentiate glioblastoma from non-glioblastoma with an AUC of 0.97. In the survival analysis, PET parameters (but not spectroscopy) were significantly correlated with overall survival. Song et al. reported that the combination of 18F-FET PET and DSC-PWI increased the diagnostic accuracy to differentiate gliomas with and without IDH mutation (AUC 0.90) compared with the single modalities (18F-FET PET and rCBV, each AUC 0.80), but none of the parameters discriminated between oligodendrogliomas and astrocytomas [78][49]. Summarising, there is some evidence that combined amino acid PET and advanced MRI is helpful in improving the non-invasive characterisation of suspected gliomas. Concerning tumour delineation, amino acid PET appears to be the most reliable method to identify metabolically active tumour tissue, and so far there is little evidence that the combination with advanced MR methods leads to superior results.

6. Hybrid PET/MRI in Patients with Recurrent Gliomas

Most studies investigating multimodal PET/MRI to differentiate brain tumour progression or recurrence from treatment-related changes have compared PWI with amino acid PET. While some older publications reported the superiority or equivalence of rCBV mapping compared with amino acid PET [94[50][51][52],95,96], more recent publications consistently observed the superiority of amino acid PET [97,98,99][53][54][55]. Recently, scholars analysed the additive value of 18F-FET PET and perfusion-weighted MRI in a group of 104 patients with suspected glioma recurrence [100][56]. Eighty-three patients had tumour progression and 21 patients had treatment-related changes. The combination of 18F-FET PET and PWI did not increase the diagnostic power, but an rCBVmax > 2.85 reached a positive predictive value of 100% so that 44 patients could be correctly classified using rCBVmax alone. In the remaining patients, 18F-FET PET still achieved an accuracy of 78%, so that 87% of the patients could be correctly diagnosed, in total. These results support the sequential use of PWI and amino acid PET, particularly when a more economical use of the diagnostic methods has priority. In contrast, one study using 11C-MET PET reported on an additive value of amino acid PET and DSC-PWI [101][57]. While both the maximum tumour-to-brain ratio (TBRmax) of 11C-MET uptake and mean rCBV achieved an AUC of 0.85, the combination of the parameters yielded an AUC of 0.95 in the differentiation tumour recurrence from radiation injury. Furthermore, a number of studies have reported the additive value of amino acid PET and MRI when including advanced MRI methods other than rCBV in patients with suspected tumour recurrence. Jena et al. achieved the highest accuracy (97%) in differentiating recurrent tumours from radiation necrosis when combining the TBRmax of 18F-FET uptake and MRS using the Cho/Cr ratio [102][58]. An identical accuracy of 97% was achieved by Sogani et al. with a combination of 18F-FET PET, MRS, PWI and DWI [103][59], and a hybrid PET/MRI study achieved an accuracy of 95% using 18F-FDOPA as the amino acid tracer [104][60]. Another hybrid PET/MRI study compared dynamic 18F-FET PET, PWI, and DWI in 47 patients with suspected glioma recurrence [105][61]. Static 18F-FET PET alone achieved an AUC of 0.86 for differentiating recurrent tumour and treatment-related changes, which could be increased to an AUC of 0.89 when combined with PWI and DWI. Lohmeier et al. reported the highest AUC by using a combination of static 18F-FET PET and ADC (0.90) versus 18F-FET PET (0.81) or ADC alone (0.82) [106][62]. These results could not be confirmed by Werner et al., who reported the highest accuracy using static and dynamic 18F-FET PET parameters (93%), which could not be further improved by ADC mapping [107][63]. Few data exist concerning the additive value of amino acid PET and advanced MR methods in terms of response assessment. A recent study reported that the simultaneous evaluation of 18F-FET PET and ADC metrics using PET/MRI allowed the early and reliable identification of treatment responses and predicted overall survival in recurrent glioblastoma patients treated with regorafenib [111][64]. A key aspect in thise study was the fact that the authors used pathological 18F-FET uptake to define the region of interest (ROI) on the ADC maps. The authors emphasised that radiological recommendations do not provide a strategy for identifying the ROI on the DWI-ADC images or how to define the threshold for pathological ADC values. Thus, a PET-guided evaluation strategy for advanced MRI methods is another important aspect for the use of PET/MRI and also played a decisive role in the combined use of 18F-FET PET and DKI mentioned above [109][65]. 

7. Hybrid PET/MRI in Paediatric Brain Tumours

The use of hybrid PET/MRI appears particularly advantageous in paediatric patients, in order to reduce the examination time, to avoid radiation exposure from the CT scanner, and to prevent repeated general anaesthesia in separate measurements [112,113][66][67]. Furthermore, the fusion of separately acquired PET and MRI data may cause more problems in children than in adults owing to the fact that paediatric tumours are frequently located in the cerebellum and medulla or by high extra cerebral 18F-FET uptake in the cranial bone marrow [18][68]. On the other hand, the logistics of anaesthesia in the hybrid scanner are challenging, especially in younger children, and attenuation correction in children causes problems [18][68] as MR-based attenuation methods often are built upon reference data sets acquired in adult subjects [114,115][69][70].

References

  1. Langen, K.J.; Galldiks, N.; Hattingen, E.; Shah, N.J. Advances in neuro-oncology imaging. Nat. Rev. Neurol. 2017, 13, 279–289.
  2. Galldiks, N.; Lohmann, P.; Albert, N.L.; Tonn, J.C.; Langen, K.J. Current status of PET imaging in neuro-oncology. Neuro-Oncol. Adv. 2019, 1, vdz010.
  3. Albert, N.L.; Weller, M.; Suchorska, B.; Galldiks, N.; Soffietti, R.; Kim, M.M.; la Fougere, C.; Pope, W.; Law, I.; Arbizu, J.; 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-Oncology 2016, 18, 1199–1208.
  4. Law, I.; Albert, N.L.; Arbizu, J.; Boellaard, R.; Drzezga, A.; Galldiks, N.; la Fougere, C.; Langen, K.J.; Lopci, E.; Lowe, V.; et al. Joint EANM/EANO/RANO practice guidelines/SNMMI procedure standards for imaging of gliomas using PET with radiolabelled amino acids and FDG: Version 1.0. Eur. J. Nucl. Med. Mol. Imaging 2019, 46, 540–557.
  5. Galldiks, N.; Langen, K.J.; Albert, N.L.; Chamberlain, M.; Soffietti, R.; Kim, M.M.; Law, I.; Le Rhun, E.; Chang, S.; Schwarting, J.; et al. PET imaging in patients with brain metastasis-report of the RANO/PET group. Neuro-Oncology 2019, 21, 585–595.
  6. Galldiks, N.; Langen, K.J.; Albert, N.L.; Law, I.; Kim, M.M.; Villanueva-Meyer, J.E.; Soffietti, R.; Wen, P.Y.; Weller, M.; Tonn, J.C. Investigational PET tracers in neuro-oncology-What’s on the horizon? A report of the PET/RANO group. Neuro-Oncology 2022, 24, 1815–1826.
  7. Piccardo, A.; Albert, N.L.; Borgwardt, L.; Fahey, F.H.; Hargrave, D.; Galldiks, N.; Jehanno, N.; Kurch, L.; Law, I.; Lim, R.; et al. Joint EANM/SIOPE/RAPNO practice guidelines/SNMMI procedure standards for imaging of paediatric gliomas using PET with radiolabelled amino acids and FDG: Version 1.0. Eur. J. Nucl. Med. Mol. Imaging 2022, 49, 3852–3869.
  8. Galldiks, N.; Niyazi, M.; Grosu, A.L.; Kocher, M.; Langen, K.J.; Law, I.; Minniti, G.; Kim, M.M.; Tsien, C.; Dhermain, F.; et al. Contribution of PET imaging to radiotherapy planning and monitoring in glioma patients—A report of the PET/RANO group. Neuro-Oncology 2021, 23, 881–893.
  9. Wester, H.J.; Herz, M.; Weber, W.; Heiss, P.; Senekowitsch-Schmidtke, R.; Schwaiger, M.; Stocklin, G. Synthesis and radiopharmacology of O-(2-fluoroethyl)-L-tyrosine for tumor imaging. J. Nucl. Med. Off. Publ. Soc. Nucl. Med. 1999, 40, 205–212.
  10. Langen, K.J.; Hamacher, K.; Weckesser, M.; Floeth, F.; Stoffels, G.; Bauer, D.; Coenen, H.H.; Pauleit, D. O-(2-fluoroethyl)-L-tyrosine: Uptake mechanisms and clinical applications. Nucl. Med. Biol. 2006, 33, 287–294.
  11. Hamacher, K.; Coenen, H.H. Efficient routine production of the 18F-labelled amino acid O-2-18F fluoroethyl-L-tyrosine. Appl. Radiat. Isot. Incl. Data Instrum. Methods Use Agric. Ind. Med. 2002, 57, 853–856.
  12. Albano, D.; Tomasini, D.; Bonu, M.; Giubbini, R.; Bertagna, F. 18F-Fluciclovine (18F-FACBC) PET/CT or PET/MRI in gliomas/glioblastomas. Ann. Nucl. Med. 2020, 34, 81–86.
  13. Tsuyuguchi, N.; Terakawa, Y.; Uda, T.; Nakajo, K.; Kanemura, Y. Diagnosis of Brain Tumors Using Amino Acid Transport PET Imaging with 18F-fluciclovine: A Comparative Study with L-methyl-11C-methionine PET Imaging. Asia Ocean. J. Nucl. Med. Biol. 2017, 5, 85–94.
  14. Wakabayashi, T.; Hirose, Y.; Miyake, K.; Arakawa, Y.; Kagawa, N.; Nariai, T.; Narita, Y.; Nishikawa, R.; Tsuyuguchi, N.; Fukami, T.; et al. Determining the extent of tumor resection at surgical planning with 18F-fluciclovine PET/CT in patients with suspected glioma: Multicenter phase III trials. Ann. Nucl. Med. 2021, 35, 1279–1292.
  15. Collet, S.; Valable, S.; Constans, J.M.; Lechapt-Zalcman, E.; Roussel, S.; Delcroix, N.; Abbas, A.; Ibazizene, M.; Bernaudin, M.; Barre, L.; et al. -fluoro-L-thymidine PET and advanced MRI for preoperative grading of gliomas. NeuroImage Clin. 2015, 8, 448–454.
  16. Mitamura, K.; Yamamoto, Y.; Kudomi, N.; Maeda, Y.; Norikane, T.; Miyake, K.; Nishiyama, Y. Intratumoral heterogeneity of 18F-FLT uptake predicts proliferation and survival in patients with newly diagnosed gliomas. Ann. Nucl. Med. 2017, 31, 46–52.
  17. Nowosielski, M.; DiFranco, M.D.; Putzer, D.; Seiz, M.; Recheis, W.; Jacobs, A.H.; Stockhammer, G.; Hutterer, M. An intra-individual comparison of MRI, -FET and -FLT PET in patients with high-grade gliomas. PLoS ONE 2014, 9, e95830.
  18. Sollini, M.; Sghedoni, R.; Erba, P.A.; Cavuto, S.; Froio, A.; De Berti, G.; Pisanello, A.; Fraternali, A.; Iori, M.; Iaccarino, C.; et al. Diagnostic performances of fluorocholine positron emission tomography in brain tumors. Q. J. Nucl. Med. Mol. Imaging 2015. epub ahead of print.
  19. Kwee, S.A.; Ko, J.P.; Jiang, C.S.; Watters, M.R.; Coel, M.N. Solitary brain lesions enhancing at MR imaging: Evaluation with fluorine 18 fluorocholine PET. Radiology 2007, 244, 557–565.
  20. Ohtani, T.; Kurihara, H.; Ishiuchi, S.; Saito, N.; Oriuchi, N.; Inoue, T.; Sasaki, T. Brain tumour imaging with carbon-11 choline: Comparison with FDG PET and gadolinium-enhanced MR imaging. Eur. J. Nucl. Med. 2001, 28, 1664–1670.
  21. Calabria, F.F.; Barbarisi, M.; Gangemi, V.; Grillea, G.; Cascini, G.L. Molecular imaging of brain tumors with radiolabeled choline PET. Neurosurg. Rev. 2018, 41, 67–76.
  22. Van Waarde, A.; Jager, P.L.; Ishiwata, K.; Dierckx, R.A.; Elsinga, P.H. Comparison of sigma-ligands and metabolic PET tracers for differentiating tumor from inflammation. J. Nucl. Med. Off. Publ. Soc. Nucl. Med. 2006, 47, 150–154.
  23. Huang, Z.; Zuo, C.; Guan, Y.; Zhang, Z.; Liu, P.; Xue, F.; Lin, X. Misdiagnoses of 11C-choline combined with 18F-FDG PET imaging in brain tumours. Nucl. Med. Commun. 2008, 29, 354–358.
  24. Werner, J.M.; Lohmann, P.; Fink, G.R.; Langen, K.J.; Galldiks, N. Current Landscape and Emerging Fields of PET Imaging in Patients with Brain Tumors. Molecules 2020, 25, 1471.
  25. Ammer, L.M.; Vollmann-Zwerenz, A.; Ruf, V.; Wetzel, C.H.; Riemenschneider, M.J.; Albert, N.L.; Beckhove, P.; Hau, P. The Role of Translocator Protein TSPO in Hallmarks of Glioblastoma. Cancers 2020, 12, 2973.
  26. Albert, N.L.; Unterrainer, M.; Fleischmann, D.F.; Lindner, S.; Vettermann, F.; Brunegraf, A.; Vomacka, L.; Brendel, M.; Wenter, V.; Wetzel, C.; et al. TSPO PET for glioma imaging using the novel ligand 18F-GE-180: First results in patients with glioblastoma. Eur. J. Nucl. Med. Mol. Imaging 2017, 44, 2230–2238.
  27. Langen, K.J.; Willuweit, A. TSPO PET using 18F-GE-180: A new perspective in neurooncology? Eur. J. Nucl. Med. Mol. Imaging 2017, 44, 2227–2229.
  28. Roncaroli, F.; Su, Z.; Herholz, K.; Gerhard, A.; Turkheimer, F.E. TSPO expression in brain tumours: Is TSPO a target for brain tumour imaging? Clin. Transl. Imaging 2016, 4, 145–156.
  29. Zinnhardt, B.; Roncaroli, F.; Foray, C.; Agushi, E.; Osrah, B.; Hugon, G.; Jacobs, A.H.; Winkeler, A. Imaging of the glioma microenvironment by TSPO PET. Eur. J. Nucl. Med. Mol. Imaging 2021, 49, 174–185.
  30. Unterrainer, M.; Fleischmann, D.F.; Diekmann, C.; Vomacka, L.; Lindner, S.; Vettermann, F.; Brendel, M.; Wenter, V.; Ertl-Wagner, B.; Herms, J.; et al. Comparison of 18F-GE-180 and dynamic 18F-FET PET in high grade glioma: A double-tracer pilot study. Eur. J. Nucl. Med. Mol. Imaging 2019, 46, 580–590.
  31. Herholz, K.; Coope, D.; Jackson, A. Metabolic and molecular imaging in neuro-oncology. Lancet Neurol. 2007, 6, 711–724.
  32. Lohmann, P.; Werner, J.M.; Shah, N.J.; Fink, G.R.; Langen, K.J.; Galldiks, N. Combined Amino Acid Positron Emission Tomography and Advanced Magnetic Resonance Imaging in Glioma Patients. Cancers 2019, 11, 153.
  33. Warmuth, C.; Gunther, M.; Zimmer, C. Quantification of blood flow in brain tumors: Comparison of arterial spin labeling and dynamic susceptibility-weighted contrast-enhanced MR imaging. Radiology 2003, 228, 523–532.
  34. Patel, P.; Baradaran, H.; Delgado, D.; Askin, G.; Christos, P.; Tsiouris, A.J.; Gupta, A. MR perfusion-weighted imaging in the evaluation of high-grade gliomas after treatment: A systematic review and meta-analysis. Neuro-Oncology 2016, 19, 118–127.
  35. Aseel, A.; McCarthy, P.; Mohammed, A. Brain magnetic resonance spectroscopy to differentiate recurrent neoplasm from radiation necrosis: A systematic review and meta-analysis. J. Neuroimaging 2023, 33, 189–201.
  36. Koh, D.M.; Padhani, A.R. Diffusion-weighted MRI: A new functional clinical technique for tumour imaging. Br. J. Radiol. 2006, 79, 633–635.
  37. Jensen, J.H.; Helpern, J.A.; Ramani, A.; Lu, H.; Kaczynski, K. Diffusional kurtosis imaging: The quantification of non-gaussian water diffusion by means of magnetic resonance imaging. Magn. Reson. Med. 2005, 53, 1432–1440.
  38. Ionescu, T.M.; Amend, M.; Hafiz, R.; Biswal, B.B.; Maurer, A.; Pichler, B.J.; Wehrl, H.F.; Herfert, K. Striatal and prefrontal D2R and SERT distributions contrastingly correlate with default-mode connectivity. NeuroImage 2021, 243, 118501.
  39. Ionescu, T.M.; Amend, M.; Hafiz, R.; Biswal, B.B.; Wehrl, H.F.; Herfert, K.; Pichler, B.J. Elucidating the complementarity of resting-state networks derived from dynamic FDG and hemodynamic fluctuations using simultaneous small-animal PET/MRI. NeuroImage 2021, 236, 118045.
  40. Ionescu, T.M.; Amend, M.; Watabe, T.; Hatazawa, J.; Maurer, A.; Reischl, G.; Pichler, B.J.; Wehrl, H.F.; Herfert, K. Neurovascular Uncoupling: Multimodal Imaging Delineates the Acute Effects of 3,4-Methylenedioxymethamphetamine. J. Nucl. Med. Off. Publ. Soc. Nucl. Med. 2023, 64, 466–471.
  41. Vidal, B.; Fieux, S.; Redoute, J.; Villien, M.; Bonnefoi, F.; Le Bars, D.; Newman-Tancredi, A.; Costes, N.; Zimmer, L. In vivo biased agonism at 5-HT(1A) receptors: Characterisation by simultaneous PET/MR imaging. Neuropsychopharmacol. Off. Publ. Am. Coll. Neuropsychopharmacol. 2018, 43, 2310–2319.
  42. Stegmayr, C.; Bandelow, U.; Oliveira, D.; Lohmann, P.; Willuweit, A.; Filss, C.; Galldiks, N.; Lubke, J.H.; Shah, N.J.; Ermert, J.; et al. Influence of blood-brain barrier permeability on O-(2-18F-fluoroethyl)-L-tyrosine uptake in rat gliomas. Eur. J. Nucl. Med. Mol. Imaging 2017, 44, 408–416.
  43. Stegmayr, C.; Oliveira, D.; Niemietz, N.; Willuweit, A.; Lohmann, P.; Galldiks, N.; Shah, N.J.; Ermert, J.; Langen, K.J. Influence of Bevacizumab on Blood-Brain Barrier Permeability and O-(2-18F-Fluoroethyl)-l-Tyrosine Uptake in Rat Gliomas. J. Nucl. Med. Off. Publ. Soc. Nucl. Med. 2017, 58, 700–705.
  44. Stegmayr, C.; Bandelow, U.; Oliveira, D.; Lohmann, P.; Willuweit, A.; Filss, C.; Galldiks, N.; Lübke, J.H.R.; Shah, N.J.; Ermert, J.; et al. O-(2-fluoroethyl)-L-tyrosine uptake and blood-brain barrier permeability under anti-angiogenic therapy in rat glioma models. J. Nucl. Med. Off. Publ. Soc. Nucl. Med. 2017, 57 (Suppl. 2), 350.
  45. Jackson, L.R.; Masi, M.R.; Selman, B.M.; Sandusky, G.E.; Zarrinmayeh, H.; Das, S.K.; Maharjan, S.; Wang, N.; Zheng, Q.H.; Pollok, K.E.; et al. Use of multimodality imaging, histology, and treatment feasibility to characterize a transgenic Rag2-null rat model of glioblastoma. Front. Oncol. 2022, 12, 939260.
  46. Verhoeven, J.; Baguet, T.; Piron, S.; Pauwelyn, G.; Bouckaert, C.; Descamps, B.; Raedt, R.; Vanhove, C.; De Vos, F.; Goethals, I. 2-FELP, a novel LAT1-specific PET tracer, for the discrimination between glioblastoma, radiation necrosis and inflammation. Nucl. Med. Biol. 2020, 82–83, 9–16.
  47. Wehrl, H.F.; Wiehr, S.; Divine, M.R.; Gatidis, S.; Gullberg, G.T.; Maier, F.C.; Rolle, A.M.; Schwenck, J.; Thaiss, W.M.; Pichler, B.J. Preclinical and Translational PET/MR Imaging. J. Nucl. Med. Off. Publ. Soc. Nucl. Med. 2014, 55, 11S–18S.
  48. Pyka, T.; Krzyzanowska, I.; Rominger, A.; Delbridge, C.; Meyer, B.; Boeckh-Behrens, T.; Zimmer, C.; Gempt, J. Multiparametric Characterization of Intracranial Gliomas Using Dynamic FET-PET and Magnetic Resonance Spectroscopy. Diagnostics 2022, 12, 2331.
  49. Song, S.; Wang, L.; Yang, H.; Shan, Y.; Cheng, Y.; Xu, L.; Dong, C.; Zhao, G.; Lu, J. Static 18F-FET PET and DSC-PWI based on hybrid PET/MR for the prediction of gliomas defined by IDH and 1p/19q status. Eur. Radiol. 2021, 31, 4087–4096.
  50. D’Souza, M.M.; Sharma, R.; Jaimini, A.; Panwar, P.; Saw, S.; Kaur, P.; Mondal, A.; Mishra, A.; Tripathi, R.P. 11C-MET PET/CT and advanced MRI in the evaluation of tumor recurrence in high-grade gliomas. Clin. Nucl. Med. 2014, 39, 791–798.
  51. Dandois, V.; Rommel, D.; Renard, L.; Jamart, J.; Cosnard, G. Substitution of 11C-methionine PET by perfusion MRI during the follow-up of treated high-grade gliomas: Preliminary results in clinical practice. J. Neuroradiol. J. De. Neuroradiol. 2010, 37, 89–97.
  52. Kim, Y.H.; Oh, S.W.; Lim, Y.J.; Park, C.K.; Lee, S.H.; Kang, K.W.; Jung, H.W.; Chang, K.H. Differentiating radiation necrosis from tumor recurrence in high-grade gliomas: Assessing the efficacy of 18F-FDG PET, 11C-methionine PET and perfusion MRI. Clin. Neurol. Neurosurg. 2010, 112, 758–765.
  53. Deuschl, C.; Kirchner, J.; Poeppel, T.D.; Schaarschmidt, B.; Kebir, S.; El Hindy, N.; Hense, J.; Quick, H.H.; Glas, M.; Herrmann, K.; et al. 11C-MET PET/MRI for detection of recurrent glioma. Eur. J. Nucl. Med. Mol. Imaging 2018, 45, 593–601.
  54. Verger, A.; Filss, C.P.; Lohmann, P.; Stoffels, G.; Sabel, M.; Wittsack, H.J.; Kops, E.R.; Galldiks, N.; Fink, G.R.; Shah, N.J.; et al. Comparison of O-(2-18F-Fluoroethyl)-L-Tyrosine Positron Emission Tomography and Perfusion-Weighted Magnetic Resonance Imaging in the Diagnosis of Patients with Progressive and Recurrent Glioma: A Hybrid Positron Emission Tomography/Magnetic Resonance Study. World Neurosurg. 2018, 113, e727–e737.
  55. Henriksen, O.M.; Hansen, A.E.; Muhic, A.; Marner, L.; Madsen, K.; Moller, S.; Hasselbalch, B.; Lundemann, M.J.; Scheie, D.; Skjoth-Rasmussen, J.; et al. Diagnostic yield of simultaneous dynamic contrast-enhanced magnetic resonance perfusion measurements and FET PET in patients with suspected recurrent anaplastic astrocytoma and glioblastoma. Eur. J. Nucl. Med. Mol. Imaging 2022, 49, 4677–4691.
  56. Steidl, E.; Langen, K.J.; Hmeidan, S.A.; Polomac, N.; Filss, C.P.; Galldiks, N.; Lohmann, P.; Keil, F.; Filipski, K.; Mottaghy, F.M.; et al. Sequential implementation of DSC-MR perfusion and dynamic FET PET allows efficient differentiation of glioma progression from treatment-related changes. Eur. J. Nucl. Med. Mol. Imaging 2021, 48, 1956–1965.
  57. Qiao, Z.; Zhao, X.; Wang, K.; Zhang, Y.; Fan, D.; Yu, T.; Shen, H.; Chen, Q.; Ai, L. Utility of Dynamic Susceptibility Contrast Perfusion-Weighted MR Imaging and 11C-Methionine PET/CT for Differentiation of Tumor Recurrence from Radiation Injury in Patients with High-Grade Gliomas. AJNR. Am. J. Neuroradiol. 2019, 40, 253–259.
  58. Jena, A.; Taneja, S.; Gambhir, A.; Mishra, A.K.; D’Souza, M.M.; Verma, S.M.; Hazari, P.P.; Negi, P.; Jhadav, G.K.; Sogani, S.K. Glioma Recurrence Versus Radiation Necrosis: Single-Session Multiparametric Approach Using Simultaneous O-(2-18F-Fluoroethyl)-L-Tyrosine PET/MRI. Clin. Nucl. Med. 2016, 41, e228–e236.
  59. Sogani, S.K.; Jena, A.; Taneja, S.; Gambhir, A.; Mishra, A.K.; D’Souza, M.M.; Verma, S.M.; Hazari, P.P.; Negi, P.; Jadhav, G.K. Potential for differentiation of glioma recurrence from radionecrosis using integrated 18F-fluoroethyl-L-tyrosine (FET) positron emission tomography/magnetic resonance imaging: A prospective evaluation. Neurol. India 2017, 65, 293–301.
  60. Jena, A.; Taneja, S.; Khan, A.A.; Sogani, S.K. Recurrent Glioma: Does Qualitative Simultaneous 18F-DOPA PET/mp-MRI Improve Diagnostic Workup? An Initial Experience. Clin. Nucl. Med. 2021, 46, 703–709.
  61. Pyka, T.; Hiob, D.; Preibisch, C.; Gempt, J.; Wiestler, B.; Schlegel, J.; Straube, C.; Zimmer, C. Diagnosis of glioma recurrence using multiparametric dynamic 18F-fluoroethyl-tyrosine PET-MRI. Eur. J. Radiol. 2018, 103, 32–37.
  62. Lohmeier, J.; Bohner, G.; Siebert, E.; Brenner, W.; Hamm, B.; Makowski, M.R. Quantitative biparametric analysis of hybrid 18F-FET PET/MR-neuroimaging for differentiation between treatment response and recurrent glioma. Sci. Rep. 2019, 9, 14603.
  63. Werner, J.M.; Stoffels, G.; Lichtenstein, T.; Borggrefe, J.; Lohmann, P.; Ceccon, G.; Shah, N.J.; Fink, G.R.; Langen, K.J.; Kabbasch, C.; et al. Differentiation of treatment-related changes from tumour progression: A direct comparison between dynamic FET PET and ADC values obtained from DWI MRI. Eur. J. Nucl. Med. Mol. Imaging 2019, 46, 1889–1901.
  64. Lombardi, G.; Spimpolo, A.; Berti, S.; Campi, C.; Anglani, M.G.; Simeone, R.; Evangelista, L.; Causin, F.; Zorzi, G.; Gorgoni, G.; et al. PET/MR in recurrent glioblastoma patients treated with regorafenib: FET and DWI-ADC for response assessment and survival prediction. Br. J. Radiol. 2022, 95, 20211018.
  65. D’Amore, F.; Grinberg, F.; Mauler, J.; Galldiks, N.; Blazhenets, G.; Farrher, E.; Filss, C.; Stoffels, G.; Mottaghy, F.M.; Lohmann, P.; et al. Combined 18F-FET PET and diffusion kurtosis MRI in posttreatment glioblastoma: Differentiation of true progression from treatment-related changes. Neurooncol Adv. 2021, 3, vdab044.
  66. Marner, L.; Nysom, K.; Sehested, A.; Borgwardt, L.; Mathiasen, R.; Henriksen, O.M.; Lundemann, M.; Munck Af Rosenschold, P.; Thomsen, C.; Bogeskov, L.; et al. Early Postoperative 18F-FET PET/MRI for Pediatric Brain and Spinal Cord Tumors. J. Nucl. Med. Off. Publ. Soc. Nucl. Med. 2019, 60, 1053–1058.
  67. Marner, L.; Lundemann, M.; Sehested, A.; Nysom, K.; Borgwardt, L.; Mathiasen, R.; Wehner, P.S.; Henriksen, O.M.; Thomsen, C.; Skjoth-Rasmussen, J.; et al. Diagnostic Accuracy and Clinical Impact of FET PET in Childhood CNS tumors. Neuro-Oncology 2021, 23, 2107–2116.
  68. Marner, L.; Henriksen, O.M.; Lundemann, M.; Larsen, V.A.; Law, I. Clinical PET/MRI in neurooncology: Opportunities and challenges from a single-institution perspective. Clin. Transl. Imaging 2017, 5, 135–149.
  69. Bezrukov, I.; Schmidt, H.; Gatidis, S.; Mantlik, F.; Schafer, J.F.; Schwenzer, N.; Pichler, B.J. Quantitative Evaluation of Segmentation- and Atlas-Based Attenuation Correction for PET/MR on Pediatric Patients. J. Nucl. Med. Off. Publ. Soc. Nucl. Med. 2015, 56, 1067–1074.
  70. Ladefoged, C.N.; Law, I.; Anazodo, U.; St Lawrence, K.; Izquierdo-Garcia, D.; Catana, C.; Burgos, N.; Cardoso, M.J.; Ourselin, S.; Hutton, B.; et al. A multi-centre evaluation of eleven clinically feasible brain PET/MRI attenuation correction techniques using a large cohort of patients. NeuroImage 2017, 147, 346–359.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
Video Production Service
Feedback