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Amino Acid PET Imaging of Glioma

  • Nuclear Medicine & PET/CT Imaging (R Flavell, Section Editor)
  • Published:
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Abstract

Purpose of Review

Gliomas are among the most lethal malignancies in the world with dismal outcomes for high-grade tumors. These lesions are difficult to completely characterize with conventional magnetic resonance imaging and amino acid positron emission tomography is a rapidly progressing area of research with widespread clinical use.

Recent Findings

Amino acid positron emission tomography allows for more accurate glioma characterization compared to traditional imaging techniques including grading of disease, delineation of tumor spread, identification of recurrent disease, and prognosis. While the summarized radiotracers share some diagnostic properties, each also has its own weaknesses and strengths.

Summary

This article summarizes recent developments and clinical applications of the most widely used amino acid radiotracers. While none of these agents are FDA approved in the United States, they are considered standard of care in Europe and other parts of the world with > 10,000 studies being performed in some centers (Langen et al. in J Neurooncol 120(3):665–666, 2014).

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Fig. 1
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Fig. 4

Image courtesy of Csaba Juhasz MD.PhD., Wayne State University School of Medicine. Detroit MI (Color figure online)

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Abbreviations

AA:

Amino acid

HGG:

High-grade glioma

LGG:

Low-grade glioma

TBR:

Tumor-to-background ratio

MTV:

Metabolic tumor volume

MET:

l-[Methyl-11C]-methionine

FET:

[18F]Fluoro-ethyltyrosine

FDOPA:

3,4-Dihydroxy-6-[18F] fluoro-l-phenylalanine

Fluciclovine:

Anti-1-amino-3- [18F]-fluorocyclobutane-1-carboxylic acid

AMT:

Α-[11C]-methyl-l-tryptophan

PFS:

Progression-free survival

OS:

Overall survival

References

Papers of particular interest, published recently, have been highlighted as: • Of importance.

  1. Langen KJ, Tonn JC, Weller M, Galldiks N. Letter to the Editor: “The role of imaging in the management of progressive glioblastoma. A systematic review and evidence-based clinical practice guideline” [J Neurooncol 2014; 118:435–60]. J Neurooncol. 2014;120(3):665–6. https://doi.org/10.1007/s11060-014-1594-z.

    Article  PubMed  Google Scholar 

  2. • Ostrom QT, Gittleman H, Fulop J, Liu M, Blanda R, Kromer C, et al. CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2008–2012. Neuro Oncol. 2015;17(Suppl 4):iv1–62. https://doi.org/10.1093/neuonc/nov189. Provides a comprehensive summary of the current descriptive epidemiology of primary brain and central nervous system tumors in the United States. Incidence counts and rates of primary malignant and non-malignant brain and CNS tumors are documented by histology, gender, age, and race.

    Article  Google Scholar 

  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 Oncology. 2017;18(6):E315–29. https://doi.org/10.1016/S1470-2045(17)30194-8.

    Article  PubMed  Google Scholar 

  4. 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(11):1963–72. https://doi.org/10.1200/JCO.2009.26.3541.

    Article  PubMed  Google Scholar 

  5. Radbruch A, Lutz K, Wiestler B, Baumer P, Heiland S, Wick W, et al. Relevance of T2 signal changes in the assessment of progression of glioblastoma according to the response assessment in neurooncology criteria. Neuro Oncol. 2012;14(2):222–9. https://doi.org/10.1093/neuonc/nor200.

    Article  CAS  PubMed  Google Scholar 

  6. • 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(9):1199–208. https://doi.org/10.1093/neuonc/now058. Provides recommendations for the use of PET imaging in gliomas. The review examines established clinical benefit in glioma patients of PET using glucose and amino acid tracers.

    Article  CAS  Google Scholar 

  7. Law I, Albert NL, Arbizu J, Boellaard R, Drzezga A, Galldiks N, et al. Joint EANM/EANO/RANO practice guidelines/SNMMI procedure standards for imaging of gliomas using PET with radiolabelled amino acids and [(18)F]FDG: version 1.0. Eur J Nucl Med Mol Imaging. 2018. https://doi.org/10.1007/s00259-018-4207-9.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Herholz K. Brain tumors: an update on clinical PET research in gliomas. Semin Nucl Med. 2017;47(1):5–17. https://doi.org/10.1053/j.semnuclmed.2016.09.004.

    Article  PubMed  Google Scholar 

  9. Boado RJ, Li JY, Nagaya M, Zhang C, Pardridge WM. Selective expression of the large neutral amino acid transporter at the blood-brain barrier. Proc Natl Acad Sci USA. 1999;96(21):12079–84.

    Article  CAS  Google Scholar 

  10. Weller M, Pfister SM, Wick W, Hegi ME, Reifenberger G, Stupp R. Molecular neuro-oncology in clinical practice: a new horizon. Lancet Oncol. 2013;14(9):e370–9. https://doi.org/10.1016/S1470-2045(13)70168-2.

    Article  CAS  PubMed  Google Scholar 

  11. • 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(13):3550–9. https://doi.org/10.1158/1078-0432.CCR-13-1440. (18)F-FDOPA PET and MRI response assessment with regard to progression-free survival and overall survival is able to identifies treatment responders to antiangiogenic therapy as early as two weeks after treatment initiation.

    Article  CAS  Google Scholar 

  12. • Palanichamy K, Thirumoorthy K, Kanji S, Gordon N, Singh R, Jacob JR, et al. Methionine and kynurenine activate oncogenic kinases in glioblastoma, and methionine deprivation compromises proliferation. Clin Cancer Res. 2016;22(14):3513–23. https://doi.org/10.1158/1078-0432.Ccr-15-2308. Methionine and kynurenine pathways are shown to be imaging and therapeutic metabolic targets for glioblastoma.

    Article  CAS  Google Scholar 

  13. 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. AJNR Am J Neuroradiol. 2008;29(10):1867–71. https://doi.org/10.3174/ajnr.A1242.

    Article  CAS  PubMed  Google Scholar 

  14. • Lopci E, Riva M, Olivari L, Raneri F, Soffietti R, Piccardo A, et al. Prognostic value of molecular and imaging biomarkers in patients with supratentorial glioma. Eur J Nucl Med Mol Imaging. 2017;44(7):1155–64. https://doi.org/10.1007/s00259-017-3618-3. MET PET uptake is shown to correlate with histological grade and IDH1 mutation status in patients with glioma. Grade, pathological classification, molecular biomarkers, SUVmax and SUVratio are also shown to be prognostic factors for progression free survival.

    Article  CAS  Google Scholar 

  15. Zhao C, Zhang Y, Wang J. A meta-analysis on the diagnostic performance of (18)F-FDG and (11)C-methionine PET for differentiating brain tumors. AJNR Am J Neuroradiol. 2014;35(6):1058–65. https://doi.org/10.3174/ajnr.A3718.

    Article  CAS  PubMed  Google Scholar 

  16. Naslund O, Smits A, Forander P, Laesser M, Bartek J Jr, Gempt J, et al. Amino acid tracers in PET imaging of diffuse low-grade gliomas: a systematic review of preoperative applications. Acta Neurochir (Wien). 2018;160(7):1451–60. https://doi.org/10.1007/s00701-018-3563-3.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Brendle C, Hempel JM, Schittenhelm J, Skardelly M, Reischl G, Bender B, et al. Glioma grading by dynamic susceptibility contrast perfusion and (11)C-methionine positron emission tomography using different regions of interest. Neuroradiology. 2018;60(4):381–9. https://doi.org/10.1007/s00234-018-1993-5.

    Article  PubMed  Google Scholar 

  18. Usinskiene J, Ulyte A, Bjornerud A, Venius J, Katsaros VK, Rynkeviciene R, et al. Optimal differentiation of high- and low-grade glioma and metastasis: a meta-analysis of perfusion, diffusion, and spectroscopy metrics. Neuroradiology. 2016;58(4):339–50. https://doi.org/10.1007/s00234-016-1642-9.

    Article  PubMed  Google Scholar 

  19. Poetsch N, Woehrer A, Gesperger J, Furtner J, Haug AR, Wilhelm D, et al. Visual and semiquantitative 11C-methionine PET: an independent prognostic factor for survival of newly diagnosed and treatment-naive gliomas. Neuro Oncol. 2018;20(3):411–9. https://doi.org/10.1093/neuonc/nox177.

    Article  PubMed  Google Scholar 

  20. Cicuendez M, Lorenzo-Bosquet C, Cuberas-Borros G, Martinez-Ricarte F, Cordero E, Martinez-Saez E, et al. Role of [(11)C] methionine positron emission tomography in the diagnosis and prediction of survival in brain tumours. Clin Neurol Neurosurg. 2015;139:328–33. https://doi.org/10.1016/j.clineuro.2015.10.035.

    Article  PubMed  Google Scholar 

  21. Schinkelshoek M, Lopci E, Clerici E, Alongi F, Mancosu P, Rodari M, et al. Impact of 11C-methionine positron emission tomography/computed tomography on radiation therapy planning and prognosis in patients with primary brain tumors. Tumori. 2014;100(6):636–44. https://doi.org/10.1700/1778.19268.

    Article  PubMed  Google Scholar 

  22. Roelcke U, Wyss MT, Nowosielski M, Ruda R, Roth P, Hofer S, et al. Amino acid positron emission tomography to monitor chemotherapy response and predict seizure control and progression-free survival in WHO grade II gliomas. Neuro Oncol. 2016;18(5):744–51. https://doi.org/10.1093/neuonc/nov282.

    Article  CAS  PubMed  Google Scholar 

  23. Jung TY, Min JJ, Bom HS, Jung S, Kim IY, Lim SH, et al. Prognostic value of post-treatment metabolic tumor volume from (11)C-methionine PET/CT in recurrent malignant glioma. Neurosurg Rev. 2017;40(2):223–9. https://doi.org/10.1007/s10143-016-0748-1.

    Article  PubMed  Google Scholar 

  24. Lucas JT Jr, Serrano N, Kim H, Li X, Snyder SE, Hwang S, et al. (11)C-methionine positron emission tomography delineates non-contrast enhancing tumor regions at high risk for recurrence in pediatric high-grade glioma. J Neurooncol. 2017;132(1):163–70. https://doi.org/10.1007/s11060-016-2354-z.

    Article  PubMed  Google Scholar 

  25. • 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(11):1709–15. https://doi.org/10.2967/jnumed.111.102533. MET PET shown to predict prognosis in gliomas and is better than FDG PET and MRI in predicting survival in low grade gliomas.

    Article  Google Scholar 

  26. Deuschl C, Moenninghoff C, Goericke S, Kirchner J, Koppen S, Binse I, et al. Response assessment of bevacizumab therapy in GBM with integrated 11C-MET-PET/MRI: a feasibility study. Eur J Nucl Med Mol Imaging. 2017;44(8):1285–95. https://doi.org/10.1007/s00259-017-3661-0.

    Article  CAS  PubMed  Google Scholar 

  27. Beppu T, Terasaki K, Sasaki T, Sato Y, Tomabechi M, Kato K, et al. MRI and 11C-methyl-l-methionine PET differentiate bevacizumab true responders after initiating therapy for recurrent glioblastoma. Clin Nucl Med. 2016;41(11):852–7. https://doi.org/10.1097/RLU.0000000000001377.

    Article  PubMed  Google Scholar 

  28. Yoo MY, Paeng JC, Cheon GJ, Lee DS, Chung JK, Kim EE, et al. Prognostic value of metabolic tumor volume on (11)C-methionine PET in predicting progression-free survival in high-grade glioma. Nucl Med Mol Imaging. 2015;49(4):291–7. https://doi.org/10.1007/s13139-015-0362-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Kobayashi A, Misumida N, Fox JT, Kanei Y. Prognostic value of left ventricular end-diastolic pressure in patients with non-ST-segment elevation myocardial infarction. Cardiol Res. 2015;6(4–5):301–5. https://doi.org/10.14740/cr406w.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Manabe O, Hattori N, Yamaguchi S, Hirata K, Kobayashi K, Terasaka S, et al. Oligodendroglial component complicates the prediction of tumour grading with metabolic imaging. Eur J Nucl Med Mol Imaging. 2015;42(6):896–904. https://doi.org/10.1007/s00259-015-2996-7.

    Article  CAS  PubMed  Google Scholar 

  31. Nojiri T, Nariai T, Aoyagi M, Senda M, Ishii K, Ishiwata K, et al. Contributions of biological tumor parameters to the incorporation rate of l-[methyl-(11)C] methionine into astrocytomas and oligodendrogliomas. J Neurooncol. 2009;93(2):233–41. https://doi.org/10.1007/s11060-008-9767-2.

    Article  CAS  PubMed  Google Scholar 

  32. Kim YI, Kim Y, Lee JY, Jang SJ. Prognostic value of the metabolic and volumetric parameters of (11)C-methionine positron-emission tomography for gliomas: a systematic review and meta-analysis. AJNR Am J Neuroradiol. 2018;39(9):1629–34. https://doi.org/10.3174/ajnr.A5707.

    Article  PubMed  Google Scholar 

  33. Moulin-Romsee G, D’Hondt E, de Groot T, Goffin J, Sciot R, Mortelmans L, et al. Non-invasive grading of brain tumours using dynamic amino acid PET imaging: does it work for 11C-methionine? Eur J Nucl Med Mol Imaging. 2007;34(12):2082–7. https://doi.org/10.1007/s00259-007-0557-4.

    Article  PubMed  Google Scholar 

  34. Deuschl C, Kirchner J, Poeppel TD, Schaarschmidt B, Kebir S, El Hindy N, et al. (11)C-MET PET/MRI for detection of recurrent glioma. Eur J Nucl Med Mol Imaging. 2018;45(4):593–601. https://doi.org/10.1007/s00259-017-3916-9.

    Article  CAS  PubMed  Google Scholar 

  35. Ideguchi M, Nishizaki T, Ikeda N, Okamura T, Tanaka Y, Fujii N, et al. A surgical strategy using a fusion image constructed from 11C-methionine PET, 18F-FDG–PET and MRI for glioma with no or minimum contrast enhancement. J Neurooncol. 2018;138(3):537–48. https://doi.org/10.1007/s11060-018-2821-9.

    Article  CAS  PubMed  Google Scholar 

  36. Tinkle C, Duncan E, Doubrovin M, Han Y, Li Y, Kim H, et al. Evaluation of (11)C-methionine PET and anatomic MRI associations in diffuse intrinsic pontine glioma. J Nucl Med. 2018. https://doi.org/10.2967/jnumed.118.212514.

    Article  PubMed  Google Scholar 

  37. • 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(9):1293–300. https://doi.org/10.1093/neuonc/nov088. Static and dynamic FET PET parameters differentiate progressive or recurrent glioma from treatment-related changes with higher accuracy than MRI.

  38. Galldiks N, Stoffels G, Ruge MI, Rapp M, Sabel M, Reifenberger G, et al. Role of O-(2-18F-fluoroethyl)-l-tyrosine PET as a diagnostic tool for detection of malignant progression in patients with low-grade glioma. J Nucl Med. 2013;54(12):2046–54. https://doi.org/10.2967/jnumed.113.123836.

    Article  CAS  PubMed  Google Scholar 

  39. Suchorska B, Giese A, Biczok A, Unterrainer M, Weller M, Drexler M, et al. Identification of time-to-peak on dynamic 18F-FET–PET as a prognostic marker specifically in IDH1/2 mutant diffuse astrocytoma. Neuro Oncol. 2018;20(2):279–88. https://doi.org/10.1093/neuonc/nox153.

    Article  PubMed  Google Scholar 

  40. Kratochwil C, Combs SE, Leotta K, Afshar-Oromieh A, Rieken S, Debus J, et al. Intra-individual comparison of (1)(8)F-FET and (1)(8)F-DOPA in PET imaging of recurrent brain tumors. Neuro Oncol. 2014;16(3):434–40. https://doi.org/10.1093/neuonc/not199.

    Article  CAS  PubMed  Google Scholar 

  41. 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(2):207–14. https://doi.org/10.2967/jnumed.111.096859.

    Article  CAS  PubMed  Google Scholar 

  42. Pyka T, Gempt J, Hiob D, Ringel F, Schlegel J, Bette S, et al. Textural analysis of pre-therapeutic [18F]-FET–PET and its correlation with tumor grade and patient survival in high-grade gliomas. Eur J Nucl Med Mol Imaging. 2016;43(1):133–41. https://doi.org/10.1007/s00259-015-3140-4.

    Article  PubMed  Google Scholar 

  43. Lohmann P, Stoffels G, Ceccon G, Rapp M, Sabel M, Filss CP, et al. Radiation injury vs. recurrent brain metastasis: combining textural feature radiomics analysis and standard parameters may increase (18)F-FET PET accuracy without dynamic scans. Eur Radiol. 2017;27(7):2916–27. https://doi.org/10.1007/s00330-016-4638-2.

    Article  PubMed  Google Scholar 

  44. Lohmann P, Lerche C, Bauer EK, Steger J, Stoffels G, Blau T, et al. Predicting IDH genotype in gliomas using FET PET radiomics. Sci Rep. 2018;8(1):13328. https://doi.org/10.1038/s41598-018-31806-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Vomacka L, Unterrainer M, Holzgreve A, Mille E, Gosewisch A, Brosch J, et al. Voxel-wise analysis of dynamic (18)F-FET PET: a novel approach for non-invasive glioma characterisation. EJNMMI Res. 2018;8(1):91. https://doi.org/10.1186/s13550-018-0444-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. • Verger A, Stoffels G, Bauer EK, Lohmann P, Blau T, Fink GR, et al. Static and dynamic (18)F-FET PET for the characterization of gliomas defined by IDH and 1p/19q status. Eur J Nucl Med Mol Imaging. 2018;45(3):443–51. https://doi.org/10.1007/s00259-017-3846-6. Static and dynamic FET PET parameters allow identification of IDH mutation status. However, IDH mutated and 1p/19q co-deleted oligodendrogliomas cannot be differentiated from glioblastomas and astrocytomas by FET PET.

    Article  Google Scholar 

  47. Buchmann N, Gempt J, Ryang YM, Pyka T, Kirschke JS, Meyer B, et al. Can early postoperative O-(2-(18F)fluoroethyl)-l-tyrosine positron emission tomography after resection of glioblastoma predict the location of later tumor recurrence? World Neurosurg. 2019;121:e467–74. https://doi.org/10.1016/j.wneu.2018.09.139.

    Article  PubMed  Google Scholar 

  48. 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:e727–37. https://doi.org/10.1016/j.wneu.2018.02.139.

    Article  PubMed  Google Scholar 

  49. Jansen NL, Suchorska B, Wenter V, Schmid-Tannwald C, Todica A, Eigenbrod S, et al. Prognostic significance of dynamic 18F-FET PET in newly diagnosed astrocytic high-grade glioma. J Nucl Med. 2015;56(1):9–15. https://doi.org/10.2967/jnumed.114.144675.

    Article  CAS  PubMed  Google Scholar 

  50. Suchorska B, Unterrainer M, Biczok A, Sosnova M, Forbrig R, Bartenstein P, et al. (18)F-FET–PET as a biomarker for therapy response in non-contrast enhancing glioma following chemotherapy. J Neurooncol. 2018;139(3):721–30. https://doi.org/10.1007/s11060-018-2919-0.

    Article  CAS  PubMed  Google Scholar 

  51. • Galldiks N, Dunkl V, Ceccon G, Tscherpel C, Stoffels G, Law I, et al. Early treatment response evaluation using FET PET compared to MRI in glioblastoma patients at first progression treated with bevacizumab plus lomustine. Eur J Nucl Med Mol Imaging. 2018;45(13):2377–86. https://doi.org/10.1007/s00259-018-4082-4. FET PET MTV is better able to predict responders compared to RANO criteria.

    Article  CAS  Google Scholar 

  52. 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 Imaging. 2013;40(1):22–33. https://doi.org/10.1007/s00259-012-2251-4.

    Article  CAS  PubMed  Google Scholar 

  53. Munck AF, Rosenschold P, Costa J, Engelholm SA, Lundemann MJ, Law I, Ohlhues L, et al. Impact of [18F]-fluoro-ethyl-tyrosine PET imaging on target definition for radiation therapy of high-grade glioma. Neuro Oncol. 2015;17(5):757–63. https://doi.org/10.1093/neuonc/nou316.

    Article  CAS  Google Scholar 

  54. Piroth MD, Galldiks N, Pinkawa M, Holy R, Stoffels G, Ermert J, et al. Relapse patterns after radiochemotherapy of glioblastoma with FET PET-guided boost irradiation and simulation to optimize radiation target volume. Radiat Oncol. 2016;11:87. https://doi.org/10.1186/s13014-016-0665-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Wardak M, Schiepers C, Cloughesy TF, Dahlbom M, Phelps ME, Huang SC. (1)(8)F-FLT and (1)(8)F-FDOPA PET kinetics in recurrent brain tumors. Eur J Nucl Med Mol Imaging. 2014;41(6):1199–209. https://doi.org/10.1007/s00259-013-2678-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Rossi Espagnet MC, Romano A, Mancuso V, Cicone F, Napolitano A, Scaringi C, et al. Multiparametric evaluation of low grade gliomas at follow-up: comparison between diffusion and perfusion MR with (18)F-FDOPA PET. Br J Radiol. 2016;89(1066):20160476. https://doi.org/10.1259/bjr.20160476.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Janvier L, Olivier P, Blonski M, Morel O, Vignaud JM, 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(9):e429–35. https://doi.org/10.1097/RLU.0000000000000897.

    Article  PubMed  Google Scholar 

  58. Karunanithi S, Sharma P, Kumar A, Gupta DK, Khangembam BC, Ballal S, et al. Can (18)F-FDOPA PET/CT predict survival in patients with suspected recurrent glioma? A prospective study. Eur J Radiol. 2014;83(1):219–25. https://doi.org/10.1016/j.ejrad.2013.09.004.

    Article  PubMed  Google Scholar 

  59. 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-naive gliomas: a cross-sectional study. J Neurooncol. 2018;139(2):399–409. https://doi.org/10.1007/s11060-018-2877-6.

    Article  CAS  PubMed  Google Scholar 

  60. Toch SR, Poussier S, Micard E, Bertaux M, Van Der Gucht A, Chevalier E, et al. Physiological whole-brain distribution of [(18)F]FDOPA uptake index in relation to age and gender: results from a voxel-based semi-quantitative analysis. Mol Imaging Biol. 2018. https://doi.org/10.1007/s11307-018-1256-1.

    Article  PubMed  Google Scholar 

  61. 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. 2014;16(4):603–9. https://doi.org/10.1093/neuonc/not166.

    Article  PubMed  Google Scholar 

  62. 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(9):5117–22.

    CAS  PubMed  Google Scholar 

  63. Verger A, Metellus P, Sala Q, Colin C, Bialecki E, Taieb D, et al. IDH mutation is paradoxically associated with higher (18)F-FDOPA PET uptake in diffuse grade II and grade III gliomas. Eur J Nucl Med Mol Imaging. 2017;44(8):1306–11. https://doi.org/10.1007/s00259-017-3668-6.

    Article  CAS  PubMed  Google Scholar 

  64. Isal S, Gauchotte G, Rech F, Blonski M, Planel S, Chawki MB, et al. A high (18)F-FDOPA uptake is associated with a slow growth rate in diffuse Grade II-III gliomas. Br J Radiol. 2018;91(1084):20170803. https://doi.org/10.1259/bjr.20170803.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Gauvain K, Ponisio MR, Barone A, Grimaldi M, Parent E, Leeds H, et al. (18)F-FDOPA PET/MRI for monitoring early response to bevacizumab in children with recurrent brain tumors. Neurooncol Pract. 2018;5(1):28–36. https://doi.org/10.1093/nop/npx008.

    Article  PubMed  Google Scholar 

  66. Karunanithi S, Sharma P, Kumar A, Khangembam BC, Bandopadhyaya GP, Kumar R, et al. Comparative diagnostic accuracy of contrast-enhanced MRI and (18)F-FDOPA PET-CT in recurrent glioma. Eur Radiol. 2013;23(9):2628–35. https://doi.org/10.1007/s00330-013-2838-6.

    Article  PubMed  Google Scholar 

  67. Parent EE, Schuster DM. Update on (18)F-fluciclovine PET for prostate cancer imaging. J Nucl Med. 2018;59(5):733–9. https://doi.org/10.2967/jnumed.117.204032.

    Article  CAS  PubMed  Google Scholar 

  68. Sasajima T, Ono T, Shimada N, Doi Y, Oka S, Kanagawa M, et al. Trans-1-amino-3-18F-fluorocyclobutanecarboxylic acid (anti-18F-FACBC) is a feasible alternative to 11C-methyl-l-methionine and magnetic resonance imaging for monitoring treatment response in gliomas. Nucl Med Biol. 2013;40(6):808–15. https://doi.org/10.1016/j.nucmedbio.2013.04.007.

    Article  CAS  PubMed  Google Scholar 

  69. Kondo A, Ishii H, Aoki S, Suzuki M, Nagasawa H, Kubota K, et al. Phase IIa clinical study of [(18)F]fluciclovine: efficacy and safety of a new PET tracer for brain tumors. Ann Nucl Med. 2016;30(9):608–18. https://doi.org/10.1007/s12149-016-1102-y.

    Article  CAS  PubMed  Google Scholar 

  70. Wakabayashi T, Iuchi T, Tsuyuguchi N, Nishikawa R, Arakawa Y, Sasayama T, et al. Diagnostic performance and safety of positron emission tomography using (18)F-fluciclovine in patients with clinically suspected high- or low-grade gliomas: a multicenter phase IIb trial. Asia Ocean J Nucl Med Biol. 2017;5(1):10–21. https://doi.org/10.22038/aojnmb.2016.7869.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Tsuyuguchi N, Terakawa Y, Uda T, Nakajo K, Kanemura Y. Diagnosis of brain tumors using amino acid transport PET imaging with (18)F-fluciclovine: a comparative study with l-methyl-(11)C-methionine PET Imaging. Asia Ocean J Nucl Med Biol. 2017;5(2):85–94. https://doi.org/10.22038/aojnmb.2017.8843.

    Article  PubMed  PubMed Central  Google Scholar 

  72. • Parent EE, Benayoun M, Ibeanu I, Olson JJ, Hadjipanayis CG, Brat DJ, et al. [(18)F]Fluciclovine PET discrimination between high- and low-grade gliomas. EJNMMI Res. 2018;8(1):67. https://doi.org/10.1186/s13550-018-0415-3. Fluciclovine PET is able to discriminate between both low-grade and high grade gliomas and normal brain by visual and semiquantitative analysis.

  73. Oldan JD, Miller SM, Barnes A, Khandani AH. Trapping of 18F-fluciclovine (FACBC) in Superior Sagittal Sinus. Clin Nucl Med. 2019;44(1):48–9. https://doi.org/10.1097/RLU.0000000000002352.

    Article  PubMed  Google Scholar 

  74. Scarsbrook A. Multi-parametric MRI/fluorine-18 fluciclovine PET-CT in glioblastoma. 2018.

  75. Juhasz C, Dwivedi S, Kamson DO, Michelhaugh SK, Mittal S. Comparison of amino acid positron emission tomographic radiotracers for molecular imaging of primary and metastatic brain tumors. Mol Imaging. 2014. https://doi.org/10.2310/7290.2014.00015.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Lukas RV, Juhasz C, Wainwright DA, James CD, Kennedy E, Stupp R, et al. Imaging tryptophan uptake with positron emission tomography in glioblastoma patients treated with indoximod. J Neurooncol. 2018. https://doi.org/10.1007/s11060-018-03013-x.

    Article  PubMed  Google Scholar 

  77. Juhasz C, Chugani DC, Barger GR, Kupsky WJ, Chakraborty PK, Muzik O, et al. Quantitative PET imaging of tryptophan accumulation in gliomas and remote cortex: correlation with tumor proliferative activity. Clin Nucl Med. 2012;37(9):838–42. https://doi.org/10.1097/RLU.0b013e318251e458.

    Article  PubMed  PubMed Central  Google Scholar 

  78. • Kamson DO, Juhasz C, Buth A, Kupsky WJ, Barger GR, Chakraborty PK, et al. Tryptophan PET in pretreatment delineation of newly-diagnosed gliomas: MRI and histopathologic correlates. J Neurooncol. 2013;112(1):121–32. https://doi.org/10.1007/s11060-013-1043-4. AMT PET shown to detect glioma-infiltrated brain tissue extending beyond the contrast-enhanced tumor mass.

    Article  CAS  Google Scholar 

  79. Alkonyi B, Barger GR, Mittal S, Muzik O, Chugani DC, Bahl G, et al. Accurate differentiation of recurrent gliomas from radiation injury by kinetic analysis of alpha-11C-methyl-l-tryptophan PET. J Nucl Med. 2012;53(7):1058–64. https://doi.org/10.2967/jnumed.111.097881.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Bosnyak E, Kamson DO, Robinette NL, Barger GR, Mittal S, Juhasz C. Tryptophan PET predicts spatial and temporal patterns of post-treatment glioblastoma progression detected by contrast-enhanced MRI. J Neurooncol. 2016;126(2):317–25. https://doi.org/10.1007/s11060-015-1970-3.

    Article  CAS  PubMed  Google Scholar 

  81. Bosnyak E, Michelhaugh SK, Klinger NV, Kamson DO, Barger GR, Mittal S, et al. Prognostic molecular and imaging biomarkers in primary glioblastoma. Clin Nucl Med. 2017;42(5):341–7. https://doi.org/10.1097/RLU.0000000000001577.

    Article  PubMed  PubMed Central  Google Scholar 

  82. Mitsuka K, Kawataki T, Satoh E, Asahara T, Horikoshi T, Kinouchi H. Expression of indoleamine 2,3-dioxygenase and correlation with pathological malignancy in gliomas. Neurosurgery. 2013;72(6):1031–8. https://doi.org/10.1227/neu.0b013e31828cf945 discussion 8–9.

    Article  PubMed  Google Scholar 

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  1. Department of Radiology, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA

    Ephraim E. Parent, Akash Sharma & Manoj Jain

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Parent, E.E., Sharma, A. & Jain, M. Amino Acid PET Imaging of Glioma. Curr Radiol Rep 7, 14 (2019). https://doi.org/10.1007/s40134-019-0324-x

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