Diagnostic Value of PET Tracers in Differentiating Glioma Tumor Recurrence from Treatment-Related Changes: A Systematic Review and Meta-Analysis

References

1. 1.
   1. Ostrom QT,
   2. Price M,
   3. Neff C, et al

   . CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2016-2020. Neuro Oncol 2023;25:iv1–99 doi:10.1093/neuonc/noad149 pmid:37793125

   CrossRefPubMed
2. 2.↵
   1. De Maria L,
   2. Panciani PP,
   3. Zeppieri M, et al

   . A systematic review of the metabolism of high-grade gliomas: current targeted therapies and future perspectives. Int J Mol Sci 2024;25:724

   CrossRefPubMed
3. 3.↵
   1. Albert NL,
   2. Galldiks N,
   3. Ellingson BM, et al

   . PET-based response assessment criteria for diffuse gliomas (PET RANO 1.0): a report of the RANO group. Lancet Oncol 2024;25:e29–41 doi:10.1016/S1470-2045(23)00525-9 pmid:38181810

   CrossRefPubMed
4. 4.↵
   1. Wen PY,
   2. van den Bent M,
   3. Youssef G, et al

   . RANO 2.0: update to the Response Assessment in Neuro-Oncology criteria for high- and low-grade gliomas in adults. J Clin Oncol 2023;41:5187–99 doi:10.1200/JCO.23.01059 pmid:37774317

   CrossRefPubMed
5. 5.↵
   1. Abbasi AW,
   2. Westerlaan HE,
   3. Holtman GA, et al

   . Incidence of tumour progression and pseudoprogression in high-grade gliomas: a systematic review and meta-analysis. Clin Neuroradiol 2018;28:401–11 doi:10.1007/s00062-017-0584-x pmid:28466127

   CrossRefPubMed
6. 6.↵
   1. van West SE,
   2. de Bruin HG,
   3. van de Langerijt B, et al

   . Incidence of pseudoprogression in low-grade gliomas treated with radiotherapy. Neuro Oncol 2017;19:719–25 doi:10.1093/neuonc/now194 pmid:28453748

   CrossRefPubMed
7. 7.↵
   1. Moher D,
   2. Liberati A,
   3. Tetzlaff J

   ; PRISMA Group, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 2009;6:e1000097 doi:10.1371/journal.pmed.1000097 pmid:19621072

   CrossRefPubMed
8. 8.↵
   1. Whiting PF,
   2. Rutjes AWS,
   3. Westwood ME

   ; QUADAS-2 Group, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 2011;155:529–36 doi:10.7326/0003-4819-155-8-201110180-00009 pmid:22007046

   CrossRefPubMedWeb of Science
9. 9.↵
   1. Zhao C,
   2. Zhang Y,
   3. 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;35:1058–65 doi:10.3174/ajnr.A3718 pmid:24029389

   Abstract/FREE Full Text
10. 10.↵
    1. Shishido H,
    2. Kawai N,
    3. Miyake K, et al

    . Diagnostic value of 11C-methionine (MET) and 18F-fluorothymidine (FLT) positron emission tomography in recurrent high-grade gliomas; differentiation from treatment-induced tissue necrosis. Cancers (Basel) 2012;4:244–56 doi:10.3390/cancers4010244 pmid:24213238

    CrossRefPubMed
11. 11.↵
    1. Nakajima T,
    2. Kumabe T,
    3. Kanamori M, et al

    . Differential diagnosis between radiation necrosis and glioma progression using sequential proton magnetic resonance spectroscopy and methionine positron emission tomography. Neurol Med Chir (Tokyo) 2009;49:394–401 doi:10.2176/nmc.49.394 pmid:19779283

    CrossRefPubMed
12. 12.↵
    1. Moreau A,
    2. Khayi F,
    3. Maureille A, et al

    . Discriminating inflammatory radiation-related changes from early recurrence in patients with glioblastomas: a preliminary analysis of 68 Ga-PSMA-11 PET/CT compared with 18F-FDOPA PET/CT. Clin Nucl Med 2023;48:657–66 doi:10.1097/RLU.0000000000004716 pmid:37276534

    CrossRefPubMed
13. 13.↵
    1. Pellerin A,
    2. Khalifé M,
    3. Sanson M, et al

    . Simultaneously acquired PET and ASL imaging biomarkers may be helpful in differentiating progression from pseudo-progression in treated gliomas. Eur Radiology 2021;31:7395–405 doi:10.1007/s00330-021-07732-0 pmid:33787971

    CrossRefPubMed
14. 14.↵
    1. de Zwart PL,
    2. van Dijken BRJ,
    3. Holtman GA, et al

    . Diagnostic accuracy of PET tracers for the differentiation of tumor progression from treatment-related changes in high-grade glioma: a systematic review and metaanalysis. J Nucl Med 2020;61:498–504 doi:10.2967/jnumed.119.233809 pmid:31541032

    Abstract/FREE Full Text
15. 15.↵
    1. Treglia G,
    2. Muoio B,
    3. Trevisi G, et al

    . Diagnostic performance and prognostic value of PET/CT with different tracers for brain tumors: a systematic review of published meta-analyses. Int J Mol Sci 2019;20:4669 doi:10.3390/ijms20194669

    CrossRefPubMed
16. 16.↵
    1. Albert NL,
    2. Weller M,
    3. Suchorska B, et al

    . Response Assessment in Neuro-Oncology Working Group and European Association for Neuro-Oncology recommendations for the clinical use of PET imaging in gliomas. Neuro Oncol 2016;18:1199–208 doi:10.1093/neuonc/now058 pmid:27106405

    CrossRefPubMed
17. 17.↵
    1. Galldiks N,
    2. Lohmann P,
    3. Fink GR, et al

    . Amino acid PET in neurooncology. J Nucl Med 2023;64:693–700 doi:10.2967/jnumed.122.264859 pmid:37055222

    Abstract/FREE Full Text
18. 18.↵
    1. Xiong M,
    2. Chen Z,
    3. Zhou C, et al

    . PSMA PET/MR is a new imaging option for identifying glioma recurrence and predicting prognosis. Recent Pat Anticancer Drug Discov 2024;19:383–95 doi:10.2174/1574892818666230519150401 pmid:38214322

    CrossRefPubMed
19. 19.↵
    1. Nabavizadeh A,
    2. Bagley SJ,
    3. Doot RK, et al

    . Distinguishing progression from pseudoprogression in glioblastoma using (18)F-fluciclovine PET. J Nucl Med 2023;64:852–58 doi:10.2967/jnumed.122.264812 pmid:36549916

    Abstract/FREE Full Text
20. 20.↵
    1. Waheed A,
    2. Singh B,
    3. Watts A, et al

    . 68 Ga-pentixafor PET/CT for in vivo imaging of CXCR4 receptors in glioma demonstrating a potential for response assessment to radiochemotherapy: preliminary results. Clin Nucl Med 2024;49:e141–48 doi:10.1097/RLU.0000000000005073 pmid:38350065

    CrossRefPubMed
21. 21.↵
    1. Blasel S,
    2. Zagorcic A,
    3. Jurcoane A, et al

    . Perfusion MRI in the evaluation of suspected glioblastoma recurrence. J Neuroimaging 2016;26:116–23 doi:10.1111/jon.12247 pmid:25907688

    CrossRefPubMed
22. 22.↵
    1. Wan B,
    2. Wang S,
    3. Tu M, et al

    . The diagnostic performance of perfusion MRI for differentiating glioma recurrence from pseudoprogression: a meta-analysis. Medicine (Baltimore) 2017;96:e6333 doi:10.1097/MD.0000000000006333 pmid:28296759

    CrossRefPubMed
23. 23.↵
    1. Yang Y,
    2. He MZ,
    3. Li T, et al

    . MRI combined with PET-CT of different tracers to improve the accuracy of glioma diagnosis: a systematic review and meta-analysis. Neurosurg Rev 2019;42:185–95 doi:10.1007/s10143-017-0906-0 pmid:28918564

    CrossRefPubMed
24. 24.↵
    1. Panholzer J,
    2. Walli G,
    3. Grün B, et al

    . Multiparametric analysis combining DSC-MR perfusion and [18F]FET-PET is superior to a single parameter approach for differentiation of progressive glioma from radiation necrosis. Clin Neuroradiol 2024;34:351–60 doi:10.1007/s00062-023-01372-1 pmid:38157019

    CrossRefPubMed
25. 25.↵
    1. Chen Q,
    2. Wang K,
    3. Ren X, et al

    . Individualized discrimination of tumor progression from treatment-related changes in different types of adult-type diffuse gliomas using [(11)C]methionine PET. J Neurooncol 2023;165:547–59 doi:10.1007/s11060-023-04529-7 pmid:38095773

    CrossRefPubMed
26. 26.
    1. Peer S,
    2. Gopinath R,
    3. Saini J, et al

    . Evaluation of the diagnostic performance of F18-fluorodeoxyglucose-positron emission tomography, dynamic susceptibility contrast perfusion, and apparent diffusion coefficient in differentiation between recurrence of a high-grade glioma and radiation necrosis. Indian J Nucl Med 2023;38:115–24 doi:10.4103/ijnm.ijnm_73_22 pmid:37456178

    CrossRefPubMed
27. 27.
    1. Müller M,
    2. Winz O,
    3. Gutsche R, et al

    . Static FET PET radiomics for the differentiation of treatment-related changes from glioma progression. J Neurooncol 2022;159:519–29 doi:10.1007/s11060-022-04089-2 pmid:35852737

    CrossRefPubMed
28. 28.
    1. Dang H,
    2. Zhang J,
    3. Wang R, et al

    . Glioblastoma recurrence versus radiotherapy injury: combined model of diffusion kurtosis imaging and 11C-MET using PET/MRI may increase accuracy of differentiation. Clin Nucl Med 2022;47:e428–36 doi:10.1097/RLU.0000000000004167 pmid:35439178

    CrossRefPubMed
29. 29.
    1. Steidl E,
    2. Langen K-J,
    3. Hmeidan SA, et al

    . Sequential implementation of DSC-MR perfusion and dynamic ¹⁸F FET PET allows efficient differentiation of glioma progression from treatment-related changes. Eur J Nucl Med Mol Imaging 2021;48:1956–65 doi:10.1007/s00259-020-05114-0 pmid:33241456

    CrossRefPubMed
30. 30.
    1. Pyatigorskaya N,
    2. Sgard B,
    3. Bertaux M, et al

    . Can FDG-PET/MR help to overcome limitations of sequential MRI and PET-FDG for differential diagnosis between recurrence/progression and radionecrosis of high-grade gliomas? J Neuroradiol 2021;48:189–94 doi:10.1016/j.neurad.2020.08.003 pmid:32858062

    CrossRefPubMed
31. 31.
    1. Celli M,
    2. Caroli P,
    3. Amadori E, et al

    . Diagnostic and prognostic potential of (18)F-FET PET in the differential diagnosis of glioma recurrence and treatment-induced changes after chemoradiation therapy. Front Oncol 2021;11:721821 doi:10.3389/fonc.2021.721821 pmid:34671551

    CrossRefPubMed
32. 32.
    1. Puranik AD,
    2. Rangarajan V,
    3. Dev ID, et al

    . Brain FET PET tumor-to-white mater ratio to differentiate recurrence from post-treatment changes in high-grade gliomas. J Neuroimaging 2021;31:1211–18 doi:10.1111/jon.12914 pmid:34388273

    CrossRefPubMed
33. 33.
    1. D’Amore F,
    2. Grinberg F,
    3. Mauler J, 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 doi:10.1093/noajnl/vdab044 pmid:34013207

    CrossRefPubMed
34. 34.
    1. Maurer GD,
    2. Brucker DP,
    3. Stoffels G, et al

    . (18)F-FET PET imaging in differentiating glioma progression from treatment-related changes: a single-center experience. J Nucl Med 2020;61:505–11 doi:10.2967/jnumed.119.234757 pmid:31519802

    Abstract/FREE Full Text
35. 35.
    1. Lohmann P,
    2. Elahmadawy MA,
    3. Gutsche R, et al

    . FET PET radiomics for differentiating pseudoprogression from early tumor progression in glioma patients post-chemoradiation. Cancers (Basel) 2020;12:3835 doi:10.3390/cancers12123835

    CrossRefPubMed
36. 36.
    1. Lohmeier J,
    2. Bohner G,
    3. Siebert E, et al

    . Quantitative biparametric analysis of hybrid (18)F-FET PET/MR-neuroimaging for differentiation between treatment response and recurrent glioma. Sci Rep 2019;9:14603 doi:10.1038/s41598-019-50182-4 pmid:31601829

    CrossRefPubMed
37. 37.
    1. Qiao Z,
    2. Zhao X,
    3. Wang K, et al

    . Utility of dynamic susceptibility contrast perfusion-weighted MR imaging and (11)C-methionine PET/CT for differentiation of tumor recurrence from radiation injury in patients with high-grade gliomas. AJNR Am J Neuroradiol 2019;40:253–59 doi:10.3174/ajnr.A5952 pmid:30655259

    Abstract/FREE Full Text
38. 38.
    1. Hojjati M,
    2. Badve C,
    3. Garg V, et al

    . Role of FDG-PET/MRI, FDG-PET/CT, and dynamic susceptibility contrast perfusion MRI in differentiating radiation necrosis from tumor recurrence in glioblastomas. J Neuroimaging 2018;28:118–25 doi:10.1111/jon.12460 pmid:28718993

    CrossRefPubMed
39. 39.
    1. Jena A,
    2. Taneja S,
    3. Jha A, et al

    . Multiparametric evaluation in differentiating glioma recurrence from treatment-induced necrosis using simultaneous ¹⁸F-FDG-PET/MRI: a single-institution retrospective study. AJNR Am J Neuroradiol 2017;38:899–907 doi:10.3174/ajnr.A5124 pmid:28341716

    Abstract/FREE Full Text
40. 40.
    1. Sogani SK,
    2. Jena A,
    3. Taneja S, et al

    . Potential for differentiation of glioma recurrence from radionecrosis using integrated ¹⁸F-fluoroethyl-L-tyrosine (FET) positron emission tomography/magnetic resonance imaging: a prospective evaluation. Neurol India 2017;65:293–301 doi:10.4103/neuroindia.NI_101_16 pmid:28290392

    CrossRefPubMed
41. 41.
    1. Jena A,
    2. Taneja S,
    3. Gambhir A, et al

    . Glioma recurrence versus radiation necrosis: single-session multiparametric approach using simultaneous O-(2-18F-fluoroethyl)-L-tyrosine PET/MRI. Clin Nucl Med 2016;41:e228-36 doi:10.1097/RLU.0000000000001152 pmid:26859208

    CrossRefPubMed
42. 42.
    1. Dankbaar JW,
    2. Snijders TJ,
    3. Robe PA, et al

    . The use of ¹⁸F-FDG PET to differentiate progressive disease from treatment induced necrosis in high grade glioma. J Neurooncol 2015;125:167–75 doi:10.1007/s11060-015-1883-1 pmid:26384811

    CrossRefPubMed
43. 43.
    1. Takenaka S,
    2. Asano Y,
    3. Shinoda J, et al

    . Comparison of (11)C-methionine, (11)C-choline, and (18)F-fluorodeoxyglucose-PET for distinguishing glioma recurrence from radiation necrosis. Neurol Med Chir (Tokyo) 2014;54:280–89

    CrossRefPubMed
44. 44.
    1. Skvortsova TY,
    2. Brodskaya ZL,
    3. Gurchin AF

    . PET using 11C-methionine in recognition of pseudoprogression in cerebral glioma after combined treatment. Zh Vopr Neirokhir Im N N Burdenko 2014;78:50–58 pmid:25406809

    CrossRefPubMed
45. 45.
    1. Alkonyi B,
    2. Barger GR,
    3. Mittal S, et al

    . Accurate differentiation of recurrent gliomas from radiation injury by kinetic analysis of α-11C-methyl-L-tryptophan PET. J Nucl Med 2012;53:1058–64 doi:10.2967/jnumed.111.097881 pmid:22653792

    Abstract/FREE Full Text