The diagnostic performance of [18F]FET PET/MRI versus [18F]FDG PET/MRI for recurrent glioma: a systematic review and meta-analysis
Purpose Our systematic review and meta-analysis aimed to evaluate the diagnostic performance of [18F]FDG PET/MRI vs. [18F]FET PET/MRI for recurrent glioma. Methods We searched for relevant articles in PubMed, Embase, and Web of Science until February 2023. Studies regarding the diagnostic performanc...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Huo, Huasong [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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© The Author(s), under exclusive licence to Italian Association of Nuclear Medicine and Molecular Imaging 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Clinical and translational imaging - Berlin : Springer Milan, 2013, 11(2023), 3 vom: 09. Mai, Seite 285-295 |
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| Übergeordnetes Werk: |
volume:11 ; year:2023 ; number:3 ; day:09 ; month:05 ; pages:285-295 |
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| DOI / URN: |
10.1007/s40336-023-00563-7 |
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| Katalog-ID: |
SPR051755726 |
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| 100 | 1 | |a Huo, Huasong |e verfasserin |4 aut | |
| 245 | 1 | 4 | |a The diagnostic performance of [18F]FET PET/MRI versus [18F]FDG PET/MRI for recurrent glioma: a systematic review and meta-analysis |
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| 520 | |a Purpose Our systematic review and meta-analysis aimed to evaluate the diagnostic performance of [18F]FDG PET/MRI vs. [18F]FET PET/MRI for recurrent glioma. Methods We searched for relevant articles in PubMed, Embase, and Web of Science until February 2023. Studies regarding the diagnostic performance of [18F]FET PET/MRI or [18F]FDG PET/MRI in recurrent glioma were included. The quality of each study was assessed using the Quality Assessment of Diagnostic Performance Studies-2 (QUADAS-2) tool. Results A total of nine studies with 310 patients were included in the analysis, the pooled sensitivity, specificity of [18F]FDG PET/MRI in detecting recurrent glioma after definitive treatment were 0.99 (95% CI 0.75–1.00) and 0.62 (95% CI 0.37–0.83), [18F]FET PET/MRI were 0.94 (95% CI 0.81–0.98) and 0.87 (95% CI 0.70–0.95), respectively. The area under curve (AUC) for [18F]FDG PET/MRI and [18F]FET PET/MRI were 0.92 (95% CI 0.89–0.94) and 0.96 (95% CI 0.94–0.97) and there is a statistical difference between the two imaging modalities (Z = 12.433, P < 0.001). Fagan nomogram indicated that when the pre-test probability was set at 50%, the post-test probability for [18F]FDG PET/MRI and [18F]FET PET/MRI could increase to 72 and 88%. Conclusions [18F]FET PET/MRI has a higher AUC compared to [18F]FDG PET/MRI in the detection of tumor recurrence in glioma. However, the results of the meta-analysis were drawn from studies with small samples. Further larger prospective studies in this setting are warranted. | ||
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| 650 | 4 | |a F]FET PET/MRI |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Yang, Fuwei |4 aut | |
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10.1007/s40336-023-00563-7 doi (DE-627)SPR051755726 (SPR)s40336-023-00563-7-e DE-627 ger DE-627 rakwb eng Huo, Huasong verfasserin aut The diagnostic performance of [18F]FET PET/MRI versus [18F]FDG PET/MRI for recurrent glioma: a systematic review and meta-analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Italian Association of Nuclear Medicine and Molecular Imaging 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Purpose Our systematic review and meta-analysis aimed to evaluate the diagnostic performance of [18F]FDG PET/MRI vs. [18F]FET PET/MRI for recurrent glioma. Methods We searched for relevant articles in PubMed, Embase, and Web of Science until February 2023. Studies regarding the diagnostic performance of [18F]FET PET/MRI or [18F]FDG PET/MRI in recurrent glioma were included. The quality of each study was assessed using the Quality Assessment of Diagnostic Performance Studies-2 (QUADAS-2) tool. Results A total of nine studies with 310 patients were included in the analysis, the pooled sensitivity, specificity of [18F]FDG PET/MRI in detecting recurrent glioma after definitive treatment were 0.99 (95% CI 0.75–1.00) and 0.62 (95% CI 0.37–0.83), [18F]FET PET/MRI were 0.94 (95% CI 0.81–0.98) and 0.87 (95% CI 0.70–0.95), respectively. The area under curve (AUC) for [18F]FDG PET/MRI and [18F]FET PET/MRI were 0.92 (95% CI 0.89–0.94) and 0.96 (95% CI 0.94–0.97) and there is a statistical difference between the two imaging modalities (Z = 12.433, P < 0.001). Fagan nomogram indicated that when the pre-test probability was set at 50%, the post-test probability for [18F]FDG PET/MRI and [18F]FET PET/MRI could increase to 72 and 88%. Conclusions [18F]FET PET/MRI has a higher AUC compared to [18F]FDG PET/MRI in the detection of tumor recurrence in glioma. However, the results of the meta-analysis were drawn from studies with small samples. Further larger prospective studies in this setting are warranted. [ (dpeaa)DE-He213 F]FET PET/MRI (dpeaa)DE-He213 [ (dpeaa)DE-He213 F]FDG PET/MRI (dpeaa)DE-He213 Diagnostic performance (dpeaa)DE-He213 Glioma (dpeaa)DE-He213 Recurrent (dpeaa)DE-He213 Meta-analysis (dpeaa)DE-He213 Shen, Shurui aut Zhang, Lanyue aut Yang, Fuwei aut Li, Yunqian (orcid)0000-0003-2199-8618 aut Enthalten in Clinical and translational imaging Berlin : Springer Milan, 2013 11(2023), 3 vom: 09. Mai, Seite 285-295 (DE-627)742738752 (DE-600)2712000-4 2281-7565 nnns volume:11 year:2023 number:3 day:09 month:05 pages:285-295 https://dx.doi.org/10.1007/s40336-023-00563-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 11 2023 3 09 05 285-295 |
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10.1007/s40336-023-00563-7 doi (DE-627)SPR051755726 (SPR)s40336-023-00563-7-e DE-627 ger DE-627 rakwb eng Huo, Huasong verfasserin aut The diagnostic performance of [18F]FET PET/MRI versus [18F]FDG PET/MRI for recurrent glioma: a systematic review and meta-analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Italian Association of Nuclear Medicine and Molecular Imaging 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Purpose Our systematic review and meta-analysis aimed to evaluate the diagnostic performance of [18F]FDG PET/MRI vs. [18F]FET PET/MRI for recurrent glioma. Methods We searched for relevant articles in PubMed, Embase, and Web of Science until February 2023. Studies regarding the diagnostic performance of [18F]FET PET/MRI or [18F]FDG PET/MRI in recurrent glioma were included. The quality of each study was assessed using the Quality Assessment of Diagnostic Performance Studies-2 (QUADAS-2) tool. Results A total of nine studies with 310 patients were included in the analysis, the pooled sensitivity, specificity of [18F]FDG PET/MRI in detecting recurrent glioma after definitive treatment were 0.99 (95% CI 0.75–1.00) and 0.62 (95% CI 0.37–0.83), [18F]FET PET/MRI were 0.94 (95% CI 0.81–0.98) and 0.87 (95% CI 0.70–0.95), respectively. The area under curve (AUC) for [18F]FDG PET/MRI and [18F]FET PET/MRI were 0.92 (95% CI 0.89–0.94) and 0.96 (95% CI 0.94–0.97) and there is a statistical difference between the two imaging modalities (Z = 12.433, P < 0.001). Fagan nomogram indicated that when the pre-test probability was set at 50%, the post-test probability for [18F]FDG PET/MRI and [18F]FET PET/MRI could increase to 72 and 88%. Conclusions [18F]FET PET/MRI has a higher AUC compared to [18F]FDG PET/MRI in the detection of tumor recurrence in glioma. However, the results of the meta-analysis were drawn from studies with small samples. Further larger prospective studies in this setting are warranted. [ (dpeaa)DE-He213 F]FET PET/MRI (dpeaa)DE-He213 [ (dpeaa)DE-He213 F]FDG PET/MRI (dpeaa)DE-He213 Diagnostic performance (dpeaa)DE-He213 Glioma (dpeaa)DE-He213 Recurrent (dpeaa)DE-He213 Meta-analysis (dpeaa)DE-He213 Shen, Shurui aut Zhang, Lanyue aut Yang, Fuwei aut Li, Yunqian (orcid)0000-0003-2199-8618 aut Enthalten in Clinical and translational imaging Berlin : Springer Milan, 2013 11(2023), 3 vom: 09. Mai, Seite 285-295 (DE-627)742738752 (DE-600)2712000-4 2281-7565 nnns volume:11 year:2023 number:3 day:09 month:05 pages:285-295 https://dx.doi.org/10.1007/s40336-023-00563-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 11 2023 3 09 05 285-295 |
| allfields_unstemmed |
10.1007/s40336-023-00563-7 doi (DE-627)SPR051755726 (SPR)s40336-023-00563-7-e DE-627 ger DE-627 rakwb eng Huo, Huasong verfasserin aut The diagnostic performance of [18F]FET PET/MRI versus [18F]FDG PET/MRI for recurrent glioma: a systematic review and meta-analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Italian Association of Nuclear Medicine and Molecular Imaging 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Purpose Our systematic review and meta-analysis aimed to evaluate the diagnostic performance of [18F]FDG PET/MRI vs. [18F]FET PET/MRI for recurrent glioma. Methods We searched for relevant articles in PubMed, Embase, and Web of Science until February 2023. Studies regarding the diagnostic performance of [18F]FET PET/MRI or [18F]FDG PET/MRI in recurrent glioma were included. The quality of each study was assessed using the Quality Assessment of Diagnostic Performance Studies-2 (QUADAS-2) tool. Results A total of nine studies with 310 patients were included in the analysis, the pooled sensitivity, specificity of [18F]FDG PET/MRI in detecting recurrent glioma after definitive treatment were 0.99 (95% CI 0.75–1.00) and 0.62 (95% CI 0.37–0.83), [18F]FET PET/MRI were 0.94 (95% CI 0.81–0.98) and 0.87 (95% CI 0.70–0.95), respectively. The area under curve (AUC) for [18F]FDG PET/MRI and [18F]FET PET/MRI were 0.92 (95% CI 0.89–0.94) and 0.96 (95% CI 0.94–0.97) and there is a statistical difference between the two imaging modalities (Z = 12.433, P < 0.001). Fagan nomogram indicated that when the pre-test probability was set at 50%, the post-test probability for [18F]FDG PET/MRI and [18F]FET PET/MRI could increase to 72 and 88%. Conclusions [18F]FET PET/MRI has a higher AUC compared to [18F]FDG PET/MRI in the detection of tumor recurrence in glioma. However, the results of the meta-analysis were drawn from studies with small samples. Further larger prospective studies in this setting are warranted. [ (dpeaa)DE-He213 F]FET PET/MRI (dpeaa)DE-He213 [ (dpeaa)DE-He213 F]FDG PET/MRI (dpeaa)DE-He213 Diagnostic performance (dpeaa)DE-He213 Glioma (dpeaa)DE-He213 Recurrent (dpeaa)DE-He213 Meta-analysis (dpeaa)DE-He213 Shen, Shurui aut Zhang, Lanyue aut Yang, Fuwei aut Li, Yunqian (orcid)0000-0003-2199-8618 aut Enthalten in Clinical and translational imaging Berlin : Springer Milan, 2013 11(2023), 3 vom: 09. Mai, Seite 285-295 (DE-627)742738752 (DE-600)2712000-4 2281-7565 nnns volume:11 year:2023 number:3 day:09 month:05 pages:285-295 https://dx.doi.org/10.1007/s40336-023-00563-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 11 2023 3 09 05 285-295 |
| allfieldsGer |
10.1007/s40336-023-00563-7 doi (DE-627)SPR051755726 (SPR)s40336-023-00563-7-e DE-627 ger DE-627 rakwb eng Huo, Huasong verfasserin aut The diagnostic performance of [18F]FET PET/MRI versus [18F]FDG PET/MRI for recurrent glioma: a systematic review and meta-analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Italian Association of Nuclear Medicine and Molecular Imaging 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Purpose Our systematic review and meta-analysis aimed to evaluate the diagnostic performance of [18F]FDG PET/MRI vs. [18F]FET PET/MRI for recurrent glioma. Methods We searched for relevant articles in PubMed, Embase, and Web of Science until February 2023. Studies regarding the diagnostic performance of [18F]FET PET/MRI or [18F]FDG PET/MRI in recurrent glioma were included. The quality of each study was assessed using the Quality Assessment of Diagnostic Performance Studies-2 (QUADAS-2) tool. Results A total of nine studies with 310 patients were included in the analysis, the pooled sensitivity, specificity of [18F]FDG PET/MRI in detecting recurrent glioma after definitive treatment were 0.99 (95% CI 0.75–1.00) and 0.62 (95% CI 0.37–0.83), [18F]FET PET/MRI were 0.94 (95% CI 0.81–0.98) and 0.87 (95% CI 0.70–0.95), respectively. The area under curve (AUC) for [18F]FDG PET/MRI and [18F]FET PET/MRI were 0.92 (95% CI 0.89–0.94) and 0.96 (95% CI 0.94–0.97) and there is a statistical difference between the two imaging modalities (Z = 12.433, P < 0.001). Fagan nomogram indicated that when the pre-test probability was set at 50%, the post-test probability for [18F]FDG PET/MRI and [18F]FET PET/MRI could increase to 72 and 88%. Conclusions [18F]FET PET/MRI has a higher AUC compared to [18F]FDG PET/MRI in the detection of tumor recurrence in glioma. However, the results of the meta-analysis were drawn from studies with small samples. Further larger prospective studies in this setting are warranted. [ (dpeaa)DE-He213 F]FET PET/MRI (dpeaa)DE-He213 [ (dpeaa)DE-He213 F]FDG PET/MRI (dpeaa)DE-He213 Diagnostic performance (dpeaa)DE-He213 Glioma (dpeaa)DE-He213 Recurrent (dpeaa)DE-He213 Meta-analysis (dpeaa)DE-He213 Shen, Shurui aut Zhang, Lanyue aut Yang, Fuwei aut Li, Yunqian (orcid)0000-0003-2199-8618 aut Enthalten in Clinical and translational imaging Berlin : Springer Milan, 2013 11(2023), 3 vom: 09. Mai, Seite 285-295 (DE-627)742738752 (DE-600)2712000-4 2281-7565 nnns volume:11 year:2023 number:3 day:09 month:05 pages:285-295 https://dx.doi.org/10.1007/s40336-023-00563-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 11 2023 3 09 05 285-295 |
| allfieldsSound |
10.1007/s40336-023-00563-7 doi (DE-627)SPR051755726 (SPR)s40336-023-00563-7-e DE-627 ger DE-627 rakwb eng Huo, Huasong verfasserin aut The diagnostic performance of [18F]FET PET/MRI versus [18F]FDG PET/MRI for recurrent glioma: a systematic review and meta-analysis 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Italian Association of Nuclear Medicine and Molecular Imaging 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Purpose Our systematic review and meta-analysis aimed to evaluate the diagnostic performance of [18F]FDG PET/MRI vs. [18F]FET PET/MRI for recurrent glioma. Methods We searched for relevant articles in PubMed, Embase, and Web of Science until February 2023. Studies regarding the diagnostic performance of [18F]FET PET/MRI or [18F]FDG PET/MRI in recurrent glioma were included. The quality of each study was assessed using the Quality Assessment of Diagnostic Performance Studies-2 (QUADAS-2) tool. Results A total of nine studies with 310 patients were included in the analysis, the pooled sensitivity, specificity of [18F]FDG PET/MRI in detecting recurrent glioma after definitive treatment were 0.99 (95% CI 0.75–1.00) and 0.62 (95% CI 0.37–0.83), [18F]FET PET/MRI were 0.94 (95% CI 0.81–0.98) and 0.87 (95% CI 0.70–0.95), respectively. The area under curve (AUC) for [18F]FDG PET/MRI and [18F]FET PET/MRI were 0.92 (95% CI 0.89–0.94) and 0.96 (95% CI 0.94–0.97) and there is a statistical difference between the two imaging modalities (Z = 12.433, P < 0.001). Fagan nomogram indicated that when the pre-test probability was set at 50%, the post-test probability for [18F]FDG PET/MRI and [18F]FET PET/MRI could increase to 72 and 88%. Conclusions [18F]FET PET/MRI has a higher AUC compared to [18F]FDG PET/MRI in the detection of tumor recurrence in glioma. However, the results of the meta-analysis were drawn from studies with small samples. Further larger prospective studies in this setting are warranted. [ (dpeaa)DE-He213 F]FET PET/MRI (dpeaa)DE-He213 [ (dpeaa)DE-He213 F]FDG PET/MRI (dpeaa)DE-He213 Diagnostic performance (dpeaa)DE-He213 Glioma (dpeaa)DE-He213 Recurrent (dpeaa)DE-He213 Meta-analysis (dpeaa)DE-He213 Shen, Shurui aut Zhang, Lanyue aut Yang, Fuwei aut Li, Yunqian (orcid)0000-0003-2199-8618 aut Enthalten in Clinical and translational imaging Berlin : Springer Milan, 2013 11(2023), 3 vom: 09. Mai, Seite 285-295 (DE-627)742738752 (DE-600)2712000-4 2281-7565 nnns volume:11 year:2023 number:3 day:09 month:05 pages:285-295 https://dx.doi.org/10.1007/s40336-023-00563-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 11 2023 3 09 05 285-295 |
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Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Purpose Our systematic review and meta-analysis aimed to evaluate the diagnostic performance of [18F]FDG PET/MRI vs. [18F]FET PET/MRI for recurrent glioma. Methods We searched for relevant articles in PubMed, Embase, and Web of Science until February 2023. Studies regarding the diagnostic performance of [18F]FET PET/MRI or [18F]FDG PET/MRI in recurrent glioma were included. The quality of each study was assessed using the Quality Assessment of Diagnostic Performance Studies-2 (QUADAS-2) tool. Results A total of nine studies with 310 patients were included in the analysis, the pooled sensitivity, specificity of [18F]FDG PET/MRI in detecting recurrent glioma after definitive treatment were 0.99 (95% CI 0.75–1.00) and 0.62 (95% CI 0.37–0.83), [18F]FET PET/MRI were 0.94 (95% CI 0.81–0.98) and 0.87 (95% CI 0.70–0.95), respectively. The area under curve (AUC) for [18F]FDG PET/MRI and [18F]FET PET/MRI were 0.92 (95% CI 0.89–0.94) and 0.96 (95% CI 0.94–0.97) and there is a statistical difference between the two imaging modalities (Z = 12.433, P < 0.001). Fagan nomogram indicated that when the pre-test probability was set at 50%, the post-test probability for [18F]FDG PET/MRI and [18F]FET PET/MRI could increase to 72 and 88%. Conclusions [18F]FET PET/MRI has a higher AUC compared to [18F]FDG PET/MRI in the detection of tumor recurrence in glioma. However, the results of the meta-analysis were drawn from studies with small samples. 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Huo, Huasong |
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Huo, Huasong misc [ misc F]FET PET/MRI misc F]FDG PET/MRI misc Diagnostic performance misc Glioma misc Recurrent misc Meta-analysis The diagnostic performance of [18F]FET PET/MRI versus [18F]FDG PET/MRI for recurrent glioma: a systematic review and meta-analysis |
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The diagnostic performance of [18F]FET PET/MRI versus [18F]FDG PET/MRI for recurrent glioma: a systematic review and meta-analysis (dpeaa)DE-He213 F]FET PET/MRI (dpeaa)DE-He213 F]FDG PET/MRI (dpeaa)DE-He213 Diagnostic performance (dpeaa)DE-He213 Glioma (dpeaa)DE-He213 Recurrent (dpeaa)DE-He213 Meta-analysis (dpeaa)DE-He213 |
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The diagnostic performance of [18F]FET PET/MRI versus [18F]FDG PET/MRI for recurrent glioma: a systematic review and meta-analysis |
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Huo, Huasong Shen, Shurui Zhang, Lanyue Yang, Fuwei Li, Yunqian |
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diagnostic performance of [18f]fet pet/mri versus [18f]fdg pet/mri for recurrent glioma: a systematic review and meta-analysis |
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The diagnostic performance of [18F]FET PET/MRI versus [18F]FDG PET/MRI for recurrent glioma: a systematic review and meta-analysis |
| abstract |
Purpose Our systematic review and meta-analysis aimed to evaluate the diagnostic performance of [18F]FDG PET/MRI vs. [18F]FET PET/MRI for recurrent glioma. Methods We searched for relevant articles in PubMed, Embase, and Web of Science until February 2023. Studies regarding the diagnostic performance of [18F]FET PET/MRI or [18F]FDG PET/MRI in recurrent glioma were included. The quality of each study was assessed using the Quality Assessment of Diagnostic Performance Studies-2 (QUADAS-2) tool. Results A total of nine studies with 310 patients were included in the analysis, the pooled sensitivity, specificity of [18F]FDG PET/MRI in detecting recurrent glioma after definitive treatment were 0.99 (95% CI 0.75–1.00) and 0.62 (95% CI 0.37–0.83), [18F]FET PET/MRI were 0.94 (95% CI 0.81–0.98) and 0.87 (95% CI 0.70–0.95), respectively. The area under curve (AUC) for [18F]FDG PET/MRI and [18F]FET PET/MRI were 0.92 (95% CI 0.89–0.94) and 0.96 (95% CI 0.94–0.97) and there is a statistical difference between the two imaging modalities (Z = 12.433, P < 0.001). Fagan nomogram indicated that when the pre-test probability was set at 50%, the post-test probability for [18F]FDG PET/MRI and [18F]FET PET/MRI could increase to 72 and 88%. Conclusions [18F]FET PET/MRI has a higher AUC compared to [18F]FDG PET/MRI in the detection of tumor recurrence in glioma. However, the results of the meta-analysis were drawn from studies with small samples. Further larger prospective studies in this setting are warranted. © The Author(s), under exclusive licence to Italian Association of Nuclear Medicine and Molecular Imaging 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstractGer |
Purpose Our systematic review and meta-analysis aimed to evaluate the diagnostic performance of [18F]FDG PET/MRI vs. [18F]FET PET/MRI for recurrent glioma. Methods We searched for relevant articles in PubMed, Embase, and Web of Science until February 2023. Studies regarding the diagnostic performance of [18F]FET PET/MRI or [18F]FDG PET/MRI in recurrent glioma were included. The quality of each study was assessed using the Quality Assessment of Diagnostic Performance Studies-2 (QUADAS-2) tool. Results A total of nine studies with 310 patients were included in the analysis, the pooled sensitivity, specificity of [18F]FDG PET/MRI in detecting recurrent glioma after definitive treatment were 0.99 (95% CI 0.75–1.00) and 0.62 (95% CI 0.37–0.83), [18F]FET PET/MRI were 0.94 (95% CI 0.81–0.98) and 0.87 (95% CI 0.70–0.95), respectively. The area under curve (AUC) for [18F]FDG PET/MRI and [18F]FET PET/MRI were 0.92 (95% CI 0.89–0.94) and 0.96 (95% CI 0.94–0.97) and there is a statistical difference between the two imaging modalities (Z = 12.433, P < 0.001). Fagan nomogram indicated that when the pre-test probability was set at 50%, the post-test probability for [18F]FDG PET/MRI and [18F]FET PET/MRI could increase to 72 and 88%. Conclusions [18F]FET PET/MRI has a higher AUC compared to [18F]FDG PET/MRI in the detection of tumor recurrence in glioma. However, the results of the meta-analysis were drawn from studies with small samples. Further larger prospective studies in this setting are warranted. © The Author(s), under exclusive licence to Italian Association of Nuclear Medicine and Molecular Imaging 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Purpose Our systematic review and meta-analysis aimed to evaluate the diagnostic performance of [18F]FDG PET/MRI vs. [18F]FET PET/MRI for recurrent glioma. Methods We searched for relevant articles in PubMed, Embase, and Web of Science until February 2023. Studies regarding the diagnostic performance of [18F]FET PET/MRI or [18F]FDG PET/MRI in recurrent glioma were included. The quality of each study was assessed using the Quality Assessment of Diagnostic Performance Studies-2 (QUADAS-2) tool. Results A total of nine studies with 310 patients were included in the analysis, the pooled sensitivity, specificity of [18F]FDG PET/MRI in detecting recurrent glioma after definitive treatment were 0.99 (95% CI 0.75–1.00) and 0.62 (95% CI 0.37–0.83), [18F]FET PET/MRI were 0.94 (95% CI 0.81–0.98) and 0.87 (95% CI 0.70–0.95), respectively. The area under curve (AUC) for [18F]FDG PET/MRI and [18F]FET PET/MRI were 0.92 (95% CI 0.89–0.94) and 0.96 (95% CI 0.94–0.97) and there is a statistical difference between the two imaging modalities (Z = 12.433, P < 0.001). Fagan nomogram indicated that when the pre-test probability was set at 50%, the post-test probability for [18F]FDG PET/MRI and [18F]FET PET/MRI could increase to 72 and 88%. Conclusions [18F]FET PET/MRI has a higher AUC compared to [18F]FDG PET/MRI in the detection of tumor recurrence in glioma. However, the results of the meta-analysis were drawn from studies with small samples. Further larger prospective studies in this setting are warranted. © The Author(s), under exclusive licence to Italian Association of Nuclear Medicine and Molecular Imaging 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR051755726</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230602064804.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230602s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s40336-023-00563-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR051755726</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s40336-023-00563-7-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Huo, Huasong</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="4"><subfield code="a">The diagnostic performance of [18F]FET PET/MRI versus [18F]FDG PET/MRI for recurrent glioma: a systematic review and meta-analysis</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s), under exclusive licence to Italian Association of Nuclear Medicine and Molecular Imaging 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Purpose Our systematic review and meta-analysis aimed to evaluate the diagnostic performance of [18F]FDG PET/MRI vs. [18F]FET PET/MRI for recurrent glioma. Methods We searched for relevant articles in PubMed, Embase, and Web of Science until February 2023. Studies regarding the diagnostic performance of [18F]FET PET/MRI or [18F]FDG PET/MRI in recurrent glioma were included. The quality of each study was assessed using the Quality Assessment of Diagnostic Performance Studies-2 (QUADAS-2) tool. Results A total of nine studies with 310 patients were included in the analysis, the pooled sensitivity, specificity of [18F]FDG PET/MRI in detecting recurrent glioma after definitive treatment were 0.99 (95% CI 0.75–1.00) and 0.62 (95% CI 0.37–0.83), [18F]FET PET/MRI were 0.94 (95% CI 0.81–0.98) and 0.87 (95% CI 0.70–0.95), respectively. The area under curve (AUC) for [18F]FDG PET/MRI and [18F]FET PET/MRI were 0.92 (95% CI 0.89–0.94) and 0.96 (95% CI 0.94–0.97) and there is a statistical difference between the two imaging modalities (Z = 12.433, P < 0.001). Fagan nomogram indicated that when the pre-test probability was set at 50%, the post-test probability for [18F]FDG PET/MRI and [18F]FET PET/MRI could increase to 72 and 88%. Conclusions [18F]FET PET/MRI has a higher AUC compared to [18F]FDG PET/MRI in the detection of tumor recurrence in glioma. However, the results of the meta-analysis were drawn from studies with small samples. 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