| Home > Publications database > 18 F-FET PET imaging in differentiating glioma progression from treatment-related changes – a single-center experience > print |
| 001 | 865195 | ||
| 005 | 20210130002938.0 | ||
| 024 | 7 | _ | |a 10.2967/jnumed.119.234757 |2 doi |
| 024 | 7 | _ | |a 0022-3123 |2 ISSN |
| 024 | 7 | _ | |a 0097-9058 |2 ISSN |
| 024 | 7 | _ | |a 0161-5505 |2 ISSN |
| 024 | 7 | _ | |a 1535-5667 |2 ISSN |
| 024 | 7 | _ | |a 2159-662X |2 ISSN |
| 024 | 7 | _ | |a 2128/24639 |2 Handle |
| 024 | 7 | _ | |a pmid:31519802 |2 pmid |
| 024 | 7 | _ | |a WOS:000530831100030 |2 WOS |
| 037 | _ | _ | |a FZJ-2019-04731 |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Maurer, Gabriele D |0 0000-0001-7329-6007 |b 0 |
| 245 | _ | _ | |a 18 F-FET PET imaging in differentiating glioma progression from treatment-related changes – a single-center experience |
| 260 | _ | _ | |a New York, NY |c 2020 |b Soc. |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1585832734_10314 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a In glioma patients, differentiation between tumor progression (TP) and treatment-related changes (TRCs) remains challenging. Difficulties in classifying imaging alterations may result in a delay or an unnecessary discontinuation of treatment. PET using O-(2-18F-fluoroethyl)-l-tyrosine (18F-FET) has been shown to be a useful tool for detecting TP and TRCs. Methods: We retrospectively evaluated 127 consecutive patients with World Health Organization grade II–IV glioma who underwent 18F-FET PET imaging to distinguish between TP and TRCs. 18F-FET PET findings were verified by neuropathology (40 patients) or clinicoradiologic follow-up (87 patients). Maximum tumor-to-brain ratios (TBRmax) of 18F-FET uptake and the slope of the time–activity curves (20–50 min after injection) were determined. The diagnostic accuracy of 18F-FET PET parameters was evaluated by receiver-operating-characteristic analysis and χ2 testing. The prognostic value of 18F-FET PET was estimated using the Kaplan–Meier method. Results: TP was diagnosed in 94 patients (74%) and TRCs in 33 (26%). For differentiating TP from TRCs, receiver-operating-characteristic analysis yielded an optimal 18F-FET TBRmax cutoff of 1.95 (sensitivity, 70%; specificity, 71%; accuracy, 70%; area under the curve, 0.75 ± 0.05). The highest accuracy was achieved by a combination of TBRmax and slope (sensitivity, 86%; specificity, 67%; accuracy, 81%). However, accuracy was poorer when tumors harbored isocitrate dehydrogenase (IDH) mutations (91% in IDH-wild-type tumors, 67% in IDH-mutant tumors, P < 0.001). 18F-FET PET results correlated with overall survival (P < 0.001). Conclusion: In our neurooncology department, the diagnostic performance of 18F-FET PET was convincing but slightly inferior to that of previous reports. |
| 536 | _ | _ | |a 572 - (Dys-)function and Plasticity (POF3-572) |0 G:(DE-HGF)POF3-572 |c POF3-572 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef |
| 700 | 1 | _ | |a Brucker, Daniel P |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Stoffels, Gabriele |0 P:(DE-Juel1)131627 |b 2 |
| 700 | 1 | _ | |a Filipski, Katharina |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Filss, Christian P |0 P:(DE-Juel1)141877 |b 4 |
| 700 | 1 | _ | |a Mottaghy, Felix M. |0 P:(DE-Juel1)132318 |b 5 |u fzj |
| 700 | 1 | _ | |a Galldiks, Norbert |0 P:(DE-Juel1)143792 |b 6 |
| 700 | 1 | _ | |a Steinbach, Joachim P |0 P:(DE-HGF)0 |b 7 |
| 700 | 1 | _ | |a Hattingen, Elke |0 P:(DE-HGF)0 |b 8 |
| 700 | 1 | _ | |a Langen, Karl-Josef |0 P:(DE-Juel1)131777 |b 9 |e Corresponding author |
| 773 | _ | _ | |a 10.2967/jnumed.119.234757 |g p. jnumed.119.234757 - |0 PERI:(DE-600)2040222-3 |n 4 |p 505-511 |t Journal of nuclear medicine |v 61 |y 2020 |x 2159-662X |
| 856 | 4 | _ | |y Published on 2019-09-13. Available in OpenAccess from 2020-03-13. |u https://juser.fz-juelich.de/record/865195/files/Maurer_2019_Post%20Print_J%20Nucl%20Med_18F-FET%20PET%20imaging%20in%20differentiating%20glioma%20progression%20from%20treatment-related%20changes.pdf |
| 856 | 4 | _ | |y Published on 2019-09-13. Available in OpenAccess from 2020-03-13. |x pdfa |u https://juser.fz-juelich.de/record/865195/files/Maurer_2019_Post%20Print_J%20Nucl%20Med_18F-FET%20PET%20imaging%20in%20differentiating%20glioma%20progression%20from%20treatment-related%20changes.pdf?subformat=pdfa |
| 909 | C | O | |o oai:juser.fz-juelich.de:865195 |p openaire |p open_access |p VDB |p driver |p dnbdelivery |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 2 |6 P:(DE-Juel1)131627 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 4 |6 P:(DE-Juel1)141877 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 5 |6 P:(DE-Juel1)132318 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 6 |6 P:(DE-Juel1)143792 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 9 |6 P:(DE-Juel1)131777 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Decoding the Human Brain |1 G:(DE-HGF)POF3-570 |0 G:(DE-HGF)POF3-572 |2 G:(DE-HGF)POF3-500 |v (Dys-)function and Plasticity |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |
| 914 | 1 | _ | |y 2020 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1030 |2 StatID |b Current Contents - Life Sciences |
| 915 | _ | _ | |a Embargoed OpenAccess |0 StatID:(DE-HGF)0530 |2 StatID |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b J NUCL MED : 2017 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0110 |2 StatID |b Science Citation Index |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1110 |2 StatID |b Current Contents - Clinical Medicine |
| 915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b J NUCL MED : 2017 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0310 |2 StatID |b NCBI Molecular Biology Database |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0320 |2 StatID |b PubMed Central |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-3-20090406 |k INM-3 |l Kognitive Neurowissenschaften |x 0 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-4-20090406 |k INM-4 |l Physik der Medizinischen Bildgebung |x 1 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-11-20170113 |k INM-11 |l Jara-Institut Quantum Information |x 2 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)INM-3-20090406 |
| 980 | _ | _ | |a I:(DE-Juel1)INM-4-20090406 |
| 980 | _ | _ | |a I:(DE-Juel1)INM-11-20170113 |
| 980 | 1 | _ | |a FullTexts |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|