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@MISC{Lohmann:908194,
author = {Lohmann, Philipp and Lerche, Christoph and Bauer, Elena and
Steger, Jan and Stoffels, Gabriele and Blau, Tobias and
Dunkl, Veronika and Filss, Christian P and Stegmayr, Carina
and Neumaier, Bernd and Shah, Nadim J and Fink, Gereon and
Langen, Karl-Josef and Galldiks, Norbert},
title = {{NIMG}-82. {PREDICTING} {ISOCITRATE} {DEHYDROGENASE}
{GENOTYPE} {IN} {GLIOMAS} {USING} {FET} {PET} {RADIOMICS}},
issn = {1523-5866},
reportid = {FZJ-2022-02447},
year = {2017},
abstract = {AbstractBACKGROUNDWe investigated the potential of
O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET textural
features compared with static and dynamic FET PET parameters
for preoperative differentiation of IDH-mutated (mut) from
IDH-wild type (wt) gliomas.METHODSEighty-four glioma
patients underwent dynamic FET PET imaging prior to
histological confirmation on a stand-alone PET scanner (56
patients; 31 GBM-wt, 3 GBM-mut, 10 AA-wt, 7 AA-mut, 2
AII-mut, 3 ODGII-mut) or a high-resolution hybrid PET/MR
scanner (28 patients; 15 GBM-wt, 2 GBM-mut, 1 AA-wt, 7
AA-mut, 1 ODGIII-mut, 1 AII-wt, 1 AII-mut). The IDH genotype
was assessed by immunohistochemistry or direct sequencing
(if immunohistochemistry was negative). Maximum and mean
tumor-to-brain ratios (TBRmax/mean) of FET uptake were
determined and time-activity curves of FET uptake were used
to evaluate the dynamic PET parameters time-to-peak (TTP)
and slope (slope of linear regression line evaluated 20-50
min post-injection). Additionally, 39 textural parameters
were calculated using the software LifeX. The diagnostic
accuracy for IDH genotype prediction by FET PET was
evaluated using ROC analyses using neuropathological results
of IDH analysis as reference. In order to further increase
the diagnostic accuracy, parameters were combined using
linear logistic regression. Data of each scanner type were
analyzed separately.RESULTSIndependent of scanner type,
diagnostic accuracies of slope, TBRmean and TBRmax were
similar (range, $75-80\%).$ Ten textural features showed an
accuracy ranging from $71-79\%$ independent of scanner type.
For both PET scanners the combined analysis increased the
diagnostic accuracy $(84\%$ and $93\%,$
respectively).CONCLUSIONSThe combination of static and
dynamic FET PET parameters with radiomics derived from
textural feature analysis leads to a high diagnostic
accuracy to predict IDH genotype of cerebral gliomas.},
cin = {INM-4 / INM-11 / JARA-BRAIN / INM-3},
ddc = {610},
cid = {I:(DE-Juel1)INM-4-20090406 / I:(DE-Juel1)INM-11-20170113 /
I:(DE-Juel1)VDB1046 / I:(DE-Juel1)INM-3-20090406},
pnm = {5253 - Neuroimaging (POF4-525)},
pid = {G:(DE-HGF)POF4-5253},
typ = {PUB:(DE-HGF)4},
doi = {10.1093/neuonc/nox168.652},
url = {https://juser.fz-juelich.de/record/908194},
}