% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@INPROCEEDINGS{Lohmann:908570,
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 = {{NMNIMG}-32. {DIFFERENTIATION} {OF} {PSEUDOPROGRESSION}
{FROM} {TUMOR} {PROGRESSION} {IN} {GLIOBLASTOMA} {PATIENTS}
{BASED} {ON} {FET} {PET} {RADIOMICS}},
issn = {1523-5866},
reportid = {FZJ-2022-02694},
year = {2017},
abstract = {AbstractBACKGROUNDDifferentiation of pseudoprogression
(PsP) from tumor progression (TP) in glioblastoma patients
can be difficult with standard MRI. Textural feature
analysis as part of the concept of radiomics offers a
quantitative method to describe tumor heterogeneity. We
investigated the potential of textural features of
O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET to discriminate
between PsP and TP in glioblastoma
patients.METHODSTwenty-six newly diagnosed glioblastoma
patients with MRI findings suspicious for TP within 12 weeks
after completion of chemoradiation with temozolomide
underwent an additional dynamic FET PET scan.
Volumes-of-interest were defined on summed images (20-40 min
post-injection) by a 3-dimensional auto-contouring process
using a tumor-to-brain ratio (TBR) of 1.6 or more. TBRs and
time-activity curves (TACs) of FET uptake were determined.
Dynamic FET PET parameters time-to-peak (TTP) and slope
(slope of the linear regression line 20-50 min
post-injection) were evaluated. Additionally, 39 textural
parameters were calculated using the software LifeX. The
diagnostic accuracy of TBRs, TTP, slope, and textural
parameters to discriminate between PsP and TP was evaluated
using ROC analyses using the results of histopathology or of
the clinico-radiological course as reference. In order to
further increase the diagnostic accuracy, parameters were
combined using linear logistic regression for classification
of PsP and TP.RESULTSFifteen patients had TP and 11 patients
had PsP. The parameters TBRmean, TBRmax and TTP yielded a
diagnostic accuracy to discriminate between PsP and TP of
$70\%,$ $74\%,$ $59\%,$ respectively. The dynamic FET PET
parameter slope yielded the highest diagnostic accuracy of
$81\%.$ The two best textural features showed an accuracy of
$74\%.$ Combining TBR with textural features lead to an
improved accuracy of $78\%.CONCLUSIONSTextural$ features
might yield additional valuable information for this highly
relevant clinical problem without the need for acquiring a
more time-consuming dynamic PET acquisition and should be
further evaluated prospectively in larger cohorts.},
month = {Nov},
date = {2017-11-16},
organization = {Joint Conference of 22nd Annual
Scientific Meeting and Education Day of
the Society-for-Neuro-Oncology /
Conference of the
Society-for-CNS-Interstitial-Delivery-of-the-Therapeutics
(SCIDOT) on Therapeutic Delivery to the
CNS, San Francisco (USA), 16 Nov 2017 -
19 Nov 2017},
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)1},
doi = {10.1093/neuonc/nox168.607},
url = {https://juser.fz-juelich.de/record/908570},
}