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@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},
}