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@ARTICLE{Lohmann:890229,
      author       = {Lohmann, Philipp and Elahmadawy, Mai A. and Gutsche, Robin
                      and Werner, Jan-Michael and Bauer, Elena K. and Ceccon,
                      Garry and Kocher, Martin and Lerche, Christoph W. and Rapp,
                      Marion and Fink, Gereon R. and Shah, Nadim J. and Langen,
                      Karl-Josef and Galldiks, Norbert},
      title        = {{FET} {PET} {R}adiomics for {D}ifferentiating
                      {P}seudoprogression from {E}arly {T}umor {P}rogression in
                      {G}lioma {P}atients {P}ost-{C}hemoradiation},
      journal      = {Cancers},
      volume       = {12},
      number       = {12},
      issn         = {2072-6694},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2021-00816},
      pages        = {3835 -},
      year         = {2020},
      abstract     = {Currently, a reliable diagnostic test for differentiating
                      pseudoprogression from early tumor progression is lacking.
                      We explored the potential of
                      O-(2-[18F]fluoroethyl)-L-tyrosine (FET) positron emission
                      tomography (PET) radiomics for this clinically important
                      task. Thirty-four patients (isocitrate dehydrogenase
                      (IDH)-wildtype glioblastoma, $94\%)$ with progressive
                      magnetic resonance imaging (MRI) changes according to the
                      Response Assessment in Neuro-Oncology (RANO) criteria within
                      the first 12 weeks after completing temozolomide
                      chemoradiation underwent a dynamic FET PET scan. Static and
                      dynamic FET PET parameters were calculated. For radiomics
                      analysis, the number of datasets was increased to 102 using
                      data augmentation. After randomly assigning patients to a
                      training and test dataset, 944 features were calculated on
                      unfiltered and filtered images. The number of features for
                      model generation was limited to four to avoid data
                      overfitting. Eighteen patients were diagnosed with early
                      tumor progression, and 16 patients had pseudoprogression.
                      The FET PET radiomics model correctly diagnosed
                      pseudoprogression in all test cohort patients (sensitivity,
                      $100\%;$ negative predictive value, $100\%).$ In contrast,
                      the diagnostic performance of the best FET PET parameter
                      (TBRmax) was lower (sensitivity, $81\%;$ negative predictive
                      value, $80\%).$ The results suggest that FET PET radiomics
                      helps diagnose patients with pseudoprogression with a high
                      diagnostic performance. Given the clinical significance,
                      further studies are warranted},
      cin          = {INM-3 / INM-4 / INM-11},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-3-20090406 / I:(DE-Juel1)INM-4-20090406 /
                      I:(DE-Juel1)INM-11-20170113},
      pnm          = {572 - (Dys-)function and Plasticity (POF3-572) / DFG
                      project 428090865 - Radiomics basierend auf MRT und
                      Aminosäure PET in der Neuroonkologie},
      pid          = {G:(DE-HGF)POF3-572 / G:(GEPRIS)428090865},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {33353180},
      UT           = {WOS:000601842800001},
      doi          = {10.3390/cancers12123835},
      url          = {https://juser.fz-juelich.de/record/890229},
}