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@INPROCEEDINGS{Lohmann:864919,
      author       = {Lohmann, Philipp and Kocher, M. and Ceccon, G. and Bauer,
                      E. K. and Stoffels, G. and Viswanathan, S. and Ruge, M. I.
                      and Neumaier, B. and Shah, N. J. and Fink, G. R. and Langen,
                      K. J. and Galldiks, N.},
      title        = {{C}ombined {FET} {PET}/{MRI} radiomics differentiates
                      radiation injury from brain metastasis recurrence},
      reportid     = {FZJ-2019-04522},
      year         = {2019},
      abstract     = {L6Combined FET PET/MRI radiomics differentiates radiation
                      injury from recurrent brain metastasisP. Lohmann1, M.
                      Kocher1, G. Ceccon2, E. K. Bauer2, G. Stoffels1, S.
                      Viswanathan1, M. I. Ruge3, B. Neumaier1, N. J. Shah1, G. R.
                      Fink2, K. Langen1, N. Galldiks21Forschungszentrum Jülich,
                      Institute of Neuroscience and Medicine, Jülich; 2University
                      of Cologne, Dept. of Neurology, Cologne; 3University of
                      Cologne, Dept. of Stereotaxy and Functional Neurosurgery,
                      CologneZiel/Aim:The aim of this study was to investigate the
                      potential of combined textural feature analysis of
                      contrast-enhanced MRI (CE-MRI) and static
                      O-(2-[F-18]fluoroethyl)-L-tyrosine (FET) PET for the
                      differentiation between local recurrent brain metastasis and
                      radiation injury since CE-MRI often remains
                      inconclusive.Methodik/Methods:Fifty-two patients with new or
                      progressive contrast-enhancing brain lesions on MRI after
                      radiotherapy (predominantly stereotactic radiosurgery) of
                      brain metastases were additionally investigated using FET
                      PET. Based on histology (n = 19) or clinicoradiological
                      follow-up (n = 33), local recurrent brain metastases were
                      diagnosed in 21 patients $(40\%)$ and radiation injury in 31
                      patients $(60\%).$ Forty-two textural features were
                      calculated on both unfiltered and filtered CE-MRI and summed
                      FET PET images (20 - 40 min p.i.), using the software LIFEx.
                      After feature selection, logistic regression models using a
                      maximum of five features to avoid overfitting were
                      calculated for each imaging modality separately and for the
                      combined FET PET/MRI features. The resulting models were
                      validated using cross-validation. Diagnostic accuracies were
                      calculated for each imaging modality separately as well as
                      for the combined model.Ergebnisse/Results:For the
                      differentiation between radiation injury and recurrence of
                      brain metastasis, textural features extracted from CE-MRI
                      had a diagnostic accuracy of $81\%$ (sensitivity, $67\%;$
                      specificity, $90\%).$ FET PET textural features revealed a
                      slightly higher diagnostic accuracy of $83\%$ (sensitivity,
                      $88\%;$ specificity, $75\%).$ However, the highest
                      diagnostic accuracy was obtained when combining CE-MRI and
                      FET PET features (accuracy, $89\%;$ sensitivity, $85\%;$
                      specificity, $96\%).Schlussfolgerungen/Conclusions:Our$
                      findings suggest that combined FET PET/MRI radiomics using
                      textural feature analysis offers a great potential to
                      contribute significantly to the management of patients with
                      brain metastases.},
      month         = {Apr},
      date          = {2019-04-03},
      organization  = {Jahrestagung der Deutschen
                       Gesellschaft für Nuklearmedizin 2019,
                       Bremen (Germany), 3 Apr 2019 - 6 Apr
                       2019},
      cin          = {INM-3 / INM-4 / INM-5},
      cid          = {I:(DE-Juel1)INM-3-20090406 / I:(DE-Juel1)INM-4-20090406 /
                      I:(DE-Juel1)INM-5-20090406},
      pnm          = {572 - (Dys-)function and Plasticity (POF3-572)},
      pid          = {G:(DE-HGF)POF3-572},
      typ          = {PUB:(DE-HGF)1},
      url          = {https://juser.fz-juelich.de/record/864919},
}