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@ARTICLE{Burth:125591,
      author       = {S. Burth and P. Kickingereder$^*$ and O. Eidel and D.
                      Tichy$^*$ and D. Bonekamp$^*$ and L. Weberling$^*$ and A.
                      Wick and S. Löw and A. Hertenstein$^*$ and M. Nowosielski
                      and H.-P. Schlemmer$^*$ and W. Wick$^*$ and M. Bendszus and
                      A. Radbruch$^*$},
      title        = {{C}linical parameters outweigh diffusion- and
                      perfusion-derived {MRI} parameters in predicting survival in
                      newly diagnosed glioblastoma.},
      journal      = {Neuro-Oncology},
      volume       = {18},
      number       = {12},
      issn         = {1523-5866},
      address      = {Oxford},
      publisher    = {Oxford Univ. Press},
      reportid     = {DKFZ-2017-01717},
      pages        = {1673 - 1679},
      year         = {2016},
      abstract     = {The purpose of this study was to determine the relevance of
                      clinical data, apparent diffusion coefficient (ADC), and
                      relative cerebral blood volume (rCBV) from dynamic
                      susceptibility contrast (DSC) perfusion and the volume
                      transfer constant (k(trans)) from dynamic contrast-enhanced
                      (DCE) perfusion for predicting overall survival (OS) and
                      progression-free survival (PFS) in newly diagnosed
                      treatment-naïve glioblastoma patients.Preoperative MR scans
                      including standardized contrast-enhanced T1 (cT1), T2 -
                      fluid-attenuated inversion recovery (FLAIR), ADC, DSC, and
                      DCE of 125 patients with subsequent histopathologically
                      confirmed glioblastoma were performed on a 3 Tesla MRI
                      scanner. ADC, DSC, and DCE parameters were analyzed in
                      semiautomatically segmented tumor volumes on
                      contrast-enhanced (CE) cT1 and hyperintense signal changes
                      on T2 FLAIR (ED). Univariate and multivariable Cox
                      regression analyses including age, sex, extent of resection
                      (EOR), and KPS were performed to assess the influence of
                      each parameter on OS and PFS.Univariate Cox regression
                      analysis demonstrated a significant association of age, KPS,
                      and EOR with PFS and age, KPS, EOR, lower ADC, and higher
                      rCBV with OS. Multivariable analysis showed independent
                      significance of male sex, KPS, EOR, and increased rCBVCE for
                      PFS, and age, sex, KPS, and EOR for OS.MRI parameters help
                      to predict OS in a univariate Cox regression analysis, and
                      increased rCBVCE is associated with shorter PFS in the
                      multivariable model. In summary, however, our findings
                      suggest that the relevance of MRI parameters is outperformed
                      by clinical parameters in a multivariable analysis, which
                      limits their prognostic value for survival prediction at the
                      time of initial diagnosis.},
      cin          = {E012 / C060 / E010 / G160 / G370},
      ddc          = {610},
      cid          = {I:(DE-He78)E012-20160331 / I:(DE-He78)C060-20160331 /
                      I:(DE-He78)E010-20160331 / I:(DE-He78)G160-20160331 /
                      I:(DE-He78)G370-20160331},
      pnm          = {315 - Imaging and radiooncology (POF3-315)},
      pid          = {G:(DE-HGF)POF3-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:27298312},
      doi          = {10.1093/neuonc/now122},
      url          = {https://inrepo02.dkfz.de/record/125591},
}