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@ARTICLE{Hussein:817964,
      author       = {Hussein, Amr and Furth, Christian and Schönberger, Stefan
                      and Hundsdoerfer, Patrick and Steffen, Ingo and Amthauer,
                      Holger and Müller, Hans-Wilhelm and Hautzel, Hubertus},
      title        = {{FDG}-{PET} {R}esponse {P}rediction in {P}ediatric
                      {H}odgkin’s {L}ymphoma: {I}mpact of {M}etabolically
                      {D}efined {T}umor {V}olumes and {I}ndividualized {SUV}
                      {M}easurements on the {P}ositive {P}redictive {V}alue},
      journal      = {Cancers},
      volume       = {7},
      number       = {1},
      issn         = {2072-6694},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2016-04543},
      pages        = {287 - 304},
      year         = {2015},
      abstract     = {Background: In pediatric Hodgkin’s lymphoma (pHL) early
                      response-to-therapy prediction is metabolically assessed by
                      (18)F-FDG PET carrying an excellent negative predictive
                      value (NPV) but an impaired positive predictive value (PPV).
                      Aim of this study was to improve the PPV while keeping the
                      optimal NPV. A comparison of different PET data analyses was
                      performed applying individualized standardized uptake values
                      (SUV), PET-derived metabolic tumor volume (MTV) and the
                      product of both parameters, termed total lesion glycolysis
                      (TLG); Methods: One-hundred-eight PET datasets (PET1, n =
                      54; PET2, n = 54) of 54 children were analysed by visual and
                      semi-quantitative means. SUVmax, SUVmean, MTV and TLG were
                      obtained the results of both PETs and the relative change
                      from PET1 to PET2 (Δ in $\%)$ were compared for their
                      capability of identifying responders and non-responders
                      using receiver operating characteristics (ROC)-curves. In
                      consideration of individual variations in noise and
                      contrasts levels all parameters were additionally obtained
                      after threshold correction to lean body mass and background;
                      Results: All semi-quantitative SUV estimates obtained at
                      PET2 were significantly superior to the visual PET2
                      analysis. However, ΔSUVmax revealed the best results (area
                      under the curve, 0.92; p < 0.001; sensitivity $100\%;$
                      specificity $85.4\%;$ PPV $46.2\%;$ NPV $100\%;$ accuracy,
                      $87.0\%)$ but was not significantly superior to
                      SUVmax-estimation at PET2 and ΔTLGmax. Likewise, the lean
                      body mass and background individualization of the datasets
                      did not impove the results of the ROC analyses; Conclusions:
                      Sophisticated semi-quantitative PET measures in early
                      response assessment of pHL patients do not perform
                      significantly better than the previously proposed ΔSUVmax.
                      All analytical strategies failed to improve the impaired PPV
                      to a clinically acceptable level while preserving the
                      excellent NPV.},
      cin          = {KME / INM-4},
      ddc          = {610},
      cid          = {I:(DE-Juel1)KME-20110218 / I:(DE-Juel1)INM-4-20090406},
      pnm          = {573 - Neuroimaging (POF3-573)},
      pid          = {G:(DE-HGF)POF3-573},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:25635760},
      UT           = {WOS:000209951000010},
      doi          = {10.3390/cancers7010287},
      url          = {https://juser.fz-juelich.de/record/817964},
}