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@ARTICLE{BlancDurand:850240,
      author       = {Blanc-Durand, Paul and Van Der Gucht, Axel and Verger,
                      Antoine and Langen, Karl-Josef and Dunet, Vincent and Bloch,
                      Jocelyne and Brouland, Jean-Philippe and Nicod-Lalonde,
                      Marie and Schaefer, Niklaus and Prior, John O.},
      title        = {{V}oxel-based 18{F}-{FET} {PET} segmentation and automatic
                      clustering of tumor voxels: {A} significant association with
                      {IDH}1 mutation status and survival in patients with
                      gliomas},
      journal      = {PLoS one},
      volume       = {13},
      number       = {6},
      issn         = {1932-6203},
      address      = {Lawrence, Kan.},
      publisher    = {PLoS},
      reportid     = {FZJ-2018-04295},
      pages        = {e0199379 -},
      year         = {2018},
      abstract     = {IntroductionAim was to develop a full automatic clustering
                      approach of the time-activity curves (TAC) from dynamic
                      18F-FET PET and evaluate its association with IDH1 mutation
                      status and survival in patients with
                      gliomas.MethodsThirty-seven patients (mean age: 45±13 y)
                      with newly diagnosed gliomas and dynamic 18F-FET PET before
                      any histopathologic investigation or treatment were
                      retrospectively included. Each dynamic 18F-FET PET was
                      realigned to the first image and spatially normalized in the
                      Montreal Neurological Institute template. A tumor mask was
                      semi-automatically generated from Z-score maps. Each brain
                      tumor voxel was clustered in one of the 3 following
                      centroids using dynamic time warping and k-means clustering
                      (centroid #1: slowly increasing slope; centroid #2: rapidly
                      increasing followed by slowly decreasing slope; and centroid
                      #3: rapidly increasing followed by rapidly decreasing
                      slope). The percentage of each dynamic 18F-FET TAC within
                      tumors and other conventional 18F-FET PET parameters
                      (maximum and mean tumor-to-brain ratios [TBRmax and
                      TBRmean], time-to-peak [TTP] and slope) was compared between
                      wild-type and IDH1 mutant tumors. Their prognostic value was
                      assessed in terms of progression free-survival (PFS) and
                      overall survival (OS) by Kaplan-Meier
                      estimates.ResultsTwenty patients were IDH1 wild-type and 17
                      IDH1 mutant. Higher percentage of centroid #1 and centroid
                      #3 within tumors were positively (P = 0.016) and negatively
                      (P = 0.01) correlated with IDH1 mutated status. Also,
                      TBRmax, TBRmean, TTP, and slope discriminated significantly
                      between tumors with and without IDH1 mutation (P range 0.01
                      to 0.04). Progression occurred in 22 patients $(59\%)$ at a
                      median of 13.1 months (7.6–37.6 months) and 13 patients
                      $(35\%)$ died from tumor progression. Patients with a
                      percentage of centroid #1 > $90\%$ had a longer survival
                      compared with those with a percentage of centroid #1 <
                      $90\%$ (P = 0.003 for PFS and P = 0.028 for OS). This
                      remained significant after stratification on IDH1 mutation
                      status (P = 0.029 for PFS and P = 0.034 for OS). Compared to
                      other conventional 18F-FET PET parameters, TTP and slope
                      were associated with PFS and OS (P range 0.009 to
                      0.04).ConclusionsBased on dynamic 18F-FET PET acquisition,
                      we developed a full automatic clustering approach of TAC
                      which appears to be a valuable noninvasive diagnostic and
                      prognostic marker in patients with gliomas},
      cin          = {INM-4},
      ddc          = {500},
      cid          = {I:(DE-Juel1)INM-4-20090406},
      pnm          = {573 - Neuroimaging (POF3-573)},
      pid          = {G:(DE-HGF)POF3-573},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:29953478},
      UT           = {WOS:000436645400028},
      doi          = {10.1371/journal.pone.0199379},
      url          = {https://juser.fz-juelich.de/record/850240},
}