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@ARTICLE{Freitag:130782,
      author       = {M. Freitag$^*$ and M. Fenchel and P. Bäumer$^*$ and T.
                      Heußer$^*$ and C. Rank$^*$ and M. Kachelrieß$^*$ and D.
                      Paech$^*$ and K. Kopka$^*$ and S. Bickelhaupt$^*$ and A.
                      Dimitrakopoulou-Strauss$^*$ and K. Maier-Hein$^*$ and R. O.
                      Floca$^*$ and M. Ladd$^*$ and H.-P. Schlemmer$^*$ and F.
                      Maier$^*$},
      title        = {{I}mproved clinical workflow for simultaneous whole-body
                      {PET}/{MRI} using high-resolution {CAIPIRINHA}-accelerated
                      {MR}-based attenuation correction.},
      journal      = {European journal of radiology},
      volume       = {96},
      issn         = {0720-048X},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {DKFZ-2017-05860},
      pages        = {12 - 20},
      year         = {2017},
      abstract     = {To explore the value and reproducibility of a novel
                      magnetic resonance based attenuation correction (MRAC) using
                      a CAIPIRINHA-accelerated T1-weighted Dixon 3D-VIBE sequence
                      for whole-body PET/MRI compared to the clinical standard.The
                      PET raw data of 19 patients from clinical routine were
                      reconstructed with standard MRAC (MRACstd) and the novel
                      MRAC (MRACcaipi), a prototype CAIPIRINHA accelerated Dixon
                      3D-VIBE sequence, both acquired in 19 s/bed position. Volume
                      of interests (VOIs) for liver, lung and all voxels of the
                      total image stack were created to calculate standardized
                      uptake values (SUVmean) followed by inter-method agreement
                      (Passing-Bablok regression, Bland-Altman analysis). A
                      voxel-wise SUV comparison per patient was performed for
                      intra-individual correlation between MRACstd and MRACcaipi.
                      Difference images (MRACstd-MRACcaipi) of attenuation maps
                      and SUV images were calculated. The image quality of
                      in/opposed-phase water and fat images obtained from
                      MRACcaipi was assessed by two readers on a 5-point
                      Likert-scale including intra-class coefficients for
                      inter-reader agreement.SUVmean correlations of VOIs
                      demonstrated high linearity (0.95<Spearman's rho<1,
                      p<0.0001, respectively), substantiated by voxel-wise SUV
                      scatter-plots (1.79×10(8) pixels). Outliers could be
                      explained by different physiological conditions between the
                      scans such as different segmentation of air-containing
                      tissue, lungs, kidneys, metal implants, diaphragm edge or
                      small air bubbles in the gastrointestinal tracts that moved
                      between MRAC acquisitions. Nasal sinuses and the trachea
                      were better segmented in MRACcaipi. High-resolution T1w
                      Dixon 3D VIBE images were acquired in all cases and could be
                      used for PET/MRI fusion. MRACcaipi images were of high
                      diagnostic quality (4.2±0.8) with 0.92-0.96 intra-class
                      correlation.The novel prototype MRACcaipi extends the value
                      for attenuation correction by providing a high spatial
                      resolution DIXON-based dataset suited for diagnostic
                      assessment towards time-efficient whole-body PET/MRI.},
      cin          = {E010 / E020 / E025 / E030 / E060 / E132 / E071},
      ddc          = {610},
      cid          = {I:(DE-He78)E010-20160331 / I:(DE-He78)E020-20160331 /
                      I:(DE-He78)E025-20160331 / I:(DE-He78)E030-20160331 /
                      I:(DE-He78)E060-20160331 / I:(DE-He78)E132-20160331 /
                      I:(DE-He78)E071-20160331},
      pnm          = {315 - Imaging and radiooncology (POF3-315)},
      pid          = {G:(DE-HGF)POF3-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:29103469},
      doi          = {10.1016/j.ejrad.2017.09.007},
      url          = {https://inrepo02.dkfz.de/record/130782},
}