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@ARTICLE{SaboridoMoral:284386,
      author       = {J. D. Saborido-Moral and M. Fernández-Patón and N.
                      Tejedor-Aguilar and A. Cristian-Marín and I.
                      Torres-Espallardo and J. M. Campayo-Esteban and J.
                      Pérez-Calatayud and D. Baltas$^*$ and L. Martí-Bonmatí
                      and M. Carles},
      title        = {{F}ree automatic software for quality assurance of computed
                      tomography calibration, edges and radiomics metrics
                      reproducibility.},
      journal      = {Physica medica},
      volume       = {114},
      issn         = {1120-1797},
      address      = {Amsterdam},
      publisher    = {Elsevier},
      reportid     = {DKFZ-2023-01980},
      pages        = {103153},
      year         = {2023},
      abstract     = {To develop a QA procedure, easy to use, reproducible and
                      based on open-source code, to automatically evaluate the
                      stability of different metrics extracted from CT images:
                      Hounsfield Unit (HU) calibration, edge characterization
                      metrics (contrast and drop range) and radiomic features.The
                      QA protocol was based on electron density phantom imaging.
                      Home-made open-source Python code was developed for the
                      automatic computation of the metrics and their
                      reproducibility analysis. The impact on reproducibility was
                      evaluated for different radiation therapy protocols, and
                      phantom positions within the field of view and systems, in
                      terms of variability (Shapiro-Wilk test for 15 repeated
                      measurements carried out over three days) and comparability
                      (Bland-Altman analysis and Wilcoxon Rank Sum Test or Kendall
                      Rank Correlation Coefficient).Regarding intrinsic
                      variability, most metrics followed a normal distribution
                      $(88\%$ of HU, $63\%$ of edge parameters and $82\%$ of
                      radiomic features). Regarding comparability, HU and contrast
                      were comparable in all conditions, and drop range only in
                      the same CT scanner and phantom position. The percentages of
                      comparable radiomic features independent of protocol,
                      position and system were $59\%,$ $78\%$ and $54\%,$
                      respectively. The non-significantly differences in HU
                      calibration curves obtained for two different institutions
                      $(7\%)$ translated in comparable Gamma Index G (1 mm, $1\%,$
                      $>99\%).An$ automated software to assess the reproducibility
                      of different CT metrics was successfully created and
                      validated. A QA routine proposal is suggested.},
      keywords     = {Automatic quality assurance (Other) / Computed tomography
                      (Other) / Radiomics (Other) / Reproducibility (Other)},
      cin          = {FR01},
      ddc          = {610},
      cid          = {I:(DE-He78)FR01-20160331},
      pnm          = {899 - ohne Topic (POF4-899)},
      pid          = {G:(DE-HGF)POF4-899},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:37778209},
      doi          = {10.1016/j.ejmp.2023.103153},
      url          = {https://inrepo02.dkfz.de/record/284386},
}