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@ARTICLE{Lauer:282900,
      author       = {E. M. Lauer and E. Riegler and J. A. Mutter and S. K. Alig
                      and S. Bleul and J. Kuehn and L. Ranganathan and C. Klingler
                      and T. Demerath and U. Würtemberger and A. Rau and J. Weiß
                      and M. Eisenblaetter and F. Bamberg and M. Prinz and J.
                      Finke and J. Duyster and G. Illerhaus and M. Diehn and A. A.
                      Alizadeh and E. Schorb and P. C. Reinacher and F.
                      Scherer$^*$},
      title        = {{I}mproved early outcome prediction by {MRI}-based 3{D}
                      tumor volume assessment in patients with {CNS} lymphomas.},
      journal      = {Neuro-Oncology},
      volume       = {26},
      number       = {2},
      issn         = {1522-8517},
      address      = {Oxford},
      publisher    = {Oxford Univ. Press},
      reportid     = {DKFZ-2023-01893},
      pages        = {374–386},
      year         = {2024},
      note         = {26(2), pp. 374–386, 2024},
      abstract     = {Central nervous system lymphomas (CNSL) display remarkable
                      clinical heterogeneity, yet accurate prediction of outcomes
                      remains challenging. The IPCG criteria are widely used in
                      routine practice for the assessment of treatment response.
                      However, the value of the IPCG criteria for ultimate outcome
                      prediction is largely unclear, mainly due to the uncertainty
                      in delineating complete from partial responses during and
                      after treatment.We explored various MRI features including
                      semi-automated 3D tumor volume measurements at different
                      disease milestones and their association with survival in 93
                      CNSL patients undergoing curative-intent treatment.At
                      diagnosis, patients with more than three lymphoma lesions,
                      periventricular involvement, and high 3D tumor volumes
                      showed significantly unfavorable PFS and OS. At first
                      interim MRI during treatment, the IPCG criteria failed to
                      discriminate outcomes in responding patients. Therefore, we
                      randomized these patients into training and validation
                      cohorts to investigate whether 3D tumor volumetry could
                      improve outcome prediction. We identified a 3D tumor volume
                      reduction of $≥97\%$ as the optimal threshold for risk
                      stratification (=3D early response, $3D_ER).$ Applied to the
                      validation cohort, patients achieving $3D_ER$ had
                      significantly superior outcomes. In multivariate analyses,
                      $3D_ER$ was independently prognostic of PFS and OS. Finally,
                      we leveraged prognostic information from 3D MRI features and
                      circulating biomarkers to build a composite metric that
                      further improved outcome prediction in CNSL.We developed
                      semi-automated 3D tumor volume measurements as strong and
                      independent early predictors of clinical outcomes in CNSL
                      patients. These radiologic features could help improve risk
                      stratification and help guide future treatment approaches.},
      keywords     = {CNS lymphoma (Other) / Circulating tumor DNA (Other) /
                      Composite biomarker (Other) / Improved early outcome
                      prediction (Other) / MRI-based 3D volumetry (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:37713267},
      doi          = {10.1093/neuonc/noad177},
      url          = {https://inrepo02.dkfz.de/record/282900},
}