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@ARTICLE{Deike:125685,
      author       = {K. Deike$^*$ and B. P. O. Wiestler$^*$ and M. Graf$^*$ and
                      C. Reimer and R. O. Floca$^*$ and P. Bäumer$^*$ and P.
                      Kickingereder$^*$ and S. Heiland and H.-P. Schlemmer$^*$ and
                      W. Wick$^*$ and M. Bendszus and A. Radbruch$^*$},
      title        = {{P}rognostic value of combined visualization of {MR}
                      diffusion and perfusion maps in glioblastoma.},
      journal      = {Journal of neuro-oncology},
      volume       = {126},
      number       = {3},
      issn         = {1573-7373},
      address      = {Dordrecht [u.a.]},
      publisher    = {Springer Science + Business Media B.V},
      reportid     = {DKFZ-2017-01811},
      pages        = {463 - 472},
      year         = {2016},
      abstract     = {We analyzed whether the combined visualization of decreased
                      apparent diffusion coefficient (ADC) values and increased
                      cerebral blood volume (CBV) in perfusion imaging can
                      identify prognosis-related growth patterns in patients with
                      newly diagnosed glioblastoma. Sixty-five consecutive
                      patients were examined with diffusion and dynamic
                      susceptibility-weighted contrast-enhanced perfusion weighted
                      MRI. ADC and CBV maps were co-registered on the T1-w image
                      and a region of interest (ROI) was manually delineated
                      encompassing the enhancing lesion. Within this ROI pixels
                      with ADC values <the 30th percentile (ADCmin), pixels with
                      CBV values >the 70th percentile (CBVmax) and the
                      intersection of pixels with ADCmin and CBVmax were
                      automatically calculated and visualized. Initially, all
                      tumors with a mean intersection greater than the upper
                      quartile of the normally distributed mean intersection of
                      all patients were subsumed to the first growth pattern
                      termed big intersection (BI). Subsequently, the remaining
                      tumors' growth patterns were categorized depending on the
                      qualitative representation of ADCmin, CBVmax and their
                      intersection. Log-rank test exposed a significantly longer
                      overall survival of BI (n = 16) compared to non-BI group (n
                      = 49) (p = 0.0057). Thirty-one, four and 14 patients of the
                      non-BI group were classified as predominant ADC-, CBV- and
                      mixed growth group, respectively. In a multivariate Cox
                      regression model, the BI-, CBV- and mixed groups had
                      significantly lower adjusted hazard ratios (p-value,
                      α(Bonferroni) < 0.006) when compared to the reference group
                      ADC: 0.29 (0.0027), 0.11 (0.038) and 0.33 (0.0059). Our
                      study provides evidence that the combination of diffusion
                      and perfusion imaging allows visualization of different
                      glioblastoma growth patterns that are associated with
                      prognosis. A possible biological hypothesis for this finding
                      could be the interpretation of the ADCmin fraction as the
                      invasion-front of tumor cells while the CBVmax fraction
                      might represent the vascular rich tumor border that is
                      'trailing behind' the invasion-front in the ADC group.},
      cin          = {E012 / G370 / C020 / E071 / E010 / L101},
      ddc          = {610},
      cid          = {I:(DE-He78)E012-20160331 / I:(DE-He78)G370-20160331 /
                      I:(DE-He78)C020-20160331 / I:(DE-He78)E071-20160331 /
                      I:(DE-He78)E010-20160331 / I:(DE-He78)L101-20160331},
      pnm          = {315 - Imaging and radiooncology (POF3-315)},
      pid          = {G:(DE-HGF)POF3-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:26518541},
      doi          = {10.1007/s11060-015-1982-z},
      url          = {https://inrepo02.dkfz.de/record/125685},
}