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@INPROCEEDINGS{Behle:1043301,
      author       = {Behle, Eric and Herold, J. M. and Schug, Alexander},
      title        = {{L}everaging {E}xperimental {V}asculature {D}ata for {H}igh
                      {R}esolution {B}rain {T}umor {S}imulations},
      reportid     = {FZJ-2025-02822},
      year         = {2025},
      abstract     = {Cancer remains a leading cause of mortality.
                      Multidisciplinary studies probe its pathology to increase
                      treatment options. Computational modeling of tumors on HPC
                      resources offers insight into its progress and an avenue for
                      advancing our understanding. However, initialization and
                      parameterization of the underlying models require
                      high-resolution data from real tissue structures. Here, we
                      leveraged HPC resources and a massive dataset of a mouse
                      brain's entire vascular network. We processed these image
                      stacks into detailed 3D representations, identified brain
                      regions of interest, and conducted a series of large-scale
                      simulations to investigate how tumor growth is influenced by
                      local vascular network characteristics. By simulating tumor
                      growth with sub-cellular resolution, we can probe to which
                      extent vessel density and network length influence growth.
                      We determined that vessel density is the primary determinant
                      of growth rate. Finally, our results allowed us to
                      extrapolate tumor cell growth predictions for the entire
                      mouse brain, highlighting the critical role of vascular
                      topology in tumor progression. Such increasingly realistic
                      simulations of cancer cells may enable researchers to bridge
                      the gap between basic biology and clinical practice,
                      supporting development of cancer therapies.},
      month         = {Mar},
      date          = {2025-03-16},
      organization  = {DPG Spring Meeting 2025, Regensburg
                       (Germany), 16 Mar 2025 - 21 Mar 2025},
      subtyp        = {After Call},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / PhD no Grant -
                      Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405)},
      pid          = {G:(DE-HGF)POF4-5111 / G:(DE-Juel1)PHD-NO-GRANT-20170405},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/1043301},
}