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@ARTICLE{Mattern:276124,
      author       = {Mattern, Hendrik and Garcia-Garcia, Berta and Böwe,
                      Stefanie and Mietzner, Grazia and Jandke, Solveig and Speck,
                      Oliver and Schreiber, Stefanie},
      title        = {{V}essel distance mapping reveals mesoscopic arterial and
                      venous patterns in the putamen, v1},
      publisher    = {Zenodo},
      reportid     = {DZNE-2025-00205},
      year         = {2023},
      abstract     = {Purpose: While vessel atlases, i.e. building one global
                      mean representative vascular model, and vessel patterns,
                      i.e. finding distinct differences in how a structure is
                      vascularized across subjects, have gained momentum recently,
                      both concepts are treated as two separated entities
                      currently. The aim of this study was to bridge vessel
                      atlases and patterns by identifying distinct arterial and
                      venous vascular patterns in the human putamen at the
                      mesoscopic scale using MRI. Methods: High resolution MRI of
                      20 healthy subjects (40 hemispheres) is leveraged to compute
                      arterial and venous segmentations, respectively. The
                      recently introduced Vessel Distance Mapping (VDM) framework
                      was combined with so-called vascular fingerprints to find
                      arterial and venous patterns in an unsupervised manner,
                      respectively. As a complementary approach, qualitative
                      pattern descriptions and expert ratings were generated. The
                      patterns found are compared with each other and to the
                      global mean in native image space and after spatial
                      normalization to MNI space, respectively. Results: Automatic
                      clustering and expert rating found similar vessel patterns
                      in the putamen, with arterial and venous patterns following
                      a unimodal and bimodal distribution, respectively. When
                      neglecting patterns with single putamen assigned, the
                      automatic clustering found 4 arterial and 3 venous, while
                      the expert rating found 3 arterial and 4 venous patterns.
                      While the patterns showed distinct differences w.r.t. each
                      other, arterial vascularization in the putamen is well
                      described by one global mean with unimodal distributed
                      subject-specific variations. Venous pattern showed a bimodal
                      distribution with either a lower or higher vascularization
                      then the global mean, limiting the representative character
                      of a single global representation as commonly used in vessel
                      atlases. Conclusion: To you best knowledge, this is the
                      first description of distinctively different vessel patterns
                      in the human putamen using MRI. Further, we provide tools to
                      investigate the vasculature beyond global averages, i.e. by
                      identifying vessel patterns using either unsupervised
                      clustering or expert ratings. Future applications included
                      assessment of vessel biases in layer-specific function MRI
                      and vascular resistance and resilience mechanisms in
                      pathologies. Overall, the study advocates the use of vessel
                      pattern-specifics atlases which become more relevant with
                      increasing imaging resolutions as vessel patterns become
                      more heterogeneous and explicit vessel co-registration is no
                      longer possible.},
      keywords     = {Vessel distance mapping (Other) / Magnetic Resonance
                      Imaging (Other) / ultra-high field (Other) / vessel imaging
                      (Other) / vasculature (Other)},
      cin          = {AG Maaß},
      cid          = {I:(DE-2719)1311001},
      pnm          = {353 - Clinical and Health Care Research (POF4-353)},
      pid          = {G:(DE-HGF)POF4-353},
      typ          = {PUB:(DE-HGF)25},
      doi          = {10.5281/zenodo.8098900},
      url          = {https://pub.dzne.de/record/276124},
}