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@ARTICLE{Pham:298182,
      author       = {S. D. T. Pham and C. Chatziantoniou and J. T. van Vliet and
                      R. J. van Tuijl and M. Bulk and M. Costagli and L. de
                      Rochefort and O. Kraff and M. Ladd$^*$ and K. Pine and I.
                      Ronen and J. C. W. Siero and M. Tosetti and A. Villringer
                      and G. J. Biessels and J. J. M. Zwanenburg},
      title        = {{B}lood {F}low {V}elocity {A}nalysis in {C}erebral
                      {P}erforating {A}rteries on 7{T} 2{D} {P}hase {C}ontrast
                      {MRI} with an {O}pen-{S}ource {S}oftware {T}ool ({SELMA}).},
      journal      = {Neuroinformatics},
      volume       = {23},
      number       = {2},
      issn         = {1539-2791},
      address      = {New York, NY},
      publisher    = {Springer},
      reportid     = {DKFZ-2025-00201},
      pages        = {11},
      year         = {2025},
      abstract     = {Blood flow velocity in the cerebral perforating arteries
                      can be quantified in a two-dimensional plane with phase
                      contrast magnetic imaging (2D PC-MRI). The velocity
                      pulsatility index (PI) can inform on the stiffness of these
                      perforating arteries, which is related to several
                      cerebrovascular diseases. Currently, there is no open-source
                      analysis tool for 2D PC-MRI data from these small vessels,
                      impeding the usage of these measurements. In this study we
                      present the Small vessEL MArker (SELMA) analysis software as
                      a novel, user-friendly, open-source tool for velocity
                      analysis in cerebral perforating arteries. The
                      implementation of the analysis algorithm in SELMA was
                      validated against previously published data with a
                      Bland-Altman analysis. The inter-rater reliability of SELMA
                      was assessed on PC-MRI data of sixty participants from three
                      MRI vendors between eight different sites. The mean velocity
                      (vmean) and velocity PI of SELMA was very similar to the
                      original results (vmean: mean difference ± standard
                      deviation: 0.1 ± 0.8 cm/s; velocity PI: mean difference ±
                      standard deviation: 0.01 ± 0.1) despite the slightly higher
                      number of detected vessels in SELMA (Ndetected: mean
                      difference ± standard deviation: 4 ± 9 vessels), which can
                      be explained by the vessel selection paradigm of SELMA. The
                      Dice Similarity Coefficient of drawn regions of interest
                      between two operators using SELMA was 0.91 (range 0.69-0.95)
                      and the overall intra-class coefficient for Ndetected,
                      vmean, and velocity PI were 0.92, 0.84, and 0.85,
                      respectively. The differences in the outcome measures was
                      higher between sites than vendors, indicating the challenges
                      in harmonizing the 2D PC-MRI sequence even across sites with
                      the same vendor. We show that SELMA is a consistent and
                      user-friendly analysis tool for small cerebral vessels.},
      keywords     = {Humans / Software / Male / Blood Flow Velocity: physiology
                      / Female / Magnetic Resonance Imaging: methods / Adult /
                      Cerebrovascular Circulation: physiology / Cerebral Arteries:
                      diagnostic imaging / Cerebral Arteries: physiology / Middle
                      Aged / Reproducibility of Results / Image Processing,
                      Computer-Assisted: methods / Algorithms / Aged / 2D PC-MRI
                      (Other) / Analysis tool (Other) / Blood flow velocity
                      (Other) / Perforating arteries (Other) / Pulsatility index
                      (Other)},
      cin          = {E020},
      ddc          = {540},
      cid          = {I:(DE-He78)E020-20160331},
      pnm          = {315 - Bildgebung und Radioonkologie (POF4-315)},
      pid          = {G:(DE-HGF)POF4-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:39841291},
      doi          = {10.1007/s12021-024-09703-4},
      url          = {https://inrepo02.dkfz.de/record/298182},
}