Evaluation of an Artificial Intelligence-Based 3D-Angiography for Visualization of Cerebral Vasculature.

Journal: Clinical neuroradiology
Published Date: Oct 9, 2019

Abstract

PURPOSE: The three-dimensional digital subtraction angiography (3D DSA) technique is the current standard and is based on both mask and fill runs to enable the subtraction technique. Artificial intelligence (AI)-based 3D angiography (3DA) was developed to reduce radiation dosage because only one contrast-enhanced run of the C‑arm system is required for reconstruction of DSA-like 3D volumes. The aim was the evaluation of this algorithm regarding its diagnostic information.

Authors

  • Stefan Lang
    Department of Clinical Neurosciences, Division of Neurosurgery, 1403 29 St. NW, Calgary, Alberta, T2N 2T9, Canada.
  • Philip Hoelter
    Department of Neuroradiology, University of Erlangen-Nuremberg, Schwabachanlage 6, 91054, Erlangen, Germany.
  • Manuel Schmidt
    Department of Neuroradiology, University of Erlangen-Nuremberg, Schwabachanlage 6, 91054, Erlangen, Germany.
  • Felix Eisenhut
    Department of Neuroradiology, University of Erlangen-Nuremberg, Schwabachanlage 6, 91054, Erlangen, Germany.
  • Christian Kaethner
    Angiography & Interventional X‑Ray Systems, Siemens Healthcare GmbH, Siemensstraße 1, 91301, Forchheim, Germany.
  • Markus Kowarschik
    Siemens Healthineers, Advanced Therapies, Forchheim, Germany.
  • Hannes Lücking
    Department of Neuroradiology, University of Erlangen-Nuremberg, Schwabachanlage 6, 91054, Erlangen, Germany.
  • Arnd Doerfler
    Department of Neuroradiology, University of Erlangen-Nuremberg, Schwabachanlage 6, 91054, Erlangen, Germany.

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