Automated Detection of Cerebral Aneurysms on TOF-MRA Using a Deep Learning Approach: An External Validation Study.

Journal: AJNR. American journal of neuroradiology
Published Date: Nov 10, 2022

Abstract

BACKGROUND AND PURPOSE: Cerebral aneurysms yield the risk of rupture, severe disability and death. Thus, early detection of cerebral aneurysms is crucial to ensure timely treatment, if necessary. AI-based software tools are expected to enhance radiologists' performance in detecting pathologies like cerebral aneurysms in the future. Our aim was to evaluate the diagnostic performance of an artificial intelligence-based software designed to detect intracranial aneurysms on TOF-MRA.

Authors

  • N C Lehnen
    From the Departments of Neuroradiology (N.C.L., R.H., F.C.S., F.D., A.R., D.P.) nils.lehnen@ukbonn.de.
  • R Haase
    From the Departments of Neuroradiology (N.C.L., R.H., F.C.S., F.D., A.R., D.P.).
  • F C Schmeel
    From the Departments of Neuroradiology (N.C.L., R.H., F.C.S., F.D., A.R., D.P.).
  • H Vatter
    Neurosurgery (H.V.), University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany.
  • F Dorn
    From the Departments of Neuroradiology (N.C.L., R.H., F.C.S., F.D., A.R., D.P.).
  • A Radbruch
    Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Hufelandstraße 55, 45147, Essen, Germany.
  • D Paech
    From the Departments of Neuroradiology (N.C.L., R.H., F.C.S., F.D., A.R., D.P.).

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