Deep learning-assistance significantly increases the detection sensitivity of neurosurgery residents for intracranial aneurysms in subarachnoid hemorrhage.

Journal: Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
PMID:

Abstract

OBJECTIVE: The purpose of this study was to evaluate the effectiveness of a deep learning model (DLM) in improving the sensitivity of neurosurgery residents to detect intracranial aneurysms on CT angiography (CTA) in patients with aneurysmal subarachnoid hemorrhage (aSAH).

Authors

  • Lukas Goertz
    Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
  • Stephanie T Jünger
    Center for Neurosurgery, Department of General Neurosurgery, University of Cologne, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany.
  • David Reinecke
    Department of Stereotactic and Functional Neurosurgery, Center for Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
  • Niklas von Spreckelsen
    Department of General Neurosurgery, Center for Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
  • Rahil Shahzad
    Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden PO Box 9600, 2300 RC, The Netherlands. Electronic address: r.shahzad@lumc.nl.
  • Frank Thiele
    Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany.
  • Kai Roman Laukamp
    Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany.
  • Marco Timmer
    Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne.
  • Roman Johannes Gertz
    Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
  • Carsten Gietzen
    From the Department of Neurology (H.G., M.H.T.S., C.W., J.D., N.R., G.R.F., O.A.O.), Faculty of Medicine and University Hospital Cologne; Division of Cardiology, Pneumology, Angiology and Intensive Care (C.A., S. Baldus), Department of Internal Medicine III, University of Cologne; Department of Neurology (S. Bittner), University Medical Center Mainz; Cognitive Neuroscience (N.R., O.A.O.), Institute of Neuroscience and Medicine (INM-3), Research Center Jülich; and Institute for Diagnostic and Interventional Radiology (C.Z., C.G., M.S.), Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany.
  • Kenan Kaya
    Department of Diagnostic and Interventional Radiology University Hospital Cologne Cologne Germany.
  • Jan-Peter Grunz
    Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany. Electronic address: Grunz_J@ukw.de.
  • Marc Schlamann
    Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
  • Christoph Kabbasch
  • Jan Borggrefe
    Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany. jan.borggrefe@uk-koeln.de.
  • Lenhard Pennig
    Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany.