Predicting incomplete occlusion of intracranial aneurysms treated with flow diverters using machine learning models.

Journal: Journal of neurosurgery
PMID: 38039540

Abstract

OBJECTIVE: Intracranial saccular aneurysms are vascular malformations responsible for 80% of nontraumatic brain hemorrhage. Recently, flow diverters have been used as a less invasive therapeutic alternative for surgery. However, they fail to achieve complete occlusion after 6 months in 25% of cases. In this study, the authors built a tool, using machine learning (ML), to predict the aneurysm occlusion outcome 6 months after treatment with flow diverters.

Authors

  • Bassel Hammoud
    1Biomedical Engineering Program and.
  • Julia El Zini
    2Department of Electrical and Computer Engineering, American University of Beirut, Lebanon.
  • Mariette Awad
    Department of Electrical and Computer Engineering, American University of Beirut, Lebanon. Electronic address: ma162@aub.edu.lb.
  • Ahmad Sweid
    Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, USA. Electronic address: ahmad.sweid@jefferson.edu.
  • Stavropoula Tjoumakaris
    Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA.
  • Pascal Jabbour
    Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA. Electronic address: pascal.jabbour@jefferson.edu.

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