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Permanent Cerebral Vessel Occlusion via Double Ligature and Transection
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Machine Learning-Enabled Automated Large Vessel Occlusion Detection Improves Transfer Times at Primary Stroke

Ngoc Mai Le1, Ananya S Iyyangar1, Youngran Kim2

  • 1Department of Neurology McGovern Medical School at UTHealth, Houston Houston TX United States.

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Automated large vessel occlusion (LVO) detection using AI significantly reduced door-in-door-out times at primary stroke centers. This accelerates care for acute ischemic stroke patients needing transfer for endovascular stroke therapy.

Keywords:
CT angiogramartificial intelligenceendovascular therapyimagingmachine learningstroke

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Area of Science:

  • Neurology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Optimizing door-in-door-out (DIDO) times is crucial for acute ischemic stroke patients with large vessel occlusion (LVO) requiring transfer for endovascular stroke therapy (EVT).
  • Primary stroke centers (PSCs) play a key role in the initial management of these critical cases.

Purpose of the Study:

  • To evaluate the impact of automated LVO detection via artificial intelligence (AI) on DIDO times at PSCs.
  • To determine if AI implementation increases the proportion of patients receiving EVT after transfer.

Main Methods:

  • A prospective multicenter registry identified LVO acute ischemic stroke patients at 7 Greater Houston PSCs.
  • A machine learning (AI) algorithm (Viz.AI) for LVO detection was implemented across all participating hospitals.
  • DIDO time was the primary outcome, analyzed using multivariable linear regression; EVT likelihood was a secondary outcome.

Main Results:

  • Among 115 patients (80 pre-AI, 35 post-AI), automated LVO detection was associated with a significant reduction in DIDO time (106 minutes).
  • The most common occlusions were in the middle cerebral artery (51.3%) and internal carotid artery (25.2%).
  • No significant difference was observed in the likelihood of receiving EVT post-transfer (OR, 2.13).

Conclusions:

  • Implementing AI for automated LVO detection significantly decreases DIDO times at PSCs.
  • This technology streamlines patient evaluation, potentially improving outcomes for stroke patients requiring transfer for advanced care.