Study on the Performance of a Machine Learning Algorithm Recognizing and Triaging Large Vessel Occlusions Using Non-contrast CT Scans

Overview

The goal of this prospective observational study is to assess the effectiveness and performance of Methinks AI stroke imaging software platform in acute Code Stroke patients, and as a comparator to study sites utilizing existing AI imaging stroke platforms. The main question\[s\] it aims to answer is: • Performance of and outcomes associated with the use of the Methinks AI stroke imaging medical device in real-world clinical practice.

This is a prospective observational medical device clinical trial that aims to assess the diagnostic performance of Methinks Investigational Device on detecting LVO and ICH on plain NCCT and CTA, in consecutive acute Code Stroke activations at the emergency department. Demographic, Clinical and Imaging variables will be collected from stroke onset through Day 7 or Discharge, whichever is earlier. Methinks results will be collected exclusively for research purposes and no clinical decisions will be made based on the output. Diagnostic performance of NCCT-LVO Methinks output will be assessed using DSA and/or CTA as ground truth. Presence of ICH will be assessed using an independent neuroradiologist final reading. The Clinical impact on workflow will be retrospectively estimated based on the reduction of time to decision in both transfer patients and the ones directly arriving to the emergency department (ED) Informed consent forms (ICF) will be waived, as approved by the IRB.

Conditions