CT angiographic radiomics signature for risk stratification in anterior large vessel occlusion stroke.

ABSTRACT:

Background and purpose

As "time is brain" in acute stroke triage, the need for automated prognostication tools continues to increase, particularly in rapidly expanding tele-stroke settings. We aimed to create an automated prognostication tool for anterior circulation large vessel occlusion (LVO) stroke based on admission CTA radiomics.

Methods

We automatically extracted 1116 radiomics features from the anterior circulation territory on admission CTAs of 829 acute LVO stroke patients who underwent mechanical thrombectomy in two academic centers. We trained, optimized, validated, and compared different machine-learning models to predict favorable outcome (modified Rankin Scale ≤ 2) at discharge and 3-month follow-up using four different input sets: "Radiomics", "Radiomics + Tr

SUBMITTER: Avery EW 

PROVIDER: S-EPMC9108990 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature