Radiomics-Based Prediction of Collateral Status from CT Angiography of Patients Following a Large Vessel Occlusion Stroke

Radiomics-Based Prediction of Collateral Status from CT Angiography of Patients Following a Large Vessel Occlusion Stroke

Background: A major driver of individual variation in long-term outcomes following a large vessel occlusion (LVO) stroke is the degree of collateral arterial circulation. We aimed to develop and evaluate machine-learning models that quantify LVO collateral status using admission computed tomography...

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Bibliographic Details
Main Authors: Emily W. Avery, Anthony Abou-Karam, Sandra Abi-Fadel, Jonas Behland, Adrian Mak, Stefan P. Haider, Tal Zeevi, Pina C. Sanelli, Christopher G. Filippi, Ajay Malhotra, Charles C. Matouk, Guido J. Falcone, Nils Petersen, Lauren H. Sansing, Kevin N. Sheth, Seyedmehdi Payabvash
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Diagnostics
Subjects:
stroke
large vessel occlusion
radiomics
machine learning
collateral status
Online Access:https://www.mdpi.com/2075-4418/14/5/485

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