Advanced radiomics techniques applied on carotid duplex ultrasound data predict adverse outcomes in acute ischemic stroke.

BACKGROUND

Acute ischemic stroke (AIS) is a leading cause of mortality and morbidity worldwide. This study explores the potential of using carotid duplex ultrasound (CDU) radiomics to predict outcomes in AIS patients, enhancing prognostic assessments through advanced imaging technologies.

METHODS

We enrolled 105 AIS patients at the Stroke Center of the First Affiliated Hospital of Soochow University. CDU images were obtained and processed using artificial intelligence to extract 1,477 radiomic features. Key features were identified and used to develop a predictive model for patient outcomes 3 months post-stroke.

RESULTS

The developed predictive model demonstrated high accuracy and clinical utility, confirmed by decision curve analysis. Inter-observer reliability was excellent, with a Cohen's kappa coefficient of 0.93, indicating consistent assessments of plaque vulnerability across different observers.

CONCLUSION

Carotid duplex ultrasound radiomics significantly enhances the ability to predict adverse outcomes in AIS, offering a precision-based approach that supports personalized management strategies. It could improve clinical outcomes by allowing targeted interventions based on specific radiomic profiles.