Stroke Risk Stratification and its Validation using Ultrasonic Echolucent Carotid Wall Plaque Morphology: A Machine Learning Paradigm

Stroke risk stratification based on grayscale morphology of the ultrasound carotid wall has recently been shown to have a promise in classification of high risk versus low risk plaque or symptomatic versus asymptomatic plaques. In previous studies, this stratification has been mainly based on analysis of the far wall of the carotid artery. Due to the multifocal nature of atherosclerotic disease, the plaque growth is not restricted to the far wall alone. This paper presents a new approach for stroke risk assessment by integrating assessment of both the near and far walls of the carotid artery using grayscale morphology of the plaque.

Source: Computers in Biology and Medicine - November 25, 2016 Category: Bioinformatics Authors: Tadashi Araki, Pankaj K. Jain, Harman S. Suri, Narendra D. Londhe, Nobutaka Ikeda, Ayman El-Baz, Vimal K. Shrivastava, Luca Saba, Andrew Nicolaides, Shoaib Shafique, John R. Laird, Ajay Gupta, Jasjit S. Suri Source Type: research