Clinical Study of Vascular Plaque Determination for Stroke Risk Assessment
Abstract
The high rate of diabetes for the veteran population (~20%) tracks with high rates of obesity and these both have increased complications that include carotid stenosis and risk of stroke. Composition information is not available for carotid stenosis even though it is a known predictor of stroke risk. Our hypothesis is that there exist correlations between the information provided by the Compositional Analysis System by Machine learning (CASM) algorithm and future outcomes for patients with carotid stenosis. This research effort involves enrolling up to 1500 subjects with significant carotid stenosis. The asymptomatic patients are followed for up to 3 years in order to determine if there are correlations between risk of stroke and the output from CASM. Also, the output of the CASM algorithm will be analyzed for key populations: e.g. diabetic vs non-diabetic and asymptomatic vs symptomatic. A total of 304 subjects have been enrolled at the two sites with a total of 402 carotid arteries. Also, 24 follow-up research ultrasound exams have been collected.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2022
- Accession Number
- AD1192593
Entities
People
- D. G. Vince
- Russell J. Fedewa
- Sheronica L. James