Title
Atherosclerotic Plaque Growth Prediction In Coronary Arteries Using A Computational Multi-Level Model; The Effect Of Diabetes.
Abstract
Atherosclerosis is the one of the major causes of mortality worldwide, urging the need for its treatment. This study is aiming to investigate the role of diabetes in the atherosclerotic plaque growth mechanisms through the utilization of a multi-level numerical model. To accomplish this, we developed a proof-of-concept mathematical model of the diabetes effect to plaque growth, that has been coupled to a state-of-the-art multi-level numerical model of plaque growth. Diabetes main effect is the increase of the average blood glucose concentration, which causes the decrease of the endothelial nitric oxide production rate by affecting several biologic pathways. Nitric oxide is a signaling molecule that regulates the endothelial flow rates, and any abnormal alteration leads to endothelial dysfunction, the major culprit of atherosclerosis. The derived model considers the modeling of blood flow in lumen and of species transport and reactions in the arterial wall. The considered factors include: (i) LDL, (ii) HDL, (iii) oxidized LDL, (iv) monocytes, (v) macrophages, (vi) cytokines, (vii) smooth muscle cells (contractile & synthetic), and (viii) collagen. The model is validated using 10 patients' reconstructed arterial data in two time-points. More specifically, baseline geometries are used as an input to our model, while follow-up geometries are used as benchmark for our model's output. The results presented a high coefficient of determination between the simulated with diabetes effect and the real follow-up geometries of 0.634.
Year
DOI
Venue
2019
10.1109/BIBE.2019.00132
2019 IEEE 19TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE)
Keywords
DocType
ISSN
atherosclerotic plaque prediction, stenosis prediction, diabetes, finite element modeling
Conference
2471-7819
Citations 
PageRank 
References 
0
0.34
0
Authors
7