Paper Info
Title
Patient-specific coronary artery blood flow simulation using myocardial volume partitioning
Abstract
Using computational simulation, we can analyze cardiovascular disease in non-invasive and quantitative manners. More specifically, computational modeling and simulation technology has enabled us to analyze functional aspect such as blood flow, as well as anatomical aspect such as stenosis, from medical images without invasive measurements. Note that the simplest ways to perform blood flow simulation is to apply patient-specific coronary anatomy with other average-valued properties; in this case, however, such conditions cannot fully reflect accurate physiological properties of patients. To resolve this limitation, we present a new patient-specific coronary blood flow simulation method by myocardial volume partitioning considering artery/myocardium structural correspondence. We focus on that blood supply is closely related to the mass of each myocardial segment corresponding to the artery. Therefore, we applied this concept for setting-up simulation conditions in the way to consider many patient-specific features as possible from medical image: First, we segmented coronary arteries and myocardium separately from cardiac CT; then the myocardium is partitioned into multiple regions based on coronary vasculature. The myocardial mass and required blood mass for each artery are estimated by converting myocardial volume fraction. Finally, the required blood mass is used as boundary conditions for each artery outlet, with given average aortic blood flow rate and pressure. To show effectiveness of the proposed method, fractional flow reserve (FFR) by simulation using CT image has been compared with invasive FFR measurement of real patient data, and as a result, 77% of accuracy has been obtained.
Year
DOI
Venue
2013
10.1117/12.2007898
Proceedings of SPIE
Keywords
Field
DocType
Blood Flow Simulation,Myocardial Volume,Computational Fluid Dynamics,Fractional Flow Reserve
Artery,Fractional flow reserve,Stenosis,Artificial intelligence,Computational simulation,Computer vision,Coronary arteries,Blood flow,Internal medicine,Modeling and simulation,Cardiology,Computational fluid dynamics,Physics
Conference
Volume
ISSN
Citations 
8670
0277-786X
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Kyung Hwan Kim112517.28
Dongwoo Kang215319.98
Nahyup Kang3404.21
Hyong-euk Lee4999.55
James D. K. Kim56111.58