Abstract

Coronary artery bypass grafting (CABG) is a surgical procedure aimed at improving blood circulation to the heart muscle in individuals with having coronary artery disease. This involves transplanting a healthy artery from elsewhere in the body to bypass a blocked coronary artery. In this study, computational fluid dynamics (CFD) simulations were performed using ansysfluent software to examine the impact of CABG on partially blocked coronary arteries. This analysis considered laminar flow conditions with the application of the no-slip boundary condition and took into account the Reynolds number parameter, considering momentum and transport properties within the specified geometric, material, and physical constraints of blockage. This paper aims to mitigate coronary artery failure by optimizing surgical techniques and leveraging insights from failure studies. Here, the chosen model contributes to establishing optimal surgical protocols for CABG, ensuring the long-term patency of the graft. Through CFD analysis, blood flow dynamics in the artery postgrafting have been evaluated for varied parameters such as blockage size and position, constituting the optimization study. Through this study, optimal outcomes are achieved when the graft is positioned appropriately to maintain laminar flow conditions within the artery. The graft should be positioned with an accurate assessment of blockage size and shape to minimize the risk of heart failure due to reduced flow velocity and wall shear stress.

References

1.
Akhtar
,
S.
,
Hussain
,
Z.
,
Nadeem
,
S.
,
Najjar
,
I. M. R.
, and
Sadoun
,
A. M.
,
2023
, “
CFD Analysis on Blood Flow Inside a Symmetric Stenosed Artery: Physiology of a Coronary Artery Disease
,”
Sci. Prog.
,
106
(
2
), pp.
1
17
.10.1177/00368504231180092
2.
Zhao
,
Y. C.
,
Vatankhah
,
P.
,
Goh
,
T.
,
Michelis
,
R.
,
Kyanian
,
K.
,
Zhang
,
Y.
,
Li
,
Z.
, and
Ju
,
L. A.
,
2021
, “
Hemodynamic Analysis for Stenosis Microfluidic Model of Thrombosis With Refined Computational Fluid Dynamics Simulation
,”
Sci. Rep.
,
11
(
1
), pp.
1
10
.10.1038/s41598-021-86310-2
3.
Attar
,
H.
,
Ahmed
,
T.
,
Rabie
,
R.
,
Amer
,
A.
,
Khosravi
,
M. R.
,
Solyman
,
A.
, and
Deif
,
M. A.
,
2023
, “
Modeling and Computational Fluid Dynamics Simulation of Blood Flow Behavior Based on MRI and CT for Atherosclerosis in Carotid Artery
,”
Multimedia Tools Appl.
,
83
(
19
), pp.
56369
56390
.10.1007/s11042-023-17765-w
4.
Liu
,
C.
,
Wu
,
G.
,
Xu
,
J.
,
Xiao
,
Q.
, and
Wang
,
H.
,
2023
, “
Numerical Investigation of the Effect of Carotid Bifurcation Stenosis Degree on Pulsatility Characteristics
,”
Front. Physiol.
,
14
, pp.
1
13
.10.3389/fphys.2023.1169198
5.
AHA Statistical
Update,
2020
, “
Heart Disease and Stroke Statistics—2020 Update: A Report From the American Heart Association
,”
Circulation
,
141
(
9
), pp.
e139
e596
.10.1161/CIR.0000000000000757
6.
Rana
,
A.
,
Westein
,
E.
,
Niego
,
B.
, and
Hagemeyer
,
C. E.
,
2019
, “
Shear-Dependent Platelet Aggregation: Mechanisms and Therapeutic Opportunities
,”
Front. Cardiovasc. Med.
,
6
, p.
141
.10.3389/fcvm.2019.00141
7.
Chen
,
Y.
, and
Ju
,
L. A.
,
2020
, “
Biomechanical Thrombosis: The Dark Side of Force and Dawn of Mechano-Medicine
,”
Stroke Vascular Neurol.
,
5
(
2
), pp.
185
197
.10.1136/svn-2019-000302
8.
Brazilek
,
R. J.
,
Tovar-Lopez
,
F. J.
,
Wong
,
A. K. T.
,
Tran
,
H.
,
Davis
,
A. S.
,
McFadyen
., and
J. D.
,
Kaplan
, et al.,
2017
, “
Application of a Strain Rate Gradient Microfluidic Device to Von Willebrand’s Disease Screening
,”
Lab a Chip
,
17
(
15
), pp.
2595
2608
.10.1039/C7LC00498B
9.
Beenutty
,
K. P.
, and
Anburajan
,
M.
,
2011
, “
Simulation and Analysis of Aortic Bypass Surgery Using Computational Fluid Dynamics
,”
3rd International Conference on Electronics Computer Technology
,
Kanyakumari, India
, Apr. 8–10, Vol.
3
, pp.
339
343
.10.1109/ICECTECH.2011.5941768
10.
Fu
,
H.
,
Jiang
,
Y.
,
Yang
,
D.
,
Scheiflinger
,
F.
,
Wong
,
W. P.
, and
Springer
,
T. A.
,
2017
, “
Flow-Induced Elongation of Von Willebrand Factor Precedes Tension-Dependent Activation
,”
Nat. Commun.
,
8
(
1
), p.
324
.10.1038/s41467-017-00230-2
11.
Chen
,
Y.
,
Ju
,
L. A.
,
Zhou
,
F.
,
Liao
,
J.
,
Xue
,
L.
,
Su
,
Q. P.
,
Jin
,
D.
, et al.,
2019
, “
An Integrin β IIbβ 3 Intermediate Affinity State Mediates Biomechanical Platelet Aggregation
,”
Nat. Mater.
,
18
(
7
), pp.
760
769
.10.1038/s41563-019-0323-6
12.
Ting
,
L. H.
,
Feghhi
,
S.
,
Taparia
,
N.
,
Smith
,
A. O.
,
Karchin
,
A.
,
Lim
,
E.
,
John
,
A. S.
, et al.,
2019
, “
Contractile Forces in Platelet Aggregates Under Microfluidic Shear Gradients Reflect Platelet Inhibition and Bleeding Risk
,”
Nat. Commun.
,
10
(
1
), p.
1204
.10.1038/s41467-019-09150-9
13.
Carvalho
,
V.
,
Rodrigues
,
N.
,
Ribeiro
,
R.
,
Costa
,
P. F.
,
Teixeira
,
J. C. F.
,
Lima
,
R. A.
, and
Teixeira
,
S. F.
,
2021
, “
Hemodynamic Study in 3D Printed Stenotic Coronary Artery Models: Experimental Validation and Transient Simulation
,”
Comput. Methods Biomech. Biomed. Eng.
,
24
(
6
), pp.
623
636
.10.1080/10255842.2020.1842377
14.
Pandey
,
R.
,
Kumar
,
M.
, and
Srivastav
,
V. K.
,
2020
, “
Numerical Computation of Blood Hemodynamic Through Constricted Human Left Coronary Artery: Pulsatile Simulations
,”
Comput. Methods Programs Biomed.
,
197
, p.
105661
.10.1016/j.cmpb.2020.105661
15.
Lopes
,
D.
,
Puga
,
H.
,
Teixeira
,
J. C.
, and
Teixeira
,
S. F.
,
2019
, “
Influenceofarterialmechanicalpropertiesoncarotidblood Flow: Comparison of CFD and FSI Studies
,”
Int. J. Mech. Sci.
,
160
, pp.
209
218
.10.1016/j.ijmecsci.2019.06.029
16.
Elhanafy
,
A.
,
Elsaid
,
A.
, and
Guaily
,
A.
,
2020
, “
Numerical Investigation of Hematocrit Variation Effect on Blood Flow in an Arterial Segment With Variable Stenosis Degree
,”
J. Mol. Liq.
,
313
, p.
113550
.10.1016/j.molliq.2020.113550
17.
Carvalho
,
V.
,
Carneiro
,
F.
,
Ferreira
,
A. C.
,
Gama
,
V.
,
Teixeira
,
J. C.
, and
Teixeira
,
S.
,
2021
, “
Numerical Study of the Unsteady Flow in Simplified and Realistic Iliac Bifurcation Models
,”
Fluids
,
6
(
8
), p.
284
.10.3390/fluids6080284
18.
Carvalho
,
V.
,
Rodrigues
,
N.
,
Ribeiro
,
R.
,
Costa
,
P. F.
,
Lima
,
R. A.
, and
F.c.f. Teixeira
,
S.
,
2020
, “
3D Printed Biomodels for Flow Visualization in Stenotic Vessels: An Experimental and Numerical Study
,”
Micromachines
,
11
(
6
), p.
549
.10.3390/mi11060549
19.
Hoving
,
A. M.
,
De Vries
,
E. E.
,
Mikhal
,
J.
,
De Borst
,
G. J.
, and
Slump
,
C. H.
,
2020
, “
A Systematic Review for the Design of in Vitro Flow Studies of the Carotid Artery Bifurcation
,”
Cardiovasc. Eng. Technol.
,
11
(
2
), pp.
111
127
.10.1007/s13239-019-00448-9
20.
Zhang
,
J.-M.
,
Zhong
,
L.
,
Su
,
B.
,
Wan
,
M.
,
Yap
,
J.
,
Tham
,
J. P. L.
,
Chua
,
L. P.
,
Ghista
,
D. N.
, and
Tan
,
R. S.
,
2014
, “
Perspective on CFD Studies of Coronary Artery Disease Lesions and Hemodynamics: A Review
,”
Int. J. Numer. Methods Biomed. Eng.
,
30
(
6
), pp.
659
680
.10.1002/cnm.2625
21.
Mallick
,
A. N.
,
Chander
,
A.
,
Choudhari
,
A. P.
,
Chattar
,
H. K.
, and
Sahani
,
A.
,
2023
, “
A Review on the Role of Soft Robotics in Medical Assistive Devices
,”
Int. J. Autom. Smart Technol.
,
13
(
1
), pp.
2416
2416
.10.5875/ausmt.v13i1.2416
22.
Mallick
,
A. N.
,
Kumar
,
M.
,
Nadda
,
R.
,
Kumar
,
K. M.
,
Ralhan
,
S.
,
Mohan
,
B.
,
Repaka
,
Ramjee
., and
Sahani
,
A.
,
2024
, “
Investigation of Failure Prevention Study of Coronary Artery Bypass Grafting Using Computational Fluid Dynamics Approach
,”
ISHMT Digital Library
,
Begel House Inc.
,
IIT Madras
,
Tamil Nadu, India
.10.1615/IHMTC-2023.1980
23.
Zhong
,
L.
,
Zhang
,
J.-M.
,
Su
,
B.
,
Tan
,
R. S.
,
Allen
,
J. C.
, and
Kassab
,
G. S.
,
2018
, “
Application of Patient-Specific Computational Fluid Dynamics in Coronary and Intra-Cardiac Flow Simulations: Challenges and Opportunities
,”
Front. Physiol.
,
9
, p.
337458
.10.3389/fphys.2018.00742
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