Back

A Constrained Mixture Theory Model to Study Autoregulation in the Coronary Circulation

Gharahi, H.; Beard, D. A.; Figueroa, C. A.; Baek, S.

2020-09-22 physiology
10.1101/2020.09.21.304030 bioRxiv
Show abstract

Coronary autoregulation is a short-term response manifested by a relatively constant flow over a wide range of perfusion pressures for a given metabolic state. This phenomenon is thought to be facilitated through a combination of mechanisms, including myogenic, shear dependent, and metabolic controls. The study of coronary autoregulation is challenging due to the coupled nature of the mechanisms and their differential effects through the coronary tree. In this paper, we developed a novel framework to study coronary autoregulation based on the constrained mixture theory. This structurally-motivated autoregulation model required calibration of anatomical and structural parameters of coronary trees via a homeostatic optimization approach using extensive literature data. Autoregulation was then simulated for two different coronary trees: subepicardial and subendocardial. The structurally calibrated model reproduced available baseline hemodynamics and autoregulation data for each coronary tree. The autoregulation analysis showed that the diameter of the intermediate and small arterioles varies the most in response to changes in perfusion pressure. Finally, we demonstrated the utility of the model in two application examples: 1) response to drops in epicardial pressure, and 2) response to drug infusion in the coronary arteries. The proposed structurally-motivated model could be extended to study long-term growth and remodeling in the coronary circulation in response to hypertension, atherosclerosis, etc. Key pointsO_LICoronary autoregulation is defined as the capability of the coronary circulation to maintain the blood supply to the heart over a range of perfusion pressures. This phenomenon is facilitated through intrinsic mechanisms that control the vascular resistance by regulating the mechanical function of smooth muscle cells. Understanding the mechanisms involved in coronary autoregulation is one of the most fundamental questions in coronary physiology. C_LIO_LIThis paper presents a structurally-motivated coronary autoregulation model that uses a nonlinear continuum mechanics approach to account for the morphometry and vessel wall composition in two coronary trees in the subepicardial and subendocardial layers. C_LIO_LIThe model is calibrated against diverse experimental data from literature and is used to study heterogeneous autoregulatory response in the coronary trees. This model drastically differs from previous models, which relied on lumped parameter model formulations, and is suited to the study of long-term pathophysiological growth and remodeling phenomena in coronary vessels. C_LI

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
Biomechanics and Modeling in Mechanobiology
25 papers in training set
Top 0.1%
28.1%
2
Frontiers in Physiology
93 papers in training set
Top 0.2%
12.7%
3
PLOS Computational Biology
1633 papers in training set
Top 4%
9.3%
50% of probability mass above
4
PLOS ONE
4510 papers in training set
Top 27%
6.5%
5
American Journal of Physiology-Heart and Circulatory Physiology
32 papers in training set
Top 0.2%
4.0%
6
Mathematical Biosciences
42 papers in training set
Top 0.2%
3.7%
7
International Journal for Numerical Methods in Biomedical Engineering
12 papers in training set
Top 0.1%
3.6%
8
Physiological Reports
35 papers in training set
Top 0.2%
2.9%
9
Biological Cybernetics
12 papers in training set
Top 0.1%
2.6%
10
Mathematical Biosciences and Engineering
23 papers in training set
Top 0.2%
2.1%
11
Journal of The Royal Society Interface
189 papers in training set
Top 2%
1.9%
12
Journal of Biomechanics
57 papers in training set
Top 0.4%
1.8%
13
Scientific Reports
3102 papers in training set
Top 57%
1.7%
14
Journal of the Mechanical Behavior of Biomedical Materials
22 papers in training set
Top 0.2%
1.4%
15
The Journal of Physiology
134 papers in training set
Top 1%
1.1%
16
Biophysical Journal
545 papers in training set
Top 5%
0.8%
17
Journal of Theoretical Biology
144 papers in training set
Top 2%
0.8%
18
Annals of Biomedical Engineering
34 papers in training set
Top 1%
0.7%
19
Journal of Experimental Biology
249 papers in training set
Top 3%
0.7%
20
Computer Methods and Programs in Biomedicine
27 papers in training set
Top 1%
0.7%
21
IFAC-PapersOnLine
12 papers in training set
Top 0.2%
0.5%
22
Journal of the American Heart Association
119 papers in training set
Top 4%
0.5%
23
Frontiers in Bioengineering and Biotechnology
88 papers in training set
Top 4%
0.5%
24
Bioengineering
24 papers in training set
Top 2%
0.5%
25
Bulletin of Mathematical Biology
84 papers in training set
Top 2%
0.5%
26
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
15 papers in training set
Top 1%
0.5%
27
iScience
1063 papers in training set
Top 40%
0.5%