I6 - Effect of coronary sinus reducer on oxygen delivery in ischemic conditions

Introduction: : Refractory angina is defined as persistent chest pain due to reduced myocardial blood flow and microvascular dysfunction, which can reduce myocardial blood flow. While revascularization strategies like percutaneous coronary intervention and coronary artery bypass grafting are standard treatments, an alternative therapy using a coronary sinus reducer (CSR) device is emerging as a promising intervention in patients who are not candidates for revascularization. The CSR is an hourglass shaped stent implanted in the coronary sinus (CS) to reduce venous outflow and increase coronary sinus pressure. Treatment using CSR has been shown to improve symptoms in patients in clinical studies. Specifically, CSR treatment has shown to significantly alleviate angina in 71% of patients [1,2], decrease anti-anginal medications [3], and improve wall motion during stress echocardiography [4]. It has been suggested that elevation of CS pressure can improve microvascular oxygen delivery to the under-perfused segments of the myocardium.
The underlying mechanism of CSR, however, has not been proven and remains poorly understood. Computational models can help resolve this issue by providing insights on how CSR affects microscale hemodynamics and oxygen transport occurring at the capillary level, which are difficult to measure in vivo. A recent computational modeling study4 from our group has shown how CSR affects the coronary microcirculation hemodynamics in ischemic regions under different degrees of stenosis. Here, we present a more advanced computer model that considers both oxygen transport and hemodynamics across multiple scales in the coronary vasculature to investigate the effects of CSR on oxygen-related metrics.

Materials and

Methods: : The computational framework couples a lumped 0D model of hemodynamics[5] and 1D finite element model of oxygen transport[6] (Figure 1). O2 transport in the coronary vessels to the myocytes is governed by a combination of convective delivery by the blood flow (advection), molecular diffusion within the blood plasma, and permeation across the capillary wall into surrounding tissue, as described in the governing equation. Free O2 concentrations, often expressed as partial pressure of oxygen (pO2), is the most common clinical measure used to describe pressure exerted by free O2 dissolved in blood or plasma. Through permeation from the capillary walls, free O2 enters the tissue space and the cardiomyocytes to support oxidative phosphorylation, where the O2 transport is governed by permeation, consumption, and diffusion processes[7].

Coronary Circulation Network
The entire coronary vasculature was constructed based on morphometric measurements (i.e., length, diameter, and branching pattern of vessels) reported in previous studies [8–10]. Specifically, the network starts from the aorta and branches into three major divisions corresponding to the left anterior descending (LAD), left circumflex (LCX), and right coronary (RCA) arteries. These main arteries further branch into smaller vessels downstream, eventually leading to three sections of capillary networks (Figure 1). The coronary network here, has 1647 capillary vessels, 68 arteries and 71 veins, including two vessels associated with the aorta and CS. To accurately represent the coronary circulation and account for all vessels in the heart, flow resistance and compliance of the vessels are scaled based on the branching ratios measured in pigs[8,9].

Results, Conclusions, and Discussions:: The computational framework is first validated against existing studies [5,11] on pressure and flow distributions across different vessel orders as well as measurements of oxygen-related metrics [12]. To simulate ischemia, the LCX (order 10) artery is occluded by varying the resistance-scaling factors to achieve fractional frow reserve (FFR) ranging from 0.8 (mild) to 0.1 (severe). A sensitivity analysis was performed to quantify the effects of FFR on the oxygen-related metrics in the ischemic regions. In comparison to the non-ischemic case, mean O2 concentration in moderate ischemic case was reduced by ~24% in moderate ischemic (FFR 0.6), and by ~32% in severe ischemic (FFR 0.1) cases. The model predicted an oxygen extraction ratio (OER) of ~74% in healthy conditions that increases to ~74.5% in the moderate ischemic (FFR 0.6) and to ~81% in severe ischemic (FFR 0.1) conditions, due to the increased metabolic load on tissue. The increase in OER is attributed to the lower flow rates in ischemic conditions, where the tissue needs more residing time of O2 from the blood is longer that facilitates more of its consumption by the tissue.
Thereafter, treatment using the CSR was simulated by scaling the resistance of the coronary sinus. With CS occlusion, the model predicted ~35% increase in mean blood flow of the ischemic capillary region, and ~9% increase in nonischemic regions, implying a significant flow redistribution through backflow from the venous section. A sensitivity analysis was performed to quantify the degrees of CS occlusion on the extent of redistribution and O2 delivery to the ischemic region. The hemodynamics results are used in the O2 transport model to investigate the effect of CSO on O2 delivery in ischemia. In summary, we developed a computational framework to understand the mechanistic aspects of CSR. Specifically, this study focuses on assessing the impact of CSR on flow redistribution and O2 delivery to the ischemic regions.

Acknowledgements and/or References (Optional):: References
1. Verheye S, Jolicœur EM, Behan MW, et al. Efficacy of a Device to Narrow the Coronary Sinus in Refractory Angina. New England Journal of Medicine. 2015;372(6):519-527. doi:10.1056/nejmoa1402556.
2. Zivelonghi C, Verheye S. The Coronary Sinus Reducer – Clinical Evidence and New Perspectives On An Emerging Tool in the Treatment of Refractory Angina. Heart Int. 2020;14(1):29. doi:10.17925/hi.2020.14.1.29.
3. Giannini F, Baldetti L, Ponticelli F, et al. Coronary Sinus Reducer Implantation for the Treatment of Chronic Refractory Angina. JACC Cardiovasc Interv. 2018;11(8):784-792. doi:10.1016/j.jcin.2018.01.251.
4. Wang H, Fan L, Choy JS, Kassab GS, Lee LC. Mechanisms of coronary sinus reducer for treatment of myocardial ischemia: in silico study. J Appl Physiol. 2024;136(5):1157-1169. doi:10.1152/japplphysiol.00910.2023.
5. Wang H, Fan L, Choy JS, Kassab GS, Lee LC. Simulation of coronary capillary transit time based on full vascular model of the heart. Comput Methods Programs Biomed. 2024;243:107908. doi:10.1016/j.cmpb.2023.107908.
6. Wang H, Choy JS, Kassab GS, Lee LC. Computer model coupling hemodynamics and oxygen transport in the coronary capillary network: Pulsatile vs. non-pulsatile analysis. Comput Methods Programs Biomed. 2024;258:108486. doi:10.1016/j.cmpb.2024.108486.
7. Beard DA, Bassingthwaighte JB. Modeling Advection and Diffusion of Oxygen in Complex Vascular Networks. Ann Biomed Eng. 2001;29(4):298-310. doi:10.1114/1.1359450.
8. Kassab GS, Rider CA, Tang N, Fung YC. Morphometry of pig coronary arterial trees. American Journal of Physiology-heart and Circulatory Physiology. 1993;265(1):H350-H365. doi:10.1152/ajpheart.1993.265.1.h350.
9. Kassab GS, Lin D, Fung YC. Morphometry of pig coronary venous system. American Journal of Physiology-heart and Circulatory Physiology. 1994;267(6):H2100-H2113. doi:10.1152/ajpheart.1994.267.6.h2100.
10. Kassab GS, Fung YC. Topology and dimensions of pig coronary capillary network. American Journal of Physiology-Heart and Circulatory Physiology. 1994;267(1):H319-H325. doi:10.1152/ajpheart.1994.267.1.h319.
11. Kassab GS, Berkley J, Fung YCB. Analysis of pig’s coronary arterial blood flow with detailed anatomical data. Ann Biomed Eng. 1997;25(1):204-217. doi:10.1007/bf02738551.
12. McCommis K, O’Connor R, Lesniak D, et al. Quantification of global myocardial oxygenation in humans: initial experience. Journal of Cardiovascular Magnetic Resonance. 2010;12(1):34. doi:10.1186/1532-429X-12-34.