ArticleComputer methods and programs in biomedicine2024
Simulation of coronary capillary transit time based on full vascular model of the heart.
Article in Computer methods and programs in biomedicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- A multi-fractal vascular tree model for characterizing blood flow in cardiovascular system.Scientific reports · 2026Article
- Computational assessment of blood lipid influence on hemodynamics in human retinal vessels.Scientific reports · 2025Article
- Computer model coupling hemodynamics and oxygen transport in the coronary capillary network: Pulsatile vs. non-pulsatile analysis.Computer methods and programs in biomedicine · 2025Article
- Rapid estimation of left ventricular contractility with a physics-informed neural network inverse modeling approach.Artificial intelligence in medicine · 2024Article
- Mechanisms of coronary sinus reducer for treatment of myocardial ischemia: in silico study.Journal of applied physiology (Bethesda, Md. : 1985) · 2024Article
- Preconditioning with selective autoretroperfusion:Frontiers in bioengineering and biotechnology · 2024Article
- Review of cardiac-coronary interaction and insights from mathematical modeling.WIREs mechanisms of diseaseReview
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Capillary transit time (CTT) is a fundamental determinant of gas exchange between blood and tissues in the heart and other organs. Despite advances in experimental techniques, it remains difficult to measure coronary CTT in vivo. Here, we developed a novel computational framework that couples coronary microcirculation with cardiac mechanics in a closed-loop system that enables prediction of hemodynamics in the entire coronary network, including arteries, veins, and capillaries. We also developed a novel "particle-tracking" approach for computing CTT where "virtual tracers" are individually tracked as they traverse the capillary network. Model predictions compare well with blood pressure and flow rate distributions in the arterial network reported in previous studies. Model predictions of transit times in the capillaries (1.21 ± 1.5 s) and entire coronary network (11.8 ± 1.8 s) also agree with measurements. We show that, with increasing coronary artery stenosis (as quantified by fractional flow reserve, FFR), intravascular pressure and flow rate downstream are reduced but remain non-stationary even at 100 % stenosis because some flow (∼3 %) is redistributed from the non-occluded to the occluded territories. Importantly, the model predicts that occlusion of a large artery results in higher CTT. For moderate stenosis (FFR > 0.6), the increase in CTT (from 1.21 s without stenosis to 2.23 s at FFR=0.6) is caused by a decrease in capillary flow rate. In severe stenosis (FFR = 0.1), the increase in CTT to 14.2 s is due to both a decrease in flow rate and an increase in path length taken by "virtual tracers" in the capillary network.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.