Multiscale Coronary Arterial Network Generation and Hemodynamics Using Patient-Specific Fractional Myocardial Blood Volume
Mostafa Mahmoudi, Arutyun Pogosyan, Amirhossein Arzani, Kim-Lien Nguyen

TL;DR
This paper introduces a method to generate detailed microvascular coronary networks from MRI data, enabling patient-specific hemodynamic simulations for heart disease.
Contribution
A novel multiscale framework for synthesizing microvascular networks using fMBV maps and MRI data, enabling patient-specific hemodynamic modeling.
Findings
Synthetic arterial networks showed strong correlation with empirical data (r > 0.87) and low variability (CoV < 0.01).
Simulated networks in an IHD patient reproduced tissue-specific morphological and functional signatures.
Mixed-effects models and Dynamic Time Warping confirmed the robustness and repeatability of the method.
Abstract
Ischemic heart disease (IHD) is the leading cause of death worldwide. Although 90% of the intramyocardial blood volume resides in the microvasculature, clinical imaging methods cannot visualize the microvascular coronary network in vivo, and non-invasive hemodynamic estimates overlook patient-specific microcirculatory contributions. Herein, we present a multiscale framework to extend the epicardial coronary tree and generate 1D microvascular networks in the myocardium based on ferumoxytol-enhanced magnetic resonance coronary imaging and fractional myocardial blood volume (fMBV) maps. Synthetic arterial networks were constructed from MRI data belonging to three swine, four healthy volunteers, and one IHD patient using a modified multistage, adaptive constrained constructive optimization approach. Hemodynamic simulations were performed in synthetic arterial networks. Morphological…
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Taxonomy
TopicsCardiac Imaging and Diagnostics · Coronary Interventions and Diagnostics · Functional Brain Connectivity Studies
