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  • Myocardial Perfusion Simulation for Coronary Artery Disease: A Coupled Patient-Specific Multiscale Model ANNALS OF BIOMEDICAL ENGINEERING Papamanolis, L., Kim, H., Jaquet, C., Sinclair, M., Schaap, M., Danad, I., van Diemen, P., Knaapen, P., Najman, L., Talbot, H., Taylor, C. A., Vignon-Clementel, I. 2021; 49 (5): 1432-1447


    Patient-specific models of blood flow are being used clinically to diagnose and plan treatment for coronary artery disease. A remaining challenge is bridging scales from flow in arteries to the micro-circulation supplying the myocardium. Previously proposed models are descriptive rather than predictive and have not been applied to human data. The goal here is to develop a multiscale patient-specific model enabling blood flow simulation from large coronary arteries to myocardial tissue. Patient vasculatures are segmented from coronary computed tomography angiography data and extended from the image-based model down to the arteriole level using a space-filling forest of synthetic trees. Blood flow is modeled by coupling a 1D model of the coronary arteries to a single-compartment Darcy myocardium model. Simulated results on five patients with non-obstructive coronary artery disease compare overall well to [[Formula: see text]O][Formula: see text]O PET exam data for both resting and hyperemic conditions. Results on a patient with severe obstructive disease link coronary artery narrowing with impaired myocardial blood flow, demonstrating the model's ability to predict myocardial regions with perfusion deficit. This is the first report of a computational model for simulating blood flow from the epicardial coronary arteries to the left ventricle myocardium applied to and validated on human data.

    View details for DOI 10.1007/s10439-020-02681-z

    View details for Web of Science ID 000595061200001

    View details for PubMedID 33263155

    View details for PubMedCentralID PMC8057976

  • Google Trends reflect allergic rhinitis symptoms related to birch and grass pollen seasons AEROBIOLOGIA Karatzas, K., Papamanolis, L., Katsifarakis, N., Riga, M., Werchan, B., Werchan, M., Berger, U., Bergmann, K. 2018; 34 (4): 437-444