The paper titled “Non-Invasive Complete Hemodynamic Model to Investigate the Effect of Multi-Stenosis in Patient-Specific Coronary Arteries”, jointly prepared byresearch assistants Hacer Duzman and E. Cenk Ersan, andProf. Dr. M. Serdar Çelebi from the Informatics Institute Computational Science and Engineering Program at ITU, has been awarded the Best Paper Award at the European Simulation and Modelling Conference (ESM’25).

Organized by EUROSIS, the conference took place in Ghent, Belgium, from 22–24 October 2025, bringing together international researchers and experts in the fields of simulation, modeling, and computational engineering.

We sincerely congratulate the authors Hacer Duzman, E. Cenk Ersan, and M. Serdar Çelebi for their achievement.

Cardiovascular diseases are a leading cause of death worldwide. Coronary arteries can become stenosed due to atherosclerosis and impair coronary hemodynamics. Computational fluid dynamics, when combined with medical imaging, enables detailed assessment of coronary hemodynamics. However, existing computational studies of stenotic coronary arteries often isolate individual coronary branches from the aortic root and apply simplified or non-physiological boundary conditions. These modeling simplifications reduce the accuracy of representing complex physiological conditions, especially in cases involving multiple stenoses. To address these limitations, this study presents a patient-specific coronary model that integrates the right and left coronary arteries along with the sinus of Valsalva, with physiologically realistic boundary conditions implemented via lumped parameter models (LPMs) for the aortic and coronary outlets. This study aims to compare the effects of varying stenosis number, location, and severity on coronary hemodynamics. Multiple case scenarios are generated, and transient, laminar, single-phase Newtonian blood flow simulations are performed. Hemodynamic indices are analyzed to assess the impact of multi-stenosis on aortic and coronary blood flow dynamics. The proposed modeling framework facilitates a comprehensive investigation of patient-specific hemodynamic variations and supports enhanced diagnostic precision.

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