{"title":"Uncertainty quantification for simulating coronary artery hemodynamics in aneurysms caused by kawasaki disease","authors":"Kieun Choi , Jinyoung Seo , Jongmin Seo","doi":"10.1016/j.cmpb.2025.108834","DOIUrl":null,"url":null,"abstract":"<div><h3>Background and Objective</h3><div>This study applies an Uncertainty Quantification (UQ) framework to assess the reliability of cardiovascular simulation about coronary artery aneurysms (CAAs) caused by Kawasaki Disease (KD) for advancing clinical decision-making. The objective is to evaluate the impact of uncertainties in hemodynamic metrics, including Wall Shear Stress (WSS), Residence Time (RT), and Fractional Flow Reserve (FFR).</div></div><div><h3>Methods</h3><div>Three patient-specific aorto-coronary anatomic models were used to perform computational fluid dynamics (CFD) simulations. A reduced-order sub-modeling approach was utilized to reduce computational costs. Uncertainties were introduced to input parameters: cardiac output, inflow waveform, in-plane velocity distribution, and intramyocardial pressure. Time-varying signals were perturbed using the Karhunen–Loève expansion. 100 samples per each patient were obtained, assuming standard distributions for input parameters. Sensitivity analysis was conducted to determine the contribution of each parameter to output variability.</div></div><div><h3>Results</h3><div>A 20 % uncertainty in cardiac output and a perturbed inflow waveform with a 7 % process variance caused variability in WSS and RT of 8 % to 35 %. Sensitivity analysis revealed that cardiac output had the most significant impact, contributing over 52 % to output variability, while the inflow waveform contributed 20-30 %. The in-plane velocity distribution influenced WSS and RT by around 10 % but showed varying contributions to FFR —3 % to 27 %. Intramyocardial pressure had a negligible effect.</div></div><div><h3>Conclusions</h3><div>This study is the first to apply UQ to KD-related CAA simulations, driven by clinical needs, with extensive investigations into the uncertain input parameters. The findings highlight cardiac output as the key factor in hemodynamic variability. It emphasizes the need for precise clinical data to enhance simulation-based predictions, particularly in managing CAAs in KD patients.</div></div>","PeriodicalId":10624,"journal":{"name":"Computer methods and programs in biomedicine","volume":"268 ","pages":"Article 108834"},"PeriodicalIF":4.9000,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer methods and programs in biomedicine","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0169260725002512","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Background and Objective
This study applies an Uncertainty Quantification (UQ) framework to assess the reliability of cardiovascular simulation about coronary artery aneurysms (CAAs) caused by Kawasaki Disease (KD) for advancing clinical decision-making. The objective is to evaluate the impact of uncertainties in hemodynamic metrics, including Wall Shear Stress (WSS), Residence Time (RT), and Fractional Flow Reserve (FFR).
Methods
Three patient-specific aorto-coronary anatomic models were used to perform computational fluid dynamics (CFD) simulations. A reduced-order sub-modeling approach was utilized to reduce computational costs. Uncertainties were introduced to input parameters: cardiac output, inflow waveform, in-plane velocity distribution, and intramyocardial pressure. Time-varying signals were perturbed using the Karhunen–Loève expansion. 100 samples per each patient were obtained, assuming standard distributions for input parameters. Sensitivity analysis was conducted to determine the contribution of each parameter to output variability.
Results
A 20 % uncertainty in cardiac output and a perturbed inflow waveform with a 7 % process variance caused variability in WSS and RT of 8 % to 35 %. Sensitivity analysis revealed that cardiac output had the most significant impact, contributing over 52 % to output variability, while the inflow waveform contributed 20-30 %. The in-plane velocity distribution influenced WSS and RT by around 10 % but showed varying contributions to FFR —3 % to 27 %. Intramyocardial pressure had a negligible effect.
Conclusions
This study is the first to apply UQ to KD-related CAA simulations, driven by clinical needs, with extensive investigations into the uncertain input parameters. The findings highlight cardiac output as the key factor in hemodynamic variability. It emphasizes the need for precise clinical data to enhance simulation-based predictions, particularly in managing CAAs in KD patients.
期刊介绍:
To encourage the development of formal computing methods, and their application in biomedical research and medical practice, by illustration of fundamental principles in biomedical informatics research; to stimulate basic research into application software design; to report the state of research of biomedical information processing projects; to report new computer methodologies applied in biomedical areas; the eventual distribution of demonstrable software to avoid duplication of effort; to provide a forum for discussion and improvement of existing software; to optimize contact between national organizations and regional user groups by promoting an international exchange of information on formal methods, standards and software in biomedicine.
Computer Methods and Programs in Biomedicine covers computing methodology and software systems derived from computing science for implementation in all aspects of biomedical research and medical practice. It is designed to serve: biochemists; biologists; geneticists; immunologists; neuroscientists; pharmacologists; toxicologists; clinicians; epidemiologists; psychiatrists; psychologists; cardiologists; chemists; (radio)physicists; computer scientists; programmers and systems analysts; biomedical, clinical, electrical and other engineers; teachers of medical informatics and users of educational software.