Predicting hemodynamic indices in coronary artery aneurysms using response surface method: An application in Kawasaki disease

Alireza Asadbeygi, Simon Lee, John Kovalchin, Hoda Hatoum*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Background and objectives: Coronary artery aneurysms (CAA), such as those in Kawasaki Disease (KD), induce hemodynamic alterations associated with thrombosis and atherosclerosis. Current clinical routines assess the risk level of the CAA cases based on the Z-Score, which considers the body surface area (BSA) and the CAA's diameter. A full geometric characterization and impact on hemodynamic metrics and their correlation with thrombotic risks have not been systematically investigated. The goal of this study was to investigate the effect of CAA shape indices on local hemodynamics using the response surface method (RSM) through considering KD applications. Methods: Transient computational fluid dynamics (CFD) simulations have been performed on idealized CAA geometries defined by geometrical ratios combining neck diameter, CAA diameter and CAA length. The results were used to develop full quadratic regression models of the indices using the response surface method (RSM). Validation using patient-specific KD models was performed. Results: The results indicated that the aneurysm diameter is the main determining factor in the thrombotic risk of CAA patients, which is consistent with clinical guidelines. Furthermore, it was observed that in most CAA cases having the same diameter, the one with the shorter length experiences higher RRT values, indicating flow stagnation and circulation. Conclusions: The developed regression models can be used to ultimately assess the thrombotic risk of CAA cases from the hemodynamic perspective. The applicability of these models was tested on 2 KD patient specific models, with close values achieved between the models and the patient-specific results.

Original languageEnglish (US)
Article number107007
JournalComputer Methods and Programs in Biomedicine
Volume224
DOIs
StatePublished - Sep 2022

Funding

This work is partially funded by Michigan Technological University's Research Excellence Fund. Alireza Asadbeygi is partly funded by the Blue Cross Blue Shield of Michigan Foundation. No other external funding was received.

Keywords

  • Computational fluid dynamics (CFD)
  • Coronary artery aneurysm (CAA)
  • Hemodynamics prediction
  • Kawasaki disease(KD)
  • Response surface method (RSM)

ASJC Scopus subject areas

  • Software
  • Health Informatics
  • Computer Science Applications

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