title: Physiome approach for the analysis of vascular flow reserve in the heart and brain.
abstract: This work reviews the key aspects of coronary and neurovascular flow reserves with an emphasis on physiomic modeling characteristics by the use of a variety of numerical approaches. First, we explain the definition of fractional flow reserve (FFR) in coronary artery and introduce its clinical significance. Then, computational researches for obtaining FFR are reviewed, and their clinical outcomes are compared. In the case of cerebrovascular reserve (CVR), in spite of substantial progress in the simulation of cerebral hemodynamics, only a few computational studies exist. Thus, we discuss the limitations of CVR simulation study and suggest the challenging issue to overcome these. Also, the future direction of physiomic researches for the flow reserves in coronary arteries and cerebral arteries is described. Also, we introduce a machine learning algorithm trained by the existing physiomic simulation data of flow reserve and suggest a prospective research direction related to this.
authors.affiliation: Department of Mechanical and Biomedical Engineering, Kangwon National University, Kangwondaehak-gil, Chuncheon-si, Kangwon-do, 200-701, Republic of Korea.
authors.forename: Kyung Eun
authors.initials: KE
authors.lastname: Lee
authors.affiliation: Department of Mechanical and Biomedical Engineering, Kangwon National University, Kangwondaehak-gil, Chuncheon-si, Kangwon-do, 200-701, Republic of Korea.
authors.forename: Ah-Jin
authors.initials: AJ
authors.lastname: Ryu
authors.affiliation: Department of Cardiology, University of Ulsan College of Medicine, Ulsan, South Korea.
authors.forename: Eun-Seok
authors.initials: ES
authors.lastname: Shin
authors.affiliation: Department of Mechanical and Biomedical Engineering, Kangwon National University, Kangwondaehak-gil, Chuncheon-si, Kangwon-do, 200-701, Republic of Korea. ebshim@kangwon.ac.kr.
authors.forename: Eun Bo
authors.initials: EB
authors.lastname: Shim
mesh_terms: D000818:Animals; D053805:Fractional Flow Reserve, Myocardial; D006801:Humans; D000069550:Machine Learning; D008955:Models, Cardiovascular; D000069336:Neurovascular Coupling
keywords: Cerebrovascular system; Coronary artery; Flow reserve; Physiomic approach