Physiome approach for the analysis of vascular flow reserve in the heart and brain.
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.
['Lee|Kyung Eun|KE|', 'Ryu|Ah-Jin|AJ|', 'Shin|Eun-Seok|ES|', 'Shim|Eun Bo|EB|']
D000818:Animals D053805:Fractional Flow Reserve, Myocardial D006801:Humans D000069550:Machine Learning D008955:Models, Cardiovascular D000069336:Neurovascular Coupling
Physiomic approach Flow reserve Coronary artery Cerebrovascular system