title: Model-based cardiovascular disease diagnosis: a preliminary in-silico study.
abstract: In this study, we developed and examined the feasibility of a model-based system identification approach to cardiovascular disease diagnosis. The basic premise of the approach is that it may be possible to diagnose cardiovascular disease from disease-induced alterations in the arterial mechanical properties manifested in the proximal and distal arterial blood pressure waveforms. It first individualizes the lumped-parameter model of wave propagation and reflection in the artery using the measurement of proximal and distal arterial blood pressure waveforms. Then, it employs a diagnosis logic, in the form of disease-specific patterns in model parameters, referred as [Formula: see text] and pulse transit time. The longitudinal change in these parameters is used to diagnose the presence of peripheral artery disease and arterial stiffening. We illustrated the feasibility of the proposed approach by testing it in a full-scale in-silico arterial tree simulation. The results showed that the approach exhibited superior sensitivity to ankle-brachial index and convenience to carotid-femoral pulse wave velocity: The model parameters [Formula: see text] and [Formula: see text] responded with up to 100 and 40 % changes to peripheral artery disease with up to 50 % arterial blockage whereas the change in ankle-brachial index was [Formula: see text]; the same parameters responded with up to 300 and 40 % changes to up to 100 % arterial stiffening while pulse transit time changed by up to 24 %. Together with the development of more convenient techniques for the measurement of arterial blood pressure waveforms, the proposed approach may evolve into a viable alternative to the state-of-the-art techniques for cardiovascular disease diagnosis.
authors.affiliation: Department of Mechanical Engineering, University of Alberta, Edmonton, AB, Canada.
authors.forename: Shiva
authors.initials: S
authors.lastname: Ebrahimi Nejad
authors.affiliation: Department of Mechanical Engineering, University of Alberta, Edmonton, AB, Canada.
authors.forename: Jason P
authors.initials: JP
authors.lastname: Carey
authors.affiliation: Department of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada.
authors.forename: M Sean
authors.initials: MS
authors.lastname: McMurtry
authors.affiliation: Department of Mechanical Engineering, University of Maryland, College Park, MD, 20742, USA. jhahn12@umd.edu.
authors.forename: Jin-Oh
authors.identifier: 0000-0001-5429-2836
authors.initials: JO
authors.lastname: Hahn
mesh_terms: D001158:Arteries / Q000473:pathology; D002318:Cardiovascular Diseases / Q000175:diagnosis*; D003198:Computer Simulation; D003935:Diagnostic Techniques, Cardiovascular; D006801:Humans; D008954:Models, Biological; D063177:Pulse Wave Analysis
keywords: Arterial stiffening; Cardiovascular disease; Diagnosis; Peripheral artery disease; System identification; Tube-load model