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Biomechanics and Modeling in Mechanobiology

, Volume 16, Issue 2, pp 549–560 | Cite as

Model-based cardiovascular disease diagnosis: a preliminary in-silico study

  • Shiva Ebrahimi Nejad
  • Jason P. Carey
  • M. Sean McMurtry
  • Jin-Oh Hahn
Original Paper
  • 257 Downloads

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 \(\alpha , \beta \) 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 \(\alpha \) and \(\beta \) 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 \({<}5\,\%\); 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.

Keywords

Diagnosis Cardiovascular disease Peripheral artery disease Arterial stiffening System identification Tube-load model 

Notes

Acknowledgments

The authors thank Dr. Mette Olusfen at North Carolina State University for providing us with the arterial tree simulation. The authors also thank Ms. Karla Telidetzki and Mr. Mason Kim for their contributions to the arterial tree simulation.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringUniversity of AlbertaEdmontonCanada
  2. 2.Department of Medicine and DentistryUniversity of AlbertaEdmontonCanada
  3. 3.Department of Mechanical EngineeringUniversity of MarylandCollege ParkUSA

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