Estimating arterial properties from doppler signals in mice

Craig J. Hartley, Anilkumar K. Reddy, Lloyd H. Michael, Jennifer S. Pocius, Thuy T. Pham, Mark L. Entman, George Taffet

Research output: Contribution to journalConference articlepeer-review

Abstract

Mice are the animal of choice for genetic manipulations many of which affect the peripheral vascular system either directly or indirectly via compensatory responses. Traditional pressure and flow methods for assessing vascular function are invasive and difficult to apply to mice so we have been developing several noninvasive techniques using Doppler ultrasound to evaluate the peripheral vasculature in mice. Velocity signals can be obtained from most major peripheral arteries for evaluation of pulsatility and resistance indices, pulse wave velocity can be measured in the aorta and carotid arteries, and the simplified Bernoulli equation can be used to estimate the pressure drop across an aortic stenosis. By measuring velocity simultaneously at two closely spaced sites along an artery, a volume waveform can be generated directly, forward and backward waves can be computed, and pulse pressure can be estimated. Characteristic impedance can be calculated from pulse wave velocity and impedance spectra and reflection coefficients can be calculated. Thus, many of the basic characteristics of the cardiovascular system can be assessed noninvasively in mice using Doppler ultrasound.

Original languageEnglish (US)
Pages (from-to)268-271
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume1
StatePublished - 2003
EventA New Beginning for Human Health: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Cancun, Mexico
Duration: Sep 17 2003Sep 21 2003

Keywords

  • Carotid blood flow
  • Doppler ultrasound
  • Mice
  • Vascular modeling

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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