Artery Research (Dec 2017)

3.6 NON-INVASIVE, MRI-BASED ESTIMATION OF PATIENT-SPECIFIC AORTIC BLOOD PRESSURE USING ONE-DIMENSIONAL BLOOD FLOW MODELLING

  • Jorge Mariscal Harana,
  • Arna van Engelen,
  • Torben Schneider,
  • Mateusz Florkow,
  • Peter Charlton,
  • Bram Ruijsink,
  • Hubrecht De Bliek,
  • Israel Valverde,
  • Marietta Carakida,
  • Kuberan Pushparajah,
  • Spencer Sherwin,
  • Rene Botnar,
  • Jordi Alastruey

DOI
https://doi.org/10.1016/j.artres.2017.10.036
Journal volume & issue
Vol. 20

Abstract

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Background and objectives: Clinical evidence shows that central (aortic) blood pressure (CBP) is a better marker of cardiovascular risk than brachial pressure [1]. However, CBP can only be accurately measured invasively, through catheterisation. We propose a novel approach to estimate CBP non-invasively from aortic MRI data and a non-invasive peripheral (brachial) pressure measurement, using a one-dimensional (1-D) model of aortic blood flow. Methods: We created a population of virtual (computed) subjects, each with distinctive arterial pulse waveforms available at multiple arterial locations, to assess our approach. This was achieved by varying cardiac (stroke volume, cardiac period, time of systole) and arterial (pulse wave velocity, peripheral vascular resistance) parameters of a distributed 1-D model of the larger systemic arteries [2] within a wide range of physiologically plausible values. After optimising our algorithm for the aortic 1-D model in silico, we tested its accuracy in a clinical population of 8 post-coarctation repair patients. Results: Results from our in silico study, after varying cardiac and arterial parameters by ±30%, showed maximum relative errors for systolic, mean and diastolic CBP of 4.5%, 3.6% and 4.2%, respectively. Average relative errors for systolic, mean and diastolic CBP were 2.7%, 0.9% and 1.2%, respectively. Corresponding average relative errors from our clinical study were 5.4%, 1.5% and 8.0%. Figure 1CBP estimation using the aortic 1-D model for a given virtual patient. Figure 2Systolic CBP estimated using the aortic 1-D model against reference systolic CBP values from in silico and in vivo data. Conclusions: We have provided a proof of concept for the non-invasive estimation of patient-specific central blood pressure using computational aortic blood flow modelling in combination with MRI data and a non-invasive peripheral pressure measurement.