Pressure mapping from flow imaging: Enhancing computation of the viscous term through velocity reconstruction in near-wall regions

TY - CHAP

T1 - Pressure mapping from flow imaging

T2 - Enhancing computation of the viscous term through velocity reconstruction in near-wall regions

AU - Donati, Fabrizio

AU - Nordsletten, David A

AU - Smith, Nicolas P

AU - Lamata de la Orden, Pablo

PY - 2014/8

Y1 - 2014/8

N2 - Although being small compared to inertial acceleration, viscous component of the pressure gradient has recently emerged as a potential biomarker for aortic disease conditions including aortic valve stenosis. However, as it involves the computation of second order derivatives and viscous dissipation is locally higher in the near-wall region of the larger vessels, where the lowest local signal-to-noise ratios are encountered, the estimation process from medical image velocity data through mathematical models is highly challenging. We propose a fully automatic framework to recover the laminar viscous pressure gradient through reconstruction of the velocity vector field in the aortic boundary region. An in-silico study is conducted and the pressure drop is computed solving a Poisson problem on pressure using both a reconstructed and non-reconstructed velocity profile near the vessel walls, showing a global improvement of performance with the enhanced method.

AB - Although being small compared to inertial acceleration, viscous component of the pressure gradient has recently emerged as a potential biomarker for aortic disease conditions including aortic valve stenosis. However, as it involves the computation of second order derivatives and viscous dissipation is locally higher in the near-wall region of the larger vessels, where the lowest local signal-to-noise ratios are encountered, the estimation process from medical image velocity data through mathematical models is highly challenging. We propose a fully automatic framework to recover the laminar viscous pressure gradient through reconstruction of the velocity vector field in the aortic boundary region. An in-silico study is conducted and the pressure drop is computed solving a Poisson problem on pressure using both a reconstructed and non-reconstructed velocity profile near the vessel walls, showing a global improvement of performance with the enhanced method.

U2 - 10.1109/EMBC.2014.6944771

DO - 10.1109/EMBC.2014.6944771

M3 - Conference paper

C2 - 25571139

SN - 9781424479276

SP - 5097

EP - 5100

BT - 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014)

PB - IEEE

ER -