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Journal Articles Inverse Problems Year : 2023

Flow recovery from distal pressure in linearized hemodynamics: an optimal control approach

Abstract

The goal of this work is to derive a reliable stable and accurate inverse problem strategy for reconstructing cardiac output blood flow entering the ascending aorta from pressure measurements at a distal site of the arterial tree, assumed here to be the descending aorta. We assume that a reduced one-dimensional model of the aorta can be linearized around its steady state, resulting in a wave system with absorbing boundary condition at the outlet. Using this model, we attempt to reconstruct the inlet flow from a pressure measurement at the distal outlet. First, we investigate the observability of the problem and prove that the inversion of the input-output operator for the flow and pressure in the space of time-periodic solutions is ill-posed of degree one. We then develop a variational approach where we minimize the discrepancy between measurements and a simulated state and penalize the error with respect to a periodic state. It is shown that the penalty strategy is convergent and provides an efficient solution for the minimization. Numerical results illustrate the robustness of our approach to noise and the potential of our method to reconstruct inlet flow from real pressure recordings during anesthesia.
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hal-04178851 , version 1 (08-08-2023)

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Sébastien Imperiale, Jessica Manganotti, Philippe Moireau. Flow recovery from distal pressure in linearized hemodynamics: an optimal control approach. Inverse Problems, 2023, 39 (7), pp.075004. ⟨10.1088/1361-6420/acd274⟩. ⟨hal-04178851⟩
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