A 1D encoder-decoder deep network for pressure estimation from 4D flow MRI: in-vitro experiments

Ruponti Nath; Amirkhosro Kazemi; Sean Callahan; M. J. Negahdar; Marcus Stoddard; Amir Amini

doi:10.1117/12.2582196

15 February 2021 A 1D encoder-decoder deep network for pressure estimation from 4D flow MRI: in-vitro experiments

Ruponti Nath, Amirkhosro Kazemi, Sean Callahan, M. J. Negahdar, Marcus Stoddard, Amir Amini

Proceedings Volume 11600, Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging; 116000Y (2021) https://doi.org/10.1117/12.2582196
Event: SPIE Medical Imaging, 2021, Online Only

Abstract

In this paper we propose a deep learning framework to estimate pressure from 4D flow MRI. Pressure drop is an important parameter to detect and diagnose different cardiovascular diseases. Accurate estimation of pressure from 4D flow MRI is hampered however due to noise and low resolution of 4D flow data. In the proposed method we consider the pressure estimation as a mapping function between velocity to pressure and employ an encoder-decoder based deep network for the mapping. A computational fluid dynamic model was designed which identically matched the geometry of a stenotic flow phantom used in 4D Flow MRI experiments and velocity and pressure data was simulated for 1000 different flow conditions to train the network. In addition, the proposed network was tested on real in -vitro 4D flow MRI in the same stenotic model for 3 different flow rates. Estimated pressures from the network showed excellent agreement with the reference CFD simulated pressures. As measure of fidelity, relative pressure drop across the stenosis was computed between the reference pressure and estimated pressure and were compared with the simplified Bernouli method. It was determined that the pressure drop estimation by the proposed method is more accurate than competing method.

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Citation Download Citation

Ruponti Nath, Amirkhosro Kazemi, Sean Callahan, M. J. Negahdar, Marcus Stoddard, and Amir Amini "A 1D encoder-decoder deep network for pressure estimation from 4D flow MRI: in-vitro experiments", Proc. SPIE 11600, Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging, 116000Y (15 February 2021); https://doi.org/10.1117/12.2582196

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