Merging computational fluid dynamics and 4D Flow MRI using proper orthogonal decomposition and ridge regression

JOURNAL OF BIOMECHANICS

卷:58

Article

Bakhshinejad, Ali¹  Baghaie, Ahmadreza²  Vali, Alireza³  Saloner, David⁴  Rayz, Vitaliy L.²  D'Souza, Roshan M.¹ 

[1] Univ Wisconsin, Dept Mech Engn, Milwaukee, WI 53201 USA

[2] Purdue Univ, Dept Biomed Engn, W Lafayette, IN 47907 USA

[3] Northwestern Univ, Dept Radiol, Evanston, IL 60208 USA

[4] Univ Calif San Francisco, Dept Radiol, Coll Med, San Francisco, CA USA

关键词: 4D-PCMR;    4D Flow MRI;    Flow reconstruction;    POD;    Proper orthogonal decomposition;    Computational fluid dynamic;   

DOI  :  10.1016/j.jbiomech.2017.05.004

来源: Elsevier

【 摘 要 】

Time resolved phase-contrast magnetic resonance imaging 4D-PCMR (also called 4D Flow MRI) data while capable of non-invasively measuring blood velocities, can be affected by acquisition noise, flow artifacts, and resolution limits. In this paper, we present a novel method for merging 4D Flow MRI with computational fluid dynamics (CFD) to address these limitations and to reconstruct de-noised, divergence-free high-resolution flow-fields. Proper orthogonal decomposition (POD) is used to construct the orthonormal basis of the local sampling of the space of all possible solutions to the flow equations both at the low-resolution level of the 4D Flow MRI grid and the high-level resolution of the CFD mesh. Low-resolution, de-noised flow is obtained by projecting in vivo 4D Flow MRI data onto the low resolution basis vectors. Ridge regression is then used to reconstruct high-resolution de-noised divergence-free solution. The effects of 4D Flow MRI grid resolution, and noise levels on the resulting velocity fields are further investigated. A numerical phantom of the flow through a cerebral aneurysm was used to compare the results obtained using the POD method with those obtained with the stateof-the-art de-noising methods. At the 4D Flow MRI grid resolution, the POD method was shown to preserve the small flow structures better than the other methods, while eliminating noise. Furthermore, the method was shown to successfully reconstruct details at the CFD mesh resolution not discernible at the 4D Flow MRI grid resolution. This method will improve the accuracy of the clinically relevant flow derived parameters, such as pressure gradients and wall shear stresses, computed from in vivo 4D Flow MRI data. (C) 2017 Elsevier Ltd. All rights reserved.

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